Literature DB >> 36138462

Revalidating the prognostic COVID-19 severity assessment (COSA) score for variants of concern.

Verena Schöning1, Evangelia Liakoni1, Christine Baumgartner2, Aristomenis K Exadaktylos3, Wolf E Hautz3, Andrew Atkinson4,5, Felix Hammann6.   

Abstract

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Year:  2022        PMID: 36138462      PMCID: PMC9503266          DOI: 10.1186/s12967-022-03634-x

Source DB:  PubMed          Journal:  J Transl Med        ISSN: 1479-5876            Impact factor:   8.440


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Dear Editor, Many prediction models have been published for Coronavirus disease 2019 (COVID-19) to support clinical decision-making for either diagnosis, prediction of mortality risk, or disease progression. An ongoing review concluded that most of these were poorly reported and had a high risk of bias, casting doubt over their real-world predictive value [1]. Additionally, dominant strains are no longer the ancestral type but variants of concern (VOCs) with different pathogenicity, and vaccinations and herd immunity can influence individual outcomes. We aimed to assess the performance of our previously published COSA (COVID-19 Severity Assessment) score on admitted patients in the twelve months following its development, a time during which the score was used clinically for risk stratification. The COSA score was developed using data from patients who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse-transcriptase polymerase chain reaction (RT-PCR) between February 1st and November 16th, 2020 (1st and 2nd waves in Switzerland, i.e. the original cohort) [2]. The revalidation cohort consisted of patients who tested positive for SARS-CoV-2 between November 17th, 2020 and November 16th, 2021. The primary outcome was disease severity, as determined by the worst outcome at any point after diagnosis: Non-severe outcome: no intensive care unit (ICU) admission or death of any cause during the observational period Severe outcome: ICU admission at any stage and / or death of any cause All patients were discharged or had died by the time the revalidation was performed. The COSA score (Table 1) was calculated for each patient using the most extreme laboratory values within 3 days prior to 1 day after the positive SARS-CoV-2 test. The results of the original and the revalidation cohort were then compared.
Table 1

COVID-19 severity assessment (COSA) score (from Ref. [2])

ParameterValueScore points
SexMale1
CRP ≥ 25 mg/L3
Sodium ≥ 144 mmol/L2
Hemoglobin ≤ 100 g/L1
eGFR according to CKD-EPI ≤ 75 mL/min1
Glucose ≥ 8.6 mmol/L1
Leucocytes ≥ 10 G/L1

The COSA score was calculated for each patient using the most extreme values within 3 days prior to 1 day after the positive SARS-CoV-2 test, with a score of 6 or higher indicating a high risk (> 50%) for a severe progression

COVID-19 severity assessment (COSA) score (from Ref. [2]) The COSA score was calculated for each patient using the most extreme values within 3 days prior to 1 day after the positive SARS-CoV-2 test, with a score of 6 or higher indicating a high risk (> 50%) for a severe progression Data wrangling, analysis, and visualization were performed in GNU R (version 4.0.2, [3]). Statistical significance levels were defined at a p-value of < 0.05, and determined with the Wilcoxon rank sum test for continuous variables, and the Chi-square test for categorical variables using the stats package (version 4.0.2). The area under the receiver operating characteristic curve (AUROC) and the 95% confidence intervals (CI) were calculated to assess the discriminatory power of the COSA score to predict a severe outcome. The COSA score was considered validated if the 95% CI of the AUROC from fitting the original and the revalidation data set were overlapping. The original cohort consisted of 626 patients (457 non-severe and 169 severe outcomes), and 508 patients were included in the revalidation cohort (301 non-severe and 208 severe outcomes). A comparison of the demographics and laboratory parameters of both cohorts is provided in Table 2. The patients in the original non-severe cohort were significantly younger with a lower share of inpatients than in the non-severe revalidation cohort. The latter had significantly higher peak C-reactive protein (CRP) and glucose, and lower minimal hemoglobin and estimated glomerular filtration rate values. For severe patients, we noted a higher proportion of inpatients and deaths, and significantly lower body weights and body mass index in the revalidation cohort. There was no significant difference in laboratory parameters.
Table 2

General demographics and laboratory parameters of the original and revalidation cohort

Non-severe (N = 758)Severe (N = 512)
Original(N = 457)Revalidation(N = 301)P valueOriginal(N = 171)Revalidation(N = 208)P value
Demographics
 Age (years)

  Median

(IQR)

64.00 (49.00, 76.00)72.00 (59.00, 82.00) < 0.00268.00 (57.00, 78.00)72.00 (59.75, 82.25)0.058
 Sex
  Female, n (%)188 (41.05)125 (41.81)0.89545 (26.32)63 (30.29)0.460
 Hospitalization
  Inpatients, n (%)319 (69.58)299 (100.00) < 0.002163 (95.27)208 (100.00)0.005
 Deaths
  Deceased, n (%)0 (0.00)0 (0.00)51 (29.82)120 (57.69) < 0.002
 Weight (kg)

  Median

(IQR)

77.90 (66.23, 88.00)76.30 (65.62, 88.00)0.52681.00 (70.40, 93.70)75.20 (65.20, 90.00)0.026
 Height (cm)

  Median

(IQR)

170.00 (165.00, 176.00)170.00 (163.00, 177.00)0.241170.00 (165.00, 176.00)170.00 (165.00, 176.75)0.883
 Body Mass Index (BMI, kg/m2)

  Median

(IQR)

