Literature DB >> 35196337

Value of D-dimer in predicting various clinical outcomes following community-acquired pneumonia: A network meta-analysis.

Jiawen Li1, Kaiyu Zhou1, Hongyu Duan1, Peng Yue1, Xiaolan Zheng1, Lei Liu1, Hongyu Liao1, Jinlin Wu1, Jinhui Li1, Yimin Hua1, Yifei Li1.   

Abstract

BACKGROUND: Whether high D-dimer level before treatment has any impact on poor outcomes in patients with community-associated pneumonia (CAP) remains unclear. Therefore, we conducted the first meta-analysis focusing specifically on prognostic value of high D-dimer level before treatment in CAP patients.
METHODS: Pubmed, Embase, the Cochrane Central Register of Controlled Trials and World Health Organization clinical trials registry center were searched up to the end of March 2021. Randomized clinical trials (RCT) and observational studies were included to demonstrate the association between the level of D-dimer and clinical outcomes. Data were extracted using an adaptation of the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS-PF). When feasible, meta-analysis using random-effects models was performed. Risk of bias and level of evidence were assessed with the Quality in Prognosis Studies tool and an adaptation of Grading of Recommendations Assessment, Development, and Evaluation. Data were analyzed using STATA 14.0 to complete meta and network analysis. MAIN OUTCOMES AND MEASURES: Besides d-dimer levels in CAP patients with poor outcomes, we also analyzed proportion of patients with or without poor outcomes correctly classified by the d-dimer levels as being at high or low risk. The poor outcome includes severe CAP, death, pulmonary embolism (PE) and invasive mechanical ventilators.
RESULTS: 32 studies with a total of 9,593 patients were eventually included. Pooled effect size (ES) suggested that d-dimer level was significantly higher in severe CAP patients than non-severe CAP patients with great heterogeneity (SMD = 1.21 95%CI 0.87-1.56, I2 = 86.8% p = 0.000). D-dimer level was significantly elevated in non-survivors compared to survivors with CAP (SMD = 1.22 95%CI 0.67-1.77, I2 = 85.1% p = 0.000). Prognostic value of d-dimer for pulmonary embolism (PE) was proved by hierarchical summary receiver operating characteristic curve (HSROC) with good summary sensitivity (0.74, 95%CI, 0.50-0.89) and summary specificity (0.82, 95%CI, 0.41-0.97). Network meta-analysis suggested that there was a significant elevation of d-dimer levels in CAP patients with poor outcome than general CAP patients but d-dimer levels weren't significantly different among poor outcomes.
CONCLUSION: The prognostic ability of d-dimer among patients with CAP appeared to be good at correctly identifying high-risk populations of poor outcomes, suggesting potential for clinical utility in patients with CAP.

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Year:  2022        PMID： 35196337      PMCID： PMC8865637          DOI： 10.1371/journal.pone.0263215

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

Community-acquired pneumonia (CAP) is defined as pneumonia acquired outside the hospital and has led to life-years lost globally [1]. Approximately 6.6% to 16.7% of hospitalized patients with CAP would enter the severe stage. Unfortunately, mortality rate is supposed to reach up to 28.8% among patients with severe CAP [2]. A considerable proportion of patients with CAP in the emergency department can be treated as outpatients. However, unpredictable disease course and uncertain outcomes are challenges for clinicians, hindering the early identification of patients at high risk. Several risk scores, such as the pneumonia severity index (PSI) and CURB-65 (confusion, urea nitrogen, respiratory rate, blood pressure, age ≥65 years), can be used to assess the severity of pneumonia and predict prognosis [3-5]. For CAP, low risk was defined as PSI score classes I to III and CURB-65 score class 1. High risk was defined by PSI score classes IV-V and CURB-65 score classes 2–5. However, they were more suitable for research than clinical decision and their performance is still controversial [6]. C-reactive protein (CRP) [7, 8] and procalcitonin (PCT) [9, 10] had been reported be a prognostic marker of outcome during severe CAP and ventilator-associated pneumonia (VAP). D-dimer is the fibrinolytic degradation products of crosslinked fibrin and is applied as a useful marker for the diagnosis of pulmonary embolism. It mirrors the severity of infection and has emerged as the extensively studied and promising blood biomarker for the risk stratification of patients with CAP [11-13]. However, whether d-dimer level is an ideal index to predict the prognosis of community-acquired pneumonia remains debatable [14, 15], because no relevant studies focusing on d-dimer levels before treatment in patients with CAP were available to conduct meta-analyses previously. For this reason, a meta-analysis was performed to systematically and quantitatively evaluate the prognostic accuracy of the d-dimer level before treatment in CAP. To our knowledge, this is the first meta-analysis specifically focusing on d-dimer levels in patients with CAP. In consideration of different disease process and different therapeutical strategies of COVID-19 due to its distinct biology and pathogen, we haven’t included publications of COVID-19 to prevent unsolvable heterogeneity.

Materials and methods

Study protocol

This analysis was conducted in accordance with a predetermined protocol following the recommendations of a guideline for systematic reviews of prognostic factor studies [16]. And the data collection and reporting was in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement [17] and Extension Statement for Reporting Network Meta-Analyses [18]. (PROSPERO; CRD42020184704)

Search strategy

We searched the Pubmed, Embase, the Cochrane Central Register of Controlled Trials and World Health Organization clinical trials registry center using a comprehensive strategy to get the publications. The strategy was “(("pneumonia"[MeSH Terms] OR (community-acquired [All Fields] AND "pneumonia"[MeSH Terms])) OR ("pneumonia"[MeSH Terms] OR "pneumonia"[All Fields])) AND ("fibrin fragment D"[Supplementary Concept] OR "fibrin fragment D"[All Fields] OR "d dimer"[All Fields])”. Search was updated to the end of March 23, 2021 with language restricted to English.

Study selection

Titles and abstracts of search results were screened independently (Jiawen Li, Hongyu Duan). The full texts of the remaining results were assessed independently by another 2 of us (Yifei Li, Yimin Hua) for inclusion based on predetermined criteria. Any discrepancies should be resolved through discussion, potentially with a third reviewer. We manually searched the reference lists of included studies and existing systematic reviews as well as all articles citing the included studies on Google Scholar. Potentially relevant reports were then retrieved as complete manuscripts and assessed for compliance to inclusion and exclusion criteria. In accordance to the objectives of our meta-analysis, we developed a ‘Population, Index prognostic factor, Comparator prognostic factor, Outcome, Timing, Settings’ (PICOTS) framework adapted from the guideline proposed by Riley et al [16]. Our study inclusion criteria were as follows according to PICOTS framework: (1)Population: CAP patients with a well-defined diagnostic reference standard for pneumonia; (2)Index prognostic factor: before-treatment d-dimer levels measured by enzyme-linked immunosorbent assay (ELISA), quantitative latex assay, immunoturbidimetric or other convinced assay machine; (3)Outcome: severe CAP patients identified by PSI, CURB-65 or other definitive scale, pulmonary embolism (PE), death or invasive ventilation. (6) If studies were based on overlapping patients, the most completed one was chosen. We used the following criteria for study exclusion: (1) patients acquired pneumonia in clinical settings (e.g. VAP or hospital-acquired pneumonia (HAP)); (2) studies were published in other language; (3) conference abstracts, reviews, case reports, and experiment studies.

