Evidence map›Paper›PMID 36987484›Full record

ArticleCureus2023

A Comparison of ICU Mortality Scoring Systems Applied to COVID-19.

Muhammad Monk, Jordan Torres, Kimberly Vickery, Gnananandh Jayaraman, Siva T Sarva, Ramesh Kesavan

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Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. [Experiences from SARS-CoV-2 pandemic at UKSH Lübeck].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Muhammad MonkInternal Medicine, HCA Houston Kingwood/University of Houston College of Medicine, Kingwood, USA.
Jordan TorresInternal Medicine, Univeristy of Houston/HCA Healthcare Kingwood, Houston, USA.
Kimberly VickeryMedical Education and Simulation, HCA Healthcare, Brentwood, USA.
Gnananandh JayaramanPulmonary and Critical Care Medicine, HCA Houston Kingwood, Kingwood, USA.
Siva T SarvaPulmonary and Critical Care Medicine, HCA Houston Kingwood, Kingwood, USA.
Ramesh KesavanPulmonary and Critical Care Medicine, HCA Houston Kingwood/University of Houston College of Medicine, Houston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Over the past three years, COVID-19 has been a major source of mortality in intensive care units around the world. Many scoring systems have been developed to estimate mortality in critically ill patients. Our intent with this study was to compare the efficacy of these systems when applied to COVID-19. Methods The was a multicenter, retrospective cohort study of critically ill patients with COVID-19 admitted to 16 hospitals in Texas from February 2020 to March 2022. The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA) score, and 4C Mortality scores were calculated on the initial day of ICU admission. Primary endpoints were all-cause mortality, ICU length of stay, and hospital length of stay. Results Initially, 62,881 patient encounters were assessed, and the cohort of 292 was selected based on the inclusion of the requisite values for each of the scoring systems. The median age was 56 +/- 14.93 years and 61% of patients were male. Mortality was defined as patients who expired or were discharged to hospice and was 78%. The different scoring systems were compared using logistic regression, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) analysis to compare the accuracy of prediction of the mortality and length of stay. The multivariate analysis showed that SOFA, APACHE II, SAPS II, and 4C scores were all significant predictors of mortality. The SOFA score had the highest AUC, though the confidence intervals for all of the models overlap therefore one model could not be considered superior to any of the others. Linear regression was performed to evaluate the models' ability to predict ICU and hospital length of stay, and none of the tested systems were found to be significant predictors of length of stay. Conclusion The SOFA, APACHE II, ISARIC 4-C, and SAPS II scores all accurately predicted mortality in critically ill patients with COVID-19. The SOFA score trended to perform the best.

Indexed as

acute physiology and chronic health evaluation (apache) iicorona virus mortality scorescovid-19intensive care unitisaric 4c scorerisk stratificationsequential organ failure assessment (sofa)simplified acute physiology score (saps) ii

Identifiers

PMID36987484
PMCPMC10040236

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.