Evidence map›Paper›PMID 35744754›Full record

ArticleMicroorganisms2022

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received.

Ariel Israel, Alejandro A Schäffer, Eugene Merzon, Ilan Green, Eli Magen, Avivit Golan-Cohen, Shlomo Vinker, Eytan Ruppin

Open access · goldAbstract read
In one paragraph

Article in Microorganisms, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 40% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 2 countries.

Ariel IsraelLeumit Health Services, Tel-Aviv 6473817, Israel.
Alejandro A SchäfferCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.ORCID 0000-0002-2147-8033
Eugene MerzonLeumit Health Services, Tel-Aviv 6473817, Israel.
Ilan GreenLeumit