Data extraction and study quality assessment

Two reviewers (Jiawen Li, Hongyu Duan) independently extracted study data and assessed risk of bias, with discrepancies resolved by a third investigator in a blinded fashion. Quality of evidence was assessed by the modified Grading of Recommendations Assessment, Development, and Evaluation system (GRADE) by consensus among the authors [19, 20]. The essential data was extracted according to the modification of CHARMS (checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies) for prognostic factors (CHARMS-PF) [16]. When an included study reported different cut-off values, we chose one which made both sensitivity and specificity more than 50% as possible. When an included literature reported the same outcome at different follow-up timepoint (e.g. 7-days mortality and 30-days mortality), we chose the earliest one. We extracted data of PSI if included studies reported severity of CAP by both PSI and CURB-65. Mean and standard deviation were estimated based on sample size, median and quartile if included studies did not reported mean and standard deviation [21, 22]. All the baseline characteristics of included studies were shown on Table 1.
Table 1

Basic characteristics of included studies.

AuthorCountryYearStudy designprimary outcomeMeasured AssaySample sizeMale (%)AgeComparisonNumber of clinical centers
Agapakis [31]Greece2010PRSeverityImmunoturbidimetric assay10861.165.11±8.34CAP VS healthySingle
Arslan [32]China2010RESeverityLatex immunoassay8446.461.67 imm75CAP VS healthySingle
Castro [45]Spain2001PRPEELISA10146.546.23±12.19CAP VS PESingle
Chalmers [33]England2009PRMortalityVitek ImmunoDiagnostic Assay System31453.8N/ASurvivor VS NoSingle
Chen [50]China2020REMortalityNot available17966.565.0 (53.0–79.0)Survivor VS non-survivalSingle
Dai [51]China2018REMortalityNot available52055.2N/ASurvivor VS non-survivalSingle
Nastasijević [39]Serbia2014RESeverity and MortalityLatex immunoassay12959.764.8x immuSeverity, survival VS non-survivalSingle
Duarte [56]Portugal2015PRSeverityNot available10263.780.49v11.41NoSingle
Mikaeilli [38]Turkey2016PRPEImmunoturbidimetric method7238.267.64±12.49PE VS CAPSingle
Ho [46]Australia2013REPENot available47248.461.15vaila6NoSingle
Jin [35]China2018PRSeverityImmunoassay27750.53.32CAP VS ControlSingle
Kline [47]USA2012PRSeverityELISA27738.055.06PE VS ControlMulticenter -
Kobayashi [52]Japan2016REMortalityNot available315345.361.99vail28Survivors VS non-survivalSingle
Single
Krykhtina [60]Ukraine2019RECAPImmunoturbidimetric method918048.0 [33.0–61.0]CAP VS HealthySingle
Li [61]China2017RE,CCSeverityD-dimer assay kit30257.38.10±1.80CAP VS HealthySingle
Luo [48]China2014PRPEELISA5750.961.36±10.70PE VS Non-PESingle
Cerda-Mancillas [11]Mexico2020PRseverityfluorescence immunoassay5271.6 ± 15SeveritySingle
IMV VS Non-IMV
Vasopressor vs Non-vasopressor
Survivor VS non-survival
Marinkovic [37]North Macedonia2016RESeverityLatex immunoassay19258.953.97±17.71CAP VS PESingle
Michelin [59]Italy2008RESeverityD-dimer assay kit39-5.58 (2–174 months)Severity of CAPSingle
Mikaeilli [38]Iran2009REMortalityELISA603547.12lityofSurvivor VS non-survivalSingle
MilbrandtUSA2009PRSeverity and MortalityLatex immunoassay93951.469.20±15.80Survivor VS non-survivalSingle
Ning Li [36]China2018RESeverityimmunoturbidimetric method9646.917.81±3.48SeveritySingle
Güneysel [34]Greece2004PRSeverityELISA6855.957.80±16.50healthy VS CAP VS severe CAPSingle
Paparoupa [49]Germany2016REPED-Dimer Test Innovance from Siemens905866.40±17.50CAP VS healthySingle
Pereira [53]Portugal2019PRMortalityImmunoturbidimetric assays1076562.00±15.70survival VS non-survivalSingle
Pertseva [40]Ukraine2019RESeverityImmunoturbIdimetric assays7354.0 [37.0–63.0]SeveritySingle
Querol-Ribelles [41]Spain2004PRSeverity and MortalityAutomated latex assay30274.873.00different clinical outcomeSingle
Salluh [54]Brazil2011PRMortalityCoagulation A Not available lyzer9044.473.5(57.7–83)suvivors VS non-survival, complications VS non-complicationsSingle
Shilon [42]Israel2003PRSeverityMiniquant D-dimer assay684067.00±20.80CAP VS healthySingle
Snijders [43]Netherlands2012PRSeverityELISA14753.763.1AitynCAP VS healthySingle
Yende [55]USA2011PRMortalityLatex immunoassay89351.268.7 (15, 73)Survivors VS non-survivalMulticenter
Zhang [58]China2015REPEImmunoturbidimetry13947.4870.73PE VS Non-PESingle

Data are presented as n (%), mean±standard deviation or median (interquartile range)

PE = pulmonary embolism. ELISA = enzyme-linked immunosorbent assay, PR = prospective cohort study, RE = retrospective cohort study, CC = case-control study, IMV = invasive mechanical ventilation

Data are presented as n (%), mean±standard deviation or median (interquartile range) PE = pulmonary embolism. ELISA = enzyme-linked immunosorbent assay, PR = prospective cohort study, RE = retrospective cohort study, CC = case-control study, IMV = invasive mechanical ventilation The included studies were further investigated for risk of bias using an adapted version of the Quality in Prognosis Studies (QUIPS) tool [23], which assessed the study-specific risk of bias across to six bias domains: study participation, study attrition, prognostic factor measurement, outcome, measurement, study confounding, statistical analysis and reporting. A study that satisfied the criteria of low risk of bias in all 6 domains was designated as having low overall risk of bias. A study with a high risk of bias in 1 or more domains was designated as having high overall risk of bias. Details on each signaling question of the QUIPS tool are elaborated on Table 2. We did not exclude any publication with high risk of bias according to QUIPS.
Table 2

Quality assessment of individual studies using the QUIPS instrument.

StudyStudy ParticipationStudy AttritionPrognostic Factor MeasurementOutcome MeasurementStudy ConfoundingStatistical Analysis and ReportingOverall Assessment
Agapakis 2010 LLMLHLH
Arslan 2010 HHLLMLH
Castro 2001 LMLMLLM
Chalmers 2009 LLLLMLM
Dai 2018 LLLMLLM
Nastasijević 2014 HMLLHLH
Mikaeilli 2016 HMLLHLH
Ho 2013 LLMLLLM
Jin 2018 LMMLHLH
Kline 2012 LLLLMLM
Kobayashi 2016 LLLMMLM
Krykhtina 2019 HLLLHLH
Li 2017 HLLLHLH
Cerda-Mancillas 2020 HLLLMHH
Marinkovic 2016 HHLLHMH
Michelin 2008 HLLLMLH
Mikaeilli 2009 MHLLHMH
Milbrandt 2009 LLLLMLM
Oziem 2004 HHLMHLH
PaparoMpa 2016 HHLLMLH
Pertseva 2019 HLLLHLH
Pereira 2019 LLLLLLL
Querol-Ribelles 2004 LLLLHLH
Salluh 2011 HLLLHLH
Shilon 2003 HLLLHLH
Snijders 2012 LLLLLLL
Yende 2011 LLLLHLH
Zhang 2016 HLLLHLH

Low: Low risk of bias; Moderate: Moderate risk of bias; High: High risk of bias. U: Unclear.

