Evidence map›Paper›PMID 35793312›Full record

ArticlePloS one2022

COVID-19 Time of Intubation Mortality Evaluation (C-TIME): A system for predicting mortality of patients with COVID-19 pneumonia at the time they require mechanical ventilation.

Robert A Raschke, Pooja Rangan, Sumit Agarwal, Suresh Uppalapu, Nehan Sher, Steven C Curry, C William Heise

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

7 authors.

Robert A RaschkeThe Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.ORCID 0000-0003-3495-7065
Pooja RanganUniversity of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.
Sumit AgarwalUniversity of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.
Suresh UppalapuUniversity of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.
Nehan SherUniversity of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.
Steven C CurryThe Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.
C William HeiseThe Division of Clinical Data Analytics and Decision Support, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States of America.ORCID 0000-0002-4795-1060

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn accurate system to predict mortality in patients requiring intubation for COVID-19 could help to inform consent, frame family expectations and assist end-of-life decisions. RESEARCH

objectiveTo develop and validate a mortality prediction system called C-TIME (COVID-19 Time of Intubation Mortality Evaluation) using variables available before intubation, determine its discriminant accuracy, and compare it to acute physiology and chronic health evaluation (APACHE IVa) and sequential organ failure assessment (SOFA).

methodsA retrospective cohort was set in 18 medical-surgical ICUs, enrolling consecutive adults, positive by SARS-CoV 2 RNA by reverse transcriptase polymerase chain reaction or positive rapid antigen test, and undergoing endotracheal intubation. All were followed until hospital discharge or death. The combined outcome was hospital mortality or terminal extubation with hospice discharge. Twenty-five clinical and laboratory variables available 48 hours prior to intubation were entered into multiple logistic regression (MLR) and the resulting model was used to predict mortality of validation cohort patients. Area under the receiver operating curve (AUROC) was calculated for C-TIME, APACHE IVa and SOFA.

resultsThe median age of the 2,440 study patients was 66 years; 61.6 percent were men, and 50.5 percent were Hispanic, Native American or African American. Age, gender, COPD, minimum mean arterial pressure, Glasgow Coma scale score, and PaO2/FiO2 ratio, maximum creatinine and bilirubin, receiving factor Xa inhibitors, days receiving non-invasive respiratory support and days receiving corticosteroids prior to intubation were significantly associated with the outcome variable. The validation cohort comprised 1,179 patients. C-TIME had the highest AUROC of 0.75 (95%CI 0.72-0.79), vs 0.67 (0.64-0.71) and 0.59 (0.55-0.62) for APACHE and SOFA, respectively (Chi2 P<0.0001).

conclusionsC-TIME is the only mortality prediction score specifically developed and validated for COVID-19 patients who require mechanical ventilation. It has acceptable discriminant accuracy and goodness-of-fit to assist decision-making just prior to intubation. The C-TIME mortality prediction calculator can be freely accessed on-line at https://phoenixmed.arizona.edu/ctime.

Indexed as

COVID-19Respiration, ArtificialAdultAgedAPACHEFemaleHumansIntubation, IntratrachealMaleRetrospective Studies

Identifiers

PMID35793312
PMCPMC9258832

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.