Evidence map›Paper›PMID 33274414›Full record

ArticleJournal of general internal medicine2021

Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019.

David M Levine, Stuart R Lipsitz, Zoe Co, Wenyu Song, Patricia C Dykes, Lipika Samal

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  4. Observational
  5. Observational
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  13. Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  14. Article
  15. Clinical Risk Score and COVID-19.Journal of general internal medicine · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

David M LevineDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA. dmlevine@bwh.harvard.edu.ORCID 0000-0002-4337-9896
Stuart R LipsitzDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
Zoe CoDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
Wenyu SongDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
Patricia C DykesDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
Lipika SamalDivision of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.

Funding

Electronic Tools to Increase Recognition and Improve Primary Care Management for Hypertension in Chronic Kidney Disease: A Multi-site Randomized Clinical TrialR01DK116898 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI Saul B. Blecker, David Alan Feldstein · 2018 to 2026
$6.0M
NIDDK NIH HHS R01 DK116898
6 · The paper itself

Abstract

backgroundUncertainty surrounding COVID-19 regarding rapid progression to acute respiratory distress syndrome and unusual clinical characteristics make discharge from a monitored setting challenging. A clinical risk score to predict 14-day occurrence of hypoxia, ICU admission, and death is unavailable.

objectiveDerive and validate a risk score to predict suitability for discharge from a monitored setting among an early cohort of patients with COVID-19.

designModel derivation and validation in a retrospective cohort. We built a manual forward stepwise logistic regression model to identify variables associated with suitability for discharge and assigned points to each variable. Event-free patients were included after at least 14 days of follow-up.

participantsAll adult patients with a COVID-19 diagnosis between March 1, 2020, and April 12, 2020, in 10 hospitals in Massachusetts, USA. MAIN MEASURES: Fourteen-day composite predicting hypoxia, ICU admission, and death. We calculated a risk score for each patient as a predictor of suitability for discharge evaluated by area under the curve. KEY

resultsOf 2059 patients with COVID-19, 1326 met inclusion. The 1014-patient training cohort had a mean age of 58 years, was 56% female, and 65% had at least one comorbidity. A total of 255 (25%) patients were suitable for discharge. Variables associated with suitability for discharge were age, oxygen saturation, and albumin level, yielding a risk score between 0 and 55. At a cut point of 30, the score had a sensitivity of 83% and specificity of 82%. The respective c-statistic for the derivation and validation cohorts were 0.8939 (95% CI, 0.8687 to 0.9192) and 0.8685 (95% CI, 0.8095 to 0.9275). The score performed similarly for inpatients and emergency department patients.

conclusionsA 3-item risk score for patients with COVID-19 consisting of age, oxygen saturation, and an acute phase reactant (albumin) using point of care data predicts suitability for discharge and may optimize scarce resources.

Indexed as

AdultAgedCOVID-19COVID-19 TestingFemaleHumansHypoxiaIntensive Care UnitsMaleMiddle AgedRespiration, ArtificialRespiratory InsufficiencyRetrospective StudiesRisk AssessmentRisk FactorsCOVID-19patient dischargeprognosisrisk scoresevere acute respiratory syndrome coronavirus 2

Identifiers

PMID33274414
PMCPMC7713904

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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.