Low: Low risk of bias; Moderate: Moderate risk of bias; High: High risk of bias. U: Unclear.

Statistical analysis

Analyses were performed for both adjusted and unadjusted estimates. To combine comparative continuous data with dichotomous data, we transformed logarithm odds ratios to effect size, assuming a normal underlying distribution [24] Quantitative synthesis was first conducted by comparing the d-dimer levels of CAP patients with various outcome. The between-study heterogeneity was evaluated by the χ2-based Q statistics and I2 test, and a significant heterogeneity was as P<0.1 [25] or I2>50%. When significant heterogeneity was observed, we would apply the random effects models for analysis. Otherwise, we would apply the fixed effects models. A sensitivity analysis was also conducted by sequential removal of each study. Here, we applied funnel plots as well as Egger’s test [26] to assess publication bias. A two-sided P value of 0.05 was deemed as statistical significance. The proportion patients with poor outcome correctly classified by the d-dimer levels as high risk was defined by dividing true-positive results by the sum of true-positive and false-negative results. The proportion of patients without poor outcome correctly classified by the d-dimer levels as low risk was defined by dividing true-negative results by the sum of true-negative and false-positive results. It was similar in concept to sensitivity and specificity although sensitivity and specificity are more appropriately reported at a particular time point in prognostic studies. Dose-response meta-analysis (DRMA) was conducted only for adjusted outcomes with more than 3 categories of exposures. When pooled effects had significant heterogeneity, and included more than 9 studies, subgroup analyses were carried out based on methodologies of d-dimer measurements, study design, location, sample size, risk of bias, number of categories and effect size type. For network meta-analysis, we evaluated global inconsistency by fitting consistency and inconsistency model [27], and evaluated local inconsistency between direct and indirect estimates by using a node-splitting procedure [28]. In order to further quantify the d-dimer level of various outcome, we calculated the frequentist analogue of the surface under the cumulative ranking curve (SUCRA) for each outcome [29]. Data was analyzed using STATA Version 14.0 [30]. The network was evaluated using frequentist multivariate meta-analysis (commands network meta and mvmeta) in Stata 14.0. Besides, publication bias and sensitivity analysis were also conducted by STATA version 14.0.

Result

Nine-hundred and twenty-five articles were retrieved from databases, of which 32 studies with a total of 9,593 patients were eventually included (Fig 1). No additional relevant articles were identified in the bibliographies of the original articles. The characteristics of the included studies are listed in Table 1.
Fig 1

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram for study identification and selection.

Characteristics of included studies

D-dimer levels were reported in 14 studies [11, 31–43] associated with severity, 6 [44-49] with PE, 12 [11, 38, 39, 41–43, 45, 50–54] with mortality and 3 [38, 39, 41] with invasive mechanical ventilator. All included studies were observational. Two [47, 55] of them were multicenter and eleven [31, 33, 34, 37, 39, 42, 43, 45, 48, 54, 55] were prospective observational studies. Five studies [32, 33, 38, 39, 41] reported d-dimer levels of different severity by class I to class V so that we combined means and standard deviation (SD) into two groups (severe CAP VS Non-severe CAP) by StatsToDo. Three studies reported dichotomous outcomes according to different categories of d-dimer without adjusted effect size and confidence interval (or standard error) compared to reference category. Therefore, dose-response meta-analysis is unavailable.

D-dimer measurement

Recommended thresholds of different d-dimer assays varied widely across studies. Cut-off values were determined as 500 or 1000 ng/mL in 7 studies [33, 41, 48, 53, 56–58]. ELISA method was used in 7 studies [34, 35, 38, 43, 45, 48, 59]; immunoturbidimetric methods were used in 7 studies [31, 36, 37, 40, 44, 53, 60] and quantitative latex assay were launched in six studies [32, 37, 39, 41, 55, 57]. The rest of included studies only reported D-dimer kit, automatic analytical instrument, but not revealed their assay methods.

Assessment of methodological quality

QUIPS tool had been used to assess the quality of included studies (Table 2). Among all the 32 studies, 20 were high risk of bias [11, 31, 32, 34, 35, 37–42, 44, 49, 54–56, 58–61], 2 studies were evaluated as low risk of bias [43, 53] and the remaining 10 studies had medium risk of bias. The number of individual domains rated as high risk ranged from 0 to 3.

The association between D-dimer level and clinical outcomes

Severity

We excluded one study [59] for quantitative synthesis because it simply defined severe CAP as pneumonia with pleural effusion. Twelve studies [11, 31, 32, 34, 35, 37–43] including 1,394 participants reported the plasma d-dimer level of both severe CAP and non-severe CAP patients. Pooled effect size (ES) suggested d-dimer level was significantly higher in severe CAP patients than non-severe CAP patients with great heterogeneity (SMD = 1.21 95%CI 0.87–1.56, I2 = 86.8% p = 0.000) (Fig 2) and pooled result with adjusted OR [36, 43] (OR = 1.07 95%CI 1.01–1.13, I2 = 60.2% p = 0.113) was consistent with continuous data (S1 Fig). By subgroup analysis, conversion of median and quartiles, combination of mean and SD, methodologies of d-dimer measurements, high risk of bias and tools of d-dimer measurement did not contribute to heterogeneity significantly.
Fig 2

Forest plot of D-dimer in severe CAP versus non-severe CAP patients.

The size of the square is proportional to study-specific statistical weights, horizontal lines represent 95% confidence interval (CI) and diamonds represent summary measures of association. SMD, standardized mean difference; ES, effect size. CAP, community-acquired pneumonia.

Forest plot of D-dimer in severe CAP versus non-severe CAP patients.

The size of the square is proportional to study-specific statistical weights, horizontal lines represent 95% confidence interval (CI) and diamonds represent summary measures of association. SMD, standardized mean difference; ES, effect size. CAP, community-acquired pneumonia. Sensitivity analysis of pooled ES of continuous data suggested that no study contribute much to the pooled estimate as our findings remained consistent (S2 Fig). Funnel plots were used to assess publication bias. We detected asymmetry in the funnel plot which was further ascertained by Egger’s test (P = 0.031; Fig 3), suggesting the presence of publication bias.
Fig 3

Funnel plot with Egger’s test for d-dimer levels and severity.

Unadjusted effect estimates from individual studies were plotted against their standard error. Solid and dashed lines represent the summary effect estimate and its 95% confidence intervals for different values of the standard error, respectively. Egger’s test estimated bias: p = 0.031. (A) Funnel plot assessing publication bias in RCTs investigating the effectiveness of different types of respiratory PPE against clinical (influenza-like illness and clinical respiratory illness) or laboratory-confirmed outcomes (influenza or other viral or bacterial respiratory infections); Harbord’s estimated bias coefficient: -0.59; p = 0.592.

Funnel plot with Egger’s test for d-dimer levels and severity.

Unadjusted effect estimates from individual studies were plotted against their standard error. Solid and dashed lines represent the summary effect estimate and its 95% confidence intervals for different values of the standard error, respectively. Egger’s test estimated bias: p = 0.031. (A) Funnel plot assessing publication bias in RCTs investigating the effectiveness of different types of respiratory PPE against clinical (influenza-like illness and clinical respiratory illness) or laboratory-confirmed outcomes (influenza or other viral or bacterial respiratory infections); Harbord’s estimated bias coefficient: -0.59; p = 0.592.