25.98 (23.38, 29.74)26.20 (23.29, 30.32)0.48928.07 (25.20, 31.20)26.87 (23.28, 29.81)0.018
Laboratory parameters
 Maximum C-reactive protein (CRP) levels
  Median (IQR)37.00 (10.00, 78.00)60.00 (21.00, 107.50) < 0.002106.00 (59.00, 175.00)125.50 (62.00, 202.50)0.300
 Maximum sodium levels
  Median (IQR)139.00 (137.00, 141.00)139.00 (137.00, 142.00)0.262142.00 (139.00, 145.00)142.00 (138.00, 146.00)0.901
 Minimum hemoglobin levels
  Median (IQR)132.00 (118.00, 144.00)126.00 (111.00, 142.00)0.004113.00 (89.50, 125.00)107.50 (84.75, 124.25)0.372
 Minimum glomerular filtration rate (GFR) values
  Median (IQR)82.00 (61.00, 97.00)75.00 (52.00, 93.00)0.00764.00 (39.50, 87.00)56.00 (31.75, 84.25)0.158
 Minimum glucose values
  Median (IQR)6.40 (5.67, 7.90)6.90 (6.00, 8.46)0.0029.50 (7.46, 12.55)9.45 (7.18, 11.80)0.393
 Minimum leukocytes values
  Median (IQR)6.32 (4.70, 8.61)6.41 (4.91, 9.09)0.2358.92 (6.65, 13.70)10.90 (7.03, 15.12)0.072

Laboratory parameters were considered from three day prior to until 1 day after the first positive SARS-CoV-2 PCR test result

IQR interquartile range

Bold numbers indicate significant differences (p < 0.05) between severe and non-severe cases.

General demographics and laboratory parameters of the original and revalidation cohort Median (IQR) Median (IQR) Median (IQR) Median (IQR) Laboratory parameters were considered from three day prior to until 1 day after the first positive SARS-CoV-2 PCR test result IQR interquartile range Bold numbers indicate significant differences (p < 0.05) between severe and non-severe cases. The AUROC was 0.85 (95% CI 0.82–0.88) and 0.80 (95% CI 0.76–0.84) for the original and revalidation cohort, respectively (Fig. 1). A closer look at the severity distribution per score value (Fig. 2) revealed a greater share of severe cases with low score values (0–4 points) in the revalidation cohort than in the original cohort. No major differences are noticeable for score points greater than 4.
Fig. 1

Area under the receiver operating characteristic (AUROC) of the COVID-19 severity assessment (COSA) score. Original (red) and revalidation cohort (blue)

Fig. 2

Percentage amount of patients with severe and non-severe COVID-19 in relation to score points in the original (A) and revalidation (B) cohort

Area under the receiver operating characteristic (AUROC) of the COVID-19 severity assessment (COSA) score. Original (red) and revalidation cohort (blue) Percentage amount of patients with severe and non-severe COVID-19 in relation to score points in the original (A) and revalidation (B) cohort Patients in the revalidation cohort presented with overall worse laboratory markers and a greater likelihood of severe outcomes compared to the original cohort (69.1% vs. 37.4%). This could be due to more selective laboratory testing for hospitalized patients only and differences in circulating variants. Although no sequencing data is available for either cohort, national surveys indicate that the dominant strain during the 1st and 2nd waves (original cohort) was the ancestral type, whereas the 3rd and 4th waves (revalidation cohort) were driven by the more transmissible and virulent VOCs Alpha (B.1.1.7) and Delta (B.1.617.2) [4]. Vaccination campaigns and an emerging population-level immunity likely mitigated the individual disease severity [5]. While the performance of the score remains robust with strong positive discriminative ability we did note a decrease in specificity towards the lower end of the scale (Fig. 2). This suggests that readjustment of the cut-offs might be beneficial for a better separation of the severity classes as new variants emerge. Despite changes in the viral landscape and population immunity, the COSA score still delivered good predictions of disease progression one year after its development. We attribute this to the simple set of covariates and the rigorous internal and external validation in the original model-building process. Adaptations to the score could become necessary in the near future as vaccination effects begin to wane and if drastically different VOCs appear.
  3 in total

1.  Effectiveness of COVID-19 vaccines against SARS-CoV-2 variants of concern: a systematic review and meta-analysis.

Authors:  Baoqi Zeng; Le Gao; Qingxin Zhou; Kai Yu; Feng Sun
Journal:  BMC Med       Date:  2022-05-23       Impact factor: 11.150

2.  Development and validation of a prognostic COVID-19 severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital.

Authors:  Verena Schöning; Evangelia Liakoni; Christine Baumgartner; Aristomenis K Exadaktylos; Wolf E Hautz; Andrew Atkinson; Felix Hammann
Journal:  J Transl Med       Date:  2021-02-05       Impact factor: 5.531

3.  Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Authors:  Laure Wynants; Ben Van Calster; Gary S Collins; Richard D Riley; Georg Heinze; Ewoud Schuit; Marc M J Bonten; Darren L Dahly; Johanna A A Damen; Thomas P A Debray; Valentijn M T de Jong; Maarten De Vos; Paul Dhiman; Maria C Haller; Michael O Harhay; Liesbet Henckaerts; Pauline Heus; Michael Kammer; Nina Kreuzberger; Anna Lohmann; Kim Luijken; Jie Ma; Glen P Martin; David J McLernon; Constanza L Andaur Navarro; Johannes B Reitsma; Jamie C Sergeant; Chunhu Shi; Nicole Skoetz; Luc J M Smits; Kym I E Snell; Matthew Sperrin; René Spijker; Ewout W Steyerberg; Toshihiko Takada; Ioanna Tzoulaki; Sander M J van Kuijk; Bas van Bussel; Iwan C C van der Horst; Florien S van Royen; Jan Y Verbakel; Christine Wallisch; Jack Wilkinson; Robert Wolff; Lotty Hooft; Karel G M Moons; Maarten van Smeden
Journal:  BMJ       Date:  2020-04-07
  3 in total

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