| Literature DB >> 25830638 |
Xin Kang1, Da-Yong Hu1, Chang-Bin Li1, Xin-Hua Li1, Shu-Ling Fan1, Yong Liu2, Guang-Yu Tang2, Zi-Sheng Ai3, Tianfu Wu4, Chandra Mohan4, Xin J Zhou5, Jun-Yan Liu1, Ai Peng1.
Abstract
BACKGROUND: Pulmonary injury is the main cause of death in acute paraquat (PQ) poisoning. However, whether quantitative lung computed tomography (CT) can be useful in predicting the outcome of PQ poisoning remains unknown. We aimed to identify early findings of quantitative lung CT as predictors of outcome in acute PQ poisoning.Entities:
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Year: 2015 PMID: 25830638 PMCID: PMC4382148 DOI: 10.1371/journal.pone.0121691
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Flow chart.
Fig 2Eight CT findings of PQ poisoning captured within the first 5-day.
A. ground glass opacity (GGO); B. consolidation; C. pleural thickening; D. hydrothorax; E. fibrosis; F. pneumomediastinum; G. nodule; H. “no obvious lesion”. Arrows represented the lesions.
Demographic and Clinical Data of Patients during the first 5-day of PQ Poisoning.
| Survivors | Nonsurvivors |
| |
|---|---|---|---|
|
| 34.3±10.8 | 33.5±12.5 | 0.289 |
|
| 18/38 | 18/23 | 0.121 |
|
| 14.3±5.5 | 14.1±5.9 | 0.880 |
|
| 15 (10–20) | 50 (20–110) | < 0.001 |
|
| 0.1 (0.0–0.2) | 0.8 (0.1–6.7) | < 0.001 |
|
| 1.5 (0.1–5.6) | 23.7 (8.9–267.0) | < 0.001 |
|
| |||
|
| 36 (64.3) | 23 (56.1) | 0.414 |
|
| 31 (55.4) | 29 (70.7) | 0.124 |
|
| 13 (23.2) | 22 (53.7) | 0.002 |
|
| 9 (16.1) | 13 (31.7) | 0.069 |
|
| 0 (0.0) | 17 (41.5) | < 0.001 |
|
| |||
|
| 3 (1–5) | 10 (5–12) | < 0.001 |
|
| 2 (0–4) | 5 (3–7) | < 0.001 |
|
| |||
|
| 15 (26.8) | 37 (90.2) | < 0.001 |
|
| 5.1 (3.1–9.5) | 7.9 (6.0–13.0) | < 0.001 |
|
| 68.5 (49.3–138.8) | 222.0 (157.6–301.0) | < 0.001 |
|
| |||
|
| 4 (7.1) | 29 (70.7) | < 0.001 |
|
| 21.5 (16.2–39.8) | 185.7 (71.2–451.8) | < 0.001 |
|
| 17.0 (10.0–44.7) | 217.9 (38.5–346.4) | < 0.001 |
|
| 14.9 (8.4–19.5) | 35.7 (10.2–66.7) | < 0.001 |
|
| 6.3 (3.5–8.4) | 23.1 (5.4–48.6) | < 0.001 |
|
| |||
|
| 2 (3.6) | 28 (68.3) | < 0.001 |
|
| 7.40 (7.37–7.42) | 7.31 (7.26–7.41) | 0.002 |
|
| 95.5 (87.9–102.0) | 55.7 (51.5–73.6) | < 0.001 |
|
| 37.2 (33.8–40.0) | 33.0 (27.9–40.4) | 0.169 |
|
| 23 (41.1) | 38 (92.7) | < 0.001 |
Definition of abbreviations: PQ = paraquat; APACHEII = Acute Physiology and Chronic Health Evaluation; SOFA = Sequential Organ Failure Assessment; continuous variable are presented as means ± SD or median (interquartile range) and categorical variable is presented as no. (%).
Note: the values of Symptom, Scoring, renal function, liver function and arterial blood gases were the peak values during the first 5-day.
Eight Lung CT Findings during the First 5 Days after PQ Intoxication.
| CT finding | Survivors ( | Nonsurvivors ( |
|
|
|---|---|---|---|---|
|
| 22 (39.3) | 35 (85.4) | < 0.001 | 9.015 |
|
| 6 (10.7) | 16 (39.0) | 0.001 | 5.333 |
|
| 17 (30.4) | 8 (19.5) | 0.228 | 0.566 |
|
| 12 (21.4) | 7 (17.1) | 0.593 | 0.755 |
|
| 21 (37.5) | 8 (19.5) | 0.056 | 0.404 |
|
| 1 (1.8) | 9 (22.0) | < 0.001 | 15.469 |
|
| 10 (17.9) | 4 (9.8) | 0.262 | 0.497 |
|
| 19 (33.9) | 3 (7.3) | 0.002 | 0.154 |
Definition of abbreviations: PQ = paraquat; OR = odds ratio.