Mortality

Mortality associated with CAP was an important clinical outcome. 12 articles had been included to make quantitative analysis. Among them, 10 articles [11, 38, 39, 41–43, 50, 52–54] including 4,117 participants reported the plasma D-dimer level of survivors and non-survivors with CAP, which confirmed significant elevation of D-dimer level in non-survivors (SMD = 0.90 95%CI 0.62–1.17, I2 = 59.4% p = 0.008) (Fig 4). In spite of great heterogeneity, the pooled ES was robust by sensitivity analysis (S3 Fig). Pooled results of adjusted ORs from 4 studies [51–53, 55] have confirmed the prognostic value of increased D-dimer (OR = 2.23 95%CI 1.15–3.31, I2 = 0.0% p = 0.791) (S4 Fig).
Fig 4

Forest plot of D-dimer in non-survivors versus survivors with CAP.

There was a significant elevation of D-dimer level in non-survivors with great of heterogeneity between trials. CAP, community-acquired pneumonia.

Forest plot of D-dimer in non-survivors versus survivors with CAP.

There was a significant elevation of D-dimer level in non-survivors with great of heterogeneity between trials. CAP, community-acquired pneumonia. The presence of asymmetric distribution of funnel plots suggested that there might be publication bias in pooled result of continuous data (S5 Fig). Paradoxically, qualitative analysis by Egger’s test did not indicate publication bias (p = 0.168).

Pulmonary embolism

Pooled effect based on continuous data from three studies suggest a significant elevation in CAP patients with PE than those without PE (SMD = 0.75 95%CI 0.11–1.38, I2 = 84.5% p = 0.002) (S6 Fig). As there were only three enrolled studies, the publication bias and subgroup analysis were unavailable. However, data from a series of studies could be converted to the form of fourfold table of diagnostic test to demonstrate the prognostic value of D-dimer in high-risk population of PE. A diagnostic meta-analysis assessment was made to further investigate the prognostic role of D-dimer. The summary sensitivity was 0.74 (95%CI, 0.50–0.89), with significant heterogeneity (P = 0.0001, x2 = 26.86, I2 = 81.4%) (S7 Fig). The summary specificity was 0.82 (95%CI, 0.41–0.97), and the pooled estimation showed significant heterogeneity (P = 0.0000, x2 = 498.29, I2 = 99.0%) (S7 Fig). HSROC curve showed potential prognostic value of d-dimer levels for patients at high risk of mortality with CAP (Fig 5).
Fig 5

HSROC for d-dimer levels and occurrence of pulmonary embolism in patients with CAP.

HSROC, hierarchical summary receiver operating characteristic curve.

HSROC for d-dimer levels and occurrence of pulmonary embolism in patients with CAP.

HSROC, hierarchical summary receiver operating characteristic curve.

Others

Pooled effects suggested patients with CAP had a higher level of d-dimer compared to healthy participants (SMD = 0.88, 95%CI 0.54–1.22, I2 = 57.9%, p = 0.037) (S8 Fig) and D-dimer was significantly further elevated in patients requiring invasive mechanical ventilator (SMD = 1.01, 95%CI 0.69–1.33, I2 = 0.0%, p = 0.815) (S9 Fig).

Network analysis

We pooled effects of different outcomes by network meta-analysis of frequentist statistics (S10 Fig) and loop inconsistency test suggested significant heterogeneity between direct and indirect comparisons (S11 Fig). The results provide evidence that there was significant elevation of d-dimer levels in CAP patients with poor outcomes than general CAP patients. But wide 95% prediction interval cross null value (0) reminded us potential heterogeneity of included studies (Fig 6). D-dimer levels weren’t significantly different among poor outcomes although the SUCRA statistic showed that d-dimer level in CAP patients requiring mechanical ventilators ranked first, followed by non-survivors, severe patients and patients with PE. (S12 Fig). Funnel plots suggested potential publication bias based on its slight asymmetry (S13 Fig).
Fig 6

Forest plot of network meta-analysis of SMD of d-dimer levels of patients with different outcomes.

The red lines show prediction interval of future research. PrI = prediction interval. SMD = standardized mean difference.

Forest plot of network meta-analysis of SMD of d-dimer levels of patients with different outcomes.

The red lines show prediction interval of future research. PrI = prediction interval. SMD = standardized mean difference.

Quality of evidence

Most of included studies are retrospective observational studies and had high or moderate risk of bias. Great heterogeneity existed in pooled effects and contributed to inconsistency of evidence. Based on GRADE system and the above considerations, the quality of evidence of our study should be low or very low.

Discussion

Our study is the first meta-analysis ever published about prognostic value of D-dimer in patients with CAP. It shows that elevated d-dimer level is significantly associated with CAP severity, mortality and PE occurrence in general analysis regardless their age, gender, race and region and the type of assay of d-dimer measurement. With the aid of method of diagnostic meta-analysis, we confirmed prognostic value of d-dimer for high-risk population of PE in patients with CAP. Although we were unable to establish a firm evidence on the independent prognostic value of d-dimer levels, our results on d-dimer levels were consistent and robust. Network meta-analysis further confirmed the evidence of conventional meta-analysis and suggested d-dimer levels were not significantly different in various poor outcomes. This biomarker may be helpful in the early identification of patients with high risk of poor outcomes to make special therapeutic strategy as soon as possible. Previous studies reported that patients with elevated D-dimer levels were more likely to suffer from thromboembolism [62], digestive cancer [63], traumatic brain injury [64], and aortic dissection [65], which are associated with coagulation disorders. However, the pathophysiology of D-dimer elevation in CAP is only partially understood. Indeed, D-dimer elevation has also been observed in children and adults without any symptoms of pneumonia. Elevation of D-dimer had been reported to be correlated with several inflammatory and coagulation factors, including C-reaction protein, procalcitonin, IL-6, prothrombin time (PT), activated partial thromboplastin time (APTT) and thrombin time (TT) [7, 9, 66, 67]. Besides, several studies showed some patients with high d-dimer levels who died from severe CAP did not present obvious disorders of coagulation function [31]. As an unconventional detection index, the value of d-dimer varied widely across different studies, resulting in great unmanageable heterogeneity in pooled effects. This is partly because of diverse measuring apparatus and assays. The primary outcome is problematic for time-to-event analyses, particularly if studies have short follow-up and significant censoring. On the other hand, it is difficult to make subgroup analysis because of limited number of included studies and insufficiently reported data to make stratification. D-dimer is only reported as a confounding factor in most of included studies so the data from them is unable to support to make dose-response meta-analysis. Moreover, given the heterogeneity in study designs and data reporting, as well as the lack of availability of individual patient data, meta-analysis of hazard ratios was not feasible. There is uncertain statistical bias in combine means and SDs into one group and estimating the sample mean and SD from the sample size, median, range and/or interquartile range.

Conclusion

This study found that the prognostic ability of d-dimer to predict multiple poor outcomes among patients with CAP. But it is difficult to distinguish high-risk populations of different poor outcomes according to d-dimer levels. Additional, more rigorously structured research appears to be needed to better quantify the association of d-dimer levels with poor outcomes in patients with CAP and to demonstrate clinical utility.

Forest plot of pooled ORs of D-dimer in severe CAP versus non-severe CAP patients.

OR, odds ratio. CAP, community-acquired pneumonia. (TIF) Click here for additional data file.

Sensitivity analysis of the individual trials on the results for plasma D-dimer level associated with severity.

(TIF) Click here for additional data file.

Sensitivity analysis of the individual trials on the results for plasma D-dimer level associated with mortality.

(TIF) Click here for additional data file.

Forest plot of pooled ORs of D-dimer in survivors versus non-survivors with CAP.

CAP, community-acquired pneumonia. (TIF) Click here for additional data file.

Funnel plot with Egger’s test for association between d-dimer levels and mortality.

(TIF) Click here for additional data file.

Forest plot of D-dimer in CAP patients with or without PE.

CAP, community-acquired pneumonia. PE, pulmonary embolism. (TIF) Click here for additional data file.

Forest plot of pooled sensitivity and pooled specificity for d-dimer levels and occurrence of pulmonary embolism.

(TIF) Click here for additional data file.

Forest plot of D-dimer in CAP patients versus healthy participants.

SMD, standardized mean difference; CAP, community-acquired pneumonia. (TIF) Click here for additional data file.

Forest plot of D-dimer in common CAP patients versus CAP patients requiring invasive mechanical ventilators.

SMD, standardized mean difference; CAP, community-acquired pneumonia. (TIF) Click here for additional data file.

The network meta-analysis of available comparisons of d-dimer levels of patients with various outcomes.

The line width is proportional to the number of trials performed between two outcomes. Circle size is proportional to the total number of patients for each clinical outcome in the network. (TIF) Click here for additional data file.

The examination of loop inconsistency.

RoR: The rate ratio of logarithms of two ORs of direct and indirect comparisons. (TIF) Click here for additional data file.

Results of network rank test and the surface under the cumulative ranking curve (SUCRA).

(TIF) Click here for additional data file.

Comparison-adjusted funnel plot for d-dimer levels of patients with various clinical outcomes.

(TIF) Click here for additional data file.

Extracted data for meta-analyses.