Fig 3Kaplan-Meier survival curves of 97 paraquat poisoned cases stratified according to different CT findings within the first 5-day period.
Patients were categorized into two groups based on whether or not they presented the specific CT finding. The P values were derived by log-rank test.
Fig 4The receiver operating characteristic (ROC) curves constructed for outcome prediction by amount of paraquat (PQ) ingestion, plasma and urine concentrations of PQ, scores of Acute Physiology and Chronic Health Evaluation (APACHE) II and Sequential Organ Failure Assessment (SOFA), as well as volume ratio of Ground glass opacity and consolidation following PQ poisoning.
Comparison of Predictors for Mortality of PQ Poisoning.
| Variable | Cutoff | AUC (95% CI) | Sen | Spe | PPV | NPV | ACC |
|---|---|---|---|---|---|---|---|
|
| 27.5ml | 0.850 (0.837–0.863) | 0.732 | 0.804 | 0.732 | 0.804 | 0.773 |
|
| 4.5 | 0.856 (0.843–8.868) | 0.829 | 0.768 | 0.723 | 0.860 | 0.794 |
|
| 2.5 | 0.788 (0.773–0.807) | 0.854 | 0.732 | 0.700 | 0.872 | 0.784 |
|
| 0.8mg/L | 0.826 (0.812–0.841) | 0.512 | 0.964 | 0.909 | 0.720 | 0.763 |
|
| 8.3mg/L | 0.861 (0.849–0.874) | 0.780 | 0.804 | 0.727 | 0.830 | 0.784 |
|
| 10.8% | 0.871 (0.857–0.884) | 0.854 | 0.893 | 0.812 | 0.893 | 0.876 |
|
| 7.1% | 0.634 (0.614–0.653) | 0.390 | 0.829 | 0.765 | 0.650 | 0.670 |
Definition of abbreviations: PQ = paraquat; AUC = area under a receiver operator curve; Sen = sensitivity; Spe = specificity; PPV = positive predictive value; NPV = negative predictive value; ACC = Accuracy; APACHEII = Acute Physiology and Chronic Health Evaluation; SOFA = Sequential Organ Failure Assessment;
Note: amount of PQ ingestion, plasma PQ concentration, and urine PQ concentration were collected on admission; other parameters were the peak values within 5 days following intake of paraquat.
Cox Proportional Hazards Models for Mortality Prediction of PQ Poisoning.
| Univariate Cox Model | Multivariate Cox Model | |||
|---|---|---|---|---|
|
| HR (95%CI) |
| HR (95%CI) |
|
|
| 6.91 (6.11–7.81) | < 0.001 | 2.49 (2.15–2.88) | < 0.001 |
|
| 10.21 (9.17–11.49) | < 0.001 | 4.52 (3.92–5.21) | < 0.001 |
|
| 7.81 (6.86–8.89) | < 0.001 | 2.04 (1.74–2.40) | < 0.001 |
|
| 8.08 (6.99–9.33) | < 0.001 | 3.80 (3.24–4.46) | < 0.001 |
|
| 5.23 (4.54–6.02) | < 0.001 | N/A | 0.225 |
|
| 14.34 (12.23–16.80) | < 0.001 | 5.82 (4.77–7.09) | < 0.001 |
|
| 2.74 (2.45–3.08) | < 0.001 | N/A | 0.229 |
|
| 6.09 (5.31–6.99) | < 0.001 | 1.72 (1.49–1.98) | < 0.001 |
|
| 0.35 (0.30–0.42) | < 0.001 | N/A | 0.240 |
Definition of abbreviations: PQ = paraquat; HR = harzard ratio; N/A = not applicable.
Note: * indicates variables were categorical using the presence of CT finding as a dichotomous variable; other variables were categorical according whether lesion volume ratio was above or below the optimal cutoff point.
Fig 5Kaplan-Meier survival curves of 97 paraquat poisoned cases stratified according to levels of GGO volume ratios within the first 5-day period.
Patients were categorized into three groups based on quartile levels of GGO volume ratios. Comparisons between curves showing difference with statistical significance (P < 0.05) are indicated.