(XLSX) Click here for additional data file. (DOC) Click here for additional data file. 16 Feb 2021 PONE-D-20-17727 Assessment the value of D-dimer in predicting various clinical outcomes following CAP: A network meta-analysis PLOS ONE Dear Dr. Li, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Apr 02 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, Cho Naing, MBBS, PhD, FRCP Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Thank you for stating the following financial disclosure: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." 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To take advantage of our partnership with Editage, visit the Editage website (www.editage.com) and enter referral code PLOSEDIT for a 15% discount off Editage services.  If the PLOS editorial team finds any language issues in text that either AJE or Editage has edited, the service provider will re-edit the text for free. Upon resubmission, please provide the following: The name of the colleague or the details of the professional service that edited your manuscript A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file) A clean copy of the edited manuscript (uploaded as the new *manuscript* file) Additional Editor Comments: The methodology is insufficient. Moreover, the selection criteria is not clear. It will be more meaningful and well focused to include randomized controlled trials, rather than non-randomized studies The assumptions required for a network- meta analysis are not addressed in the methods, and a lack of reporting them in the results. Thank you [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: I Don't Know Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors Li et al presented their network meta-analysis on the utility of D-dimer as biomarkers of community-acquired pneumonia. While the paper has merit, this is hardly suitable for publication at this stage. 1. English used are mostly non-standard, contain a lot of errors and may create confusion. This alone warrants a major revision. I strongly urge a scientific English editing before going to the next review round. I would not go for the next round of review unless the authors provided evidence of scientific english editing. I have limited myself to review up to methodology section and a few tables only and hold it on until sufficient english editing is done for reviewing further. 2. The authors claimed of using Cochrane Handbook for their analysis. Which Cochrane Handbook was used? I understand there is a diagnostic test accuracy handbook currently in process of development. I dont think the intervention handbook is appropriate for this study. 3. Search strategy. Search is quite outdated (28 Oct 2019) which practically excluded an important aetiology, SARS-CoV-2, unless the study purposely wanted to exclude that. 4. Inclusion criteria. Dichotomy between case-control and cohort studies could be confusing. I think, in any case, the study should be comparing between different groups of diseases (CAP, healthy, PE, etc) using the particular marker of interest (D-dimer). Studies could be either cross-sectional or cohort (observation over particular timeframe). 5. Inclusion criteria 7 and 8 are confusing when they dichotomize case-control and cohort. Criterias in 7 should be applicable into 8 and vice versa. Inclusion criteria 10 is unclear. 6. Does "repeat publication" means "duplication"? If so, this is normally understood as part of the screening process. 7. What do the authors mean by "This metaanalysis would prefer to include the studies deemed moderate to high methodological quality which should be scored at least 5 stars."? Does this mean studies were excluded if they dont qualify for this? 8. Table 1. All acronyms: PR, CR, PE, etc should be explained at the bottom of the table. 9. Table 1 in column whether comorbidities were excluded. Some studies were "No". Since certain comorbidities are to be excluded. This warrants further detailing of what comorbidities were included. 10. Table 1. What does area refer to? Earlier, 4 studies were reported as multi-center, but none in "area" column indicated that. Reviewer #2: The manuscript is well prepared and data analysis was done thoroughly. The following are a few minor suggestions for improvement. Title “Assessing the value” or “assessment of the value of” or “Value of D-dimer in predicting various clinical outcomes following CAP: A network meta-analysis Abstract Page 9: line 3: The role of D-dimer in predicting clinical outcomes is debating in many areas including the severity of community-acquired pneumonia (CAP), in hospital mortality and the risk of pulmonary embolism (PE). So that We aimed to carry out a meta-analysis to identify the role of d-dimer in predicting clinical outcomes which are associated CAP. Page 9; line 11: Data “was” analyzed Page 9: line 15: more suitable replacement for “hospital dead cases” and “PE attack patients” Page 9: line 20: to explore the distinguished role Page 9: line 26: PE high risk population �  high risk population of PE Background Page 11 Line 1: one of the most common respiratory diseases Line 4: CAP patients would progress into severe CAP Line 5: However, for a large proportion of CAP cases who visit emergency department could receive medical treatment without hospitalization. Line 7: critical for accurate treatment and to set setting up an appropriate care strategy To find reference 6 Line 12: procalcitonin [9, 10] had been reported with a great sensitivity for predicting the prognosis of CAP Line 14: Nevertheless, their specificities are not good enough to distinguish the various clinical outcomes of CAP. (reference?) 28th Jan 2021Nevertheless, their specificities are not good enough to distinguish the various clinical outcomes of CAP. Page 12 Line 21: The inclusion criteria were as followings: should be “as follows”. Page 13 Line 21: Besides, “The quality” of predictive and diagnostic study’s. “the quality” Page 15 Line 12: The network will be evaluated using frequentist multivariate meta-analysis. Should be “the network was evaluated” Page 16 Line 4: after carefully evaluated or after careful evaluation. Line 10: In addition, patients with diarrhea and congenital heart diseases were excluded in 3 studies of children. (not clear) Page 17 Line 25: ORs had been pooled to identify. Data analysis and interpretation was carried out properly. Page 21 line 17 elevated D-dimer is an available supplement to PSI and CURB-65, which are the most widely used points-scoring system to assess severity of pneumonia. [50] -- what is noted from reference 50 is "The coagulation system is often activated in CAP, and development of thrombocytopenia (platelet count, <100,000 cells/mm3) is also associated with a worse prognosis [86, 90–92]."- Is it quite certain with this reference only to use "is an available supplement to PSI and CURB-65 with this reference only "? thank you. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 7 May 2021 Dear editor, We could not find any places in the system to update the finical statement, so that we typed our newest finical statement here. We confirmed the financial statement as the followings: “This work was supported by grants from the National Natural Science Foundation This work was supported by grants from the National Natural Science Foundation of China awarded to YL (81700360) and HD (81971457, 81602817). The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.” Reviewer #1: 1. English used are mostly non-standard, contain a lot of errors and may create confusion. This alone warrants a major revision. I strongly urge a scientific English editing before going to the next review round. I would not go for the next round of review unless the authors provided evidence of scientific english editing. I have limited myself to review up to methodology section and a few tables only and hold it on until sufficient english editing is done for reviewing further. Response: We are sorry for non-standard English. We have make scientific English editing in revised version. Thanks a lot. 2. The authors claimed of using Cochrane Handbook for their analysis. Which Cochrane Handbook was used? I understand there is a diagnostic test accuracy handbook currently in process of development. I dont think the intervention handbook is appropriate for this study. Response: In 2019, the Cochrane Prognosis Methods Group has funded to make a guide to systematic review and meta-analysis of prognostic factor studies, which was published in BMJ. Therefore, we revised our articles according to this guide instead of Cochrane Intervention Handbook. Thanks for your advice. 3. Search strategy. Search is quite outdated (28 Oct 2019) which practically excluded an important aetiology, SARS-CoV-2, unless the study purposely wanted to exclude that. Response: We updated our study to end of March 2021. In our opinion, COVID-19 is not a standard community-acquired pneumonia (CAP) with absolute different disease process and therapeutical strategies. SARS-Cov-2 is not one of pathogens of CAP based on current consensus, although it may be CAP pathogen in future. We have stated in our article why we didn’t include studies associated with COVID-19. 4. Inclusion criteria. Dichotomy between case-control and cohort studies could be confusing. I think, in any case, the study should be comparing between different groups of diseases (CAP, healthy, PE, etc) using the particular marker of interest (D-dimer). Studies could be either cross-sectional or cohort (observation over particular timeframe). Response: We are sorry to make inclusion criteria confusing. We have remade our inclusion criteria according to modification of CHARMS (checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies) for prognostic factors (CHARMS-PF). Cross-sectional or and cohort studies were included according to “a guide to systematic review and meta-analysis of prognostic factor studies”. 5. Inclusion criteria 7 and 8 are confusing when they dichotomize case-control and cohort. Criterias in 7 should be applicable into 8 and vice versa. Inclusion criteria 10 is unclear. Response: We have advised as stated. Thanks a lot. 6. Does "repeat publication" means "duplication"? If so, this is normally understood as part of the screening process Response: We have replaced "repeat publication" with “duplication” and made it as part of the screening process. Thanks for your advice. 7. What do the authors mean by "This metaanalysis would prefer to include the studies deemed moderate to high methodological quality which should be scored at least 5 stars."? Does this mean study were excluded if they dont qualify for this? Response: According the guide, we didn’t exclude any study due to high risk of bias. We regarded methodological quality as one factor to make subgroup analysis. 8. Table 1. All acronyms: PR, CR, PE, etc should be explained at the bottom of the table. Response: We added explanation of all acronyms at the bottom of the table. Thanks. 9. Table 1 in column whether comorbidities were excluded. Some studies were "No". Since certain comorbidities are to be excluded. This warrants further detailing of what comorbidities were included. Response: The data associated with comorbidity is insufficient to make further analyses as d-dimer is not a main research topic in most included studies. Therefore, we didn’t include comorbidities in Table 1 in revised version. 10. Table 1. What does area refer to? Earlier, 4 studies were reported as multi-center, but none in "area" column indicated that. Response: We have replaced area with country and the multi-center studies were made in several hospital of the same country. Through careful screening again, only 2 studies meet the criteria of multicenter studies in our revised version. Reviewer #2 Title “Assessing the value” or “assessment of the value of” or “Value of D-dimer in predicting various clinical outcomes following CAP: A network meta-analysis. Response: We have revised our title as you suggest. Thanks for your advice. Abstract (1) Page 9: line 3: The role of D-dimer in predicting clinical outcomes is debating in many areas including the severity of community-acquired pneumonia (CAP), in hospital mortality and the risk of pulmonary embolism (PE). So that We aimed to carry out a meta-analysis to identify the role of d-dimer in predicting clinical outcomes which are associated CAP. (2) Page 9; line 11: Data “was” analyzed (3) Page 9: line 15: more suitable replacement for “hospital dead cases” and “PE attack patients” (4) Page 9: line 20: to explore the distinguished role (5) Page 9: line 26: PE high risk population �  high risk population of PE Response: We have revised as follows according to your advices: (1) However, whether the d-dimer level is an ideal index to predict the prognosis of community-acquired pneumonia remains debatable, because no relevant studies focusing on d-dimer levels before treatment in patients with CAP specifically were available to conduct meta-analyses previously. For this reason, a meta-analysis was performed to systematically and quantitatively evaluate the prognostic accuracy of the d-dimer level before treatment in CAP. (2) All “data were” were replaced with “data was” (3) “hospital dead cases” and “PE attack patients” were replaced with “non-survivors” and “patients with PE” (4) “to explore the distinguished role” was deleted. (5) “PE high risk population” was replaced with high-risk population of PE Background Page 11 (1) Line 1: one of the most common respiratory diseases (2) Line 4: CAP patients would progress into severe CAP (3) Line 5: However, for a large proportion of CAP cases who visit emergency department could receive medical treatment without hospitalization. (4) Line 7: critical for accurate treatment and to set setting up an appropriate care strategy (5) To find reference 6 Line 12: procalcitonin [9, 10] had been reported with a great sensitivity for predicting the prognosis of CAP (6) Line 14: Nevertheless, their specificities are not good enough to distinguish the various clinical outcomes of CAP. (reference?) Response: We have revised as follows according to your advices: (1) “one of the most common respiratory diseases” has been deleted. (2) “CAP patients would progress into severe CAP” was replaced with “enter the severe stage” (3) We revised this sentence as “A considerable proportion of patients with CAP in the emergency department can be treated as outpatients.” (4) We have deleted this sentence. (5) We have revised and only emphasized the potential prognostic value rather than sensitivity and specificity. (6) We have revised and only emphasized the potential prognostic value rather than sensitivity and specificity. Page 12 Line 21: The inclusion criteria were as followings: should be “as follows”. Response: We have revised as your advice. Thanks very much. Page 13 (1) Line 21: Besides, “The quality” of predictive and diagnostic study’s. “the quality” Response: We have deleted this sentence. Page 15 Line 12: The network will be evaluated using frequentist multivariate meta-analysis. Should be “the network was evaluated” Response: We have replaced “will be” with “was”. Page 16 (1) Line 4: after carefully evaluated or after careful evaluation. (2) Line 10: In addition, patients with diarrhea and congenital heart diseases were excluded in 3 studies of children. (not clear) Response: (1) We have revised as your advice. (2) We have deleted this sentence. Page 17 (1) Line 25: ORs had been pooled to identify. Data analysis and interpretation was carried out properly. Page 21 line 17 elevated D-dimer is an available supplement to PSI and CURB-65, which are the most widely used points-scoring system to assess severity of pneumonia. what is noted from reference 50 is "The coagulation system is often activated in CAP, and development of thrombocytopenia (platelet count, <100,000 cells/mm3) is also associated with a worse prognosis [86, 90–92]."- Is it quite certain with this reference only to use "is an available supplement to PSI and CURB-65 with this reference only "? Response: (1) We have revised as “Pooled results from adjust ORs have identified”. (2) We agree with your opinion and have deleted this sentence because it is not convincing that d-dimer is an available supplement to PSI and CURB-65 with this reference. 16 Jul 2021 PONE-D-20-17727R1 Value of D-dimer in predicting various clinical outcomes following community-acquired pneumonia: A network meta-analysis PLOS ONE Dear Dr. Li, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Aug 30 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see:  http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Cho Naing, MBBS, PhD, FRCP Academic Editor PLOS ONE Journal Requirements: Additional Editor Comments (if provided): The manuscript has been improved to a certain extent. Still, there are important areas needed to improve. As indicated by the Reviewer # 1, it is not meaningful to combine data from the different study designs. Thank you. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: (No Response) Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I have seen a lot of improvements since the first draft of the manuscript. However, methodologically speaking, I still have major doubts. 1. The authors identified only 1 RCT and the rest are observational study. I don't think it is reasonable to mix results of RCT and observational studies into a meta-analysis. They should be reported, analyzed, discussed, and concluded separately because their data were generated from totally different study designs. 2. SMD is standardized mean difference not "standard mean deviation" as it was mentioned in the abbreviation list. This is used for measuring effect of treatment. I am really not sure if this is applicable for prognostic study. It is unclear how the concept of "mean difference" is applied to determine whether d-dimer can be used to predict outcome. I feel it is more straightforward to use OR for this purpose, where a standard cut-off is used to determine high/low d-dimer level. 3. Variations in methodologies used to measure d-dimer level might have contributed to the significant heterogeneity. The authors have mentioned of doing subgroup analyses. I wonder if variations in methodologies were considered when doing subgroup analyses? Reviewer #2: 1) pg 17 why significant heterogeneity is mentioned as P<0.1, Did this value apply to the whole manuscript? 2) pg 19 Assessment of methodological quality QUIPS tool had been used to assess the quality of included studies (Table 2). Among all the 32 studies, 20 were high risk of bias [11, 30, 31, 33, 34, 36-41, 43, 48, 53-55, 57-60] and only 2 studies were evaluated as low risk of bias[42, 52]. The number of individual domains rated as high risk ranged from 0 to 3. Is there any specific reason that why moderate category is excluded from the discussing in the “Data Extraction and Study Quality Assessment component as well as from the “results” session. 3) Results session - kindly recheck the following data: o pooled result of figure 4 SMD=1.22 95%CI 0.67-1.77, I2=85.1% p=0.000 written in the paragraph and the data from the figure o supplementary figure 4 – 3 studies or 4 studies, pooled result "Pooled results of adjusted ORs from 4 studies [50-52, 54] have confirmed the prognostic value of increased D dimer (ES=0.90 95%CI 0.62-1.17, I2=59.4% p=0.008) (Supplementary Figure. 4). We didn’t find factors contributing to the heterogeneity by subgroup analysis" Kindly recheck which was written in the paragraph and the data from the figure o pooled result of supplementary figure 6 Pooled effect based on continuous data from three studies suggest a significant elevation in CAP patients with PE than those without PE (ES=1.07 95%CI 1.01-1.13, I2=60.2% p=0.113). (Supplementary Figure. 6). kindly recheck which was written in the paragraph and the data from the figure o some data of supplementary figure 7 I2=81.4% kindly recheck which was written in the paragraph and the data from the figure - for the “others” kindly refer with the respective figures Pooled effects suggested patients with CAP had a higher level of d-dimer compared to healthy participants (SMD=0.88, 95%CI 0.54-1.22, I2=57.9 %, p=0.037) and D-dimer was significantly further elevated in patients requiring invasive mechanical ventilator (SMD=1.01, 95%CI 0.69-1.33, I2=0.0%, p=0.815). (Kindly add "Referencing figures") 4) page 22 - 2nd paragraph – “this is may be” – incorrect use, please update 5) I would suggest to avoid using “it’s” “didn’t” – instead kindly use "it is or did not" and some minor punctuation and grammar usage. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 1 Oct 2021 Reviewer 1 1. The authors identified only 1 RCT and the rest are observational study. I don't think it is reasonable to mix results of RCT and observational studies into a meta-analysis. They should be reported, analyzed, discussed, and concluded separately because their data were generated from totally different study designs. Response to reviewer: We are sorry for this point of confuse. The reference 42 (Snijders, 2012), which was mentioned as one RCT in our article, was a secondary analysis based on a randomized controlled trial. Although the original analysis was in line with principles of RCTs, the secondary analysis based on outcome of patients (for example, d-dimer value of survivor and non-survivors) should be regarded as case-control study design. We have revised its design type as case-control study and examined the robustness of conclusion without this study which was not showed in article. Thanks very much. 2. SMD is standardized mean difference not "standard mean deviation" as it was mentioned in the abbreviation list. This is used for measuring effect of treatment. I am really not sure if this is applicable for prognostic study. It is unclear how the concept of "mean difference" is applied to determine whether d-dimer can be used to predict outcome. I feel it is more straightforward to use OR for this purpose, where a standard cut-off is used to determine high/low d-dimer level. Response to reviewer: It’s our negligence in abbreviation list where we wrongly used “standard mean deviation” and we have corrected it. As a guide for meta-analysis of prognostic studies published in BMJ journal suggested, unadjusted and adjusted prognostic effect estimates (eg, risk ratios, odds ratios, hazard ratios, mean differences) could be results to examine prognostic factors, although adjusted ratios are most recommended. The unadjusted odds ratio which we have transformed to standardized mean difference represented the risk that patients with poor outcome or prognosis had high levels of d-dimers. TAmong included studies for our meta-analysis, only a small proportion of them had supplied adjusted ORs and we have made data synthesis of these ORs. Because no consensus for prognostic meta-analysis, we also examined efficacy of prognostic factors with the help of principle of diagnostic meta-analysis, which regarded patients with poor outcome as positive evens of gold standard and regarded prognostic factors with cutoff as diagnostic method. Dose-response meta-analyses were a relatively ideal method to take full advantage of information and data of primary studies. Unfortunately, undetailed reports of included primary studies made it impossible to make dose-response curves. To be honest, our original intention was to measure the risk ratios that patients with different levels of d-dimer had poor outcome, but the existing studies did not support to complete such a meta-analysis. Therefore, we chose to transform odds ratio to SMD, not vice versa, to directly represent higher d-dimer level in patients with poor outcome. On the other hand, most of included studies reports continuous data and too much transform would bring unpredicted bias. We expected that our work would inspire more researchers to make more scientific studies and report more detailed data. We are trying to make a meta-analysis of individual participant data to solve this problem. Thank you. 3. Variations in methodologies used to measure d-dimer level might have contributed to the significant heterogeneity. The authors have mentioned of doing subgroup analyses. I wonder if variations in methodologies were considered when doing subgroup analyses? Response to reviewer: We are sorry for absence of mention of this subgroup analysis. We had made subgroup meta-analysis by methodologies of d-dimer measurement, but we didn’t put the figure of synthesis into our article because of too many more important figures. When pooled results showed great heterogeneity, nearly all subgroups including more than 3 studies also have considerable heterogeneity. For example, I-square of subgroups of studies having used Immunoturbidimetric assay, latex immunoassay and ELISA were 86.1%, 96.4% and 96.1%, respectively. We have added this point in our article. Reviewer #2: 1) pg 17 why significant heterogeneity is mentioned as P<0.1, Did this value apply to the whole manuscript? Response to reviewer: A limitation of Cochran’s Q test is that it might be underpowered when few studies have been included or when event rates are low. Therefore, it is often recommended to adopt a higher P-value (rather than 0.05) as a threshold for statistical significance when using Cochran’s Q test to determine statistical heterogeneity. We added relevant reference for this P value in our article. (2) pg 19 Assessment of methodological quality QUIPS tool had been used to assess the quality of included studies (Table 2). Among all the 32 studies, 20 were high risk of bias [11, 30, 31, 33, 34, 36-41, 43, 48, 53-55, 57-60] and only 2 studies were evaluated as low risk of bias [42, 52]. The number of individual domains rated as high risk ranged from 0 to 3. Is there any specific reason that why moderate category is excluded from the discussing in the “Data Extraction and Study Quality Assessment component as well as from the “results” session. Response to reviewer: We are sorry for our confusing description. What we wanted to make readers knew was that 20 included studies were high risk, 2 were low risk and the remaining 10 studies were medium risk of bias. We have revised it. Thank you. 3) Results session - kindly recheck the following data: o pooled result of figure 4 SMD=1.22 95%CI 0.67-1.77, I2=85.1% p=0.000 written in the paragraph and the data from the figure o supplementary figure 4 – 3 studies or 4 studies, pooled result "Pooled results of adjusted ORs from 4 studies [50-52, 54] have confirmed the prognostic value of increased D dimer (ES=0.90 95%CI 0.62-1.17, I2=59.4% p=0.008) (Supplementary Figure. 4). We didn’t find factors contributing to the heterogeneity by subgroup analysis" Kindly recheck which was written in the paragraph and the data from the figure o pooled result of supplementary figure 6 Pooled effect based on continuous data from three studies suggest a significant elevation in CAP patients with PE than those without PE (ES=1.07 95%CI 1.01-1.13, I2=60.2% p=0.113). (Supplementary Figure. 6). kindly recheck which was written in the paragraph and the data from the figure o some data of supplementary figure 7 I2=81.4% kindly recheck which was written in the paragraph and the data from the figure - for the “others” kindly refer with the respective figures Pooled effects suggested patients with CAP had a higher level of d-dimer compared to healthy participants (SMD=0.88, 95%CI 0.54-1.22, I2=57.9 %, p=0.037) and D-dimer was significantly further elevated in patients requiring invasive mechanical ventilator (SMD=1.01, 95%CI 0.69-1.33, I2=0.0%, p=0.815). (Kindly add "Referencing figures") Response to reviewer: We are sorry for our serious negligence to mistakenly correspond valued of pooled results to figures. Thanks for your correction with patience and we have revised our article according to your suggestion. Thank you very much. 4) page 22 - 2nd paragraph – “this is may be” – incorrect use, please update Response to reviewer: We have modified it to “this is partly because of …”. Thanks for your advice. 5) I would suggest to avoid using “it’s” “didn’t” – instead kindly use "it is or did not" and some minor punctuation and grammar usage. Response to reviewer: We have replaced with “it is or did not” in our revised article. Thank you. Submitted filename: Response to Reviewers.docx Click here for additional data file. 17 Jan 2022 Value of D-dimer in predicting various clinical outcomes following community-acquired pneumonia: A network meta-analysis PONE-D-20-17727R2 Dear Dr. Li, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Cho Naing, MBBS, PhD, FRCP Academic Editor PLOS ONE Additional Editor Comments (optional): The authors have addressed the comments with reasonable improvement and justification, Thank you Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I have no more substantial comments for this manuscript, but I still see quite a number references to RCT while the authors have mentioned that no RCTs were included. Reviewer #2: I am grateful for this well written manuscript and robust analysis. The comments have been appropriately addressed and the contents were revised accordingly. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No 28 Jan 2022 PONE-D-20-17727R2 Value of D-dimer in predicting various clinical outcomes following community-acquired pneumonia: A network meta-analysis Dear Dr. Li: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Cho Naing Academic Editor PLOS ONE
  66 in total

1.  Prevalence of venous thromboembolic events and diagnostic performance of the wells score and revised geneva scores for pulmonary embolism in patients with interstitial lung disease: a prospective study.

Authors:  Qun Luo; Jiaxing Xie; Qian Han; Chunli Tang; Xiaobo Chen; Lulu Wu; Rongchang Chen
Journal:  Heart Lung Circ       Date:  2014-03-12       Impact factor: 2.975

2.  Lung vessels thrombosis in hospitalized patients with community-acquired pneumonia: role of endothelial function, hemostasis, fibrinolysis and inflammation on different phases of treatment

Authors:  Mariia A Krykhtina; Kseniia O Bielosludtseva; Larysa A Botvinikova; Nataliia M Matikina
Journal:  Wiad Lek       Date:  2019-08-31

3.  Incidence, direct costs and duration of hospitalization of patients hospitalized with community acquired pneumonia: A nationwide retrospective claims database analysis.

Authors:  Mark H Rozenbaum; Marie-Josee J Mangen; Susanne M Huijts; Tjip S van der Werf; Maarten J Postma
Journal:  Vaccine       Date:  2015-05-14       Impact factor: 3.641

4.  Checking consistency in mixed treatment comparison meta-analysis.

Authors:  S Dias; N J Welton; D M Caldwell; A E Ades
Journal:  Stat Med       Date:  2010-03-30       Impact factor: 2.373

5.  The association between plasma D-dimer levels and community-acquired pneumonia.

Authors:  Sulhattin Arslan; Serdal Ugurlu; Gokten Bulut; Ibrahim Akkurt
Journal:  Clinics (Sao Paulo)       Date:  2010-06       Impact factor: 2.365

6.  C-reactive protein and procalcitonin as predictors of survival and septic shock in ventilator-associated pneumonia.

Authors:  G Hillas; T Vassilakopoulos; P Plantza; A Rasidakis; P Bakakos
Journal:  Eur Respir J       Date:  2009-08-28       Impact factor: 16.671

7.  Assessing bias in studies of prognostic factors.

Authors:  Jill A Hayden; Danielle A van der Windt; Jennifer L Cartwright; Pierre Côté; Claire Bombardier
Journal:  Ann Intern Med       Date:  2013-02-19       Impact factor: 25.391

Review 8.  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Authors: 
Journal:  Lancet       Date:  2015-06-07       Impact factor: 202.731

9.  Elevated hemostasis markers after pneumonia increases one-year risk of all-cause and cardiovascular deaths.

Authors:  Sachin Yende; Gina D'Angelo; Florian Mayr; John A Kellum; Lisa Weissfeld; A Murat Kaynar; Tammy Young; Kaikobad Irani; Derek C Angus
Journal:  PLoS One       Date:  2011-08-10       Impact factor: 3.240

10.  Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.

Authors:  Xiang Wan; Wenqian Wang; Jiming Liu; Tiejun Tong
Journal:  BMC Med Res Methodol       Date:  2014-12-19       Impact factor: 4.615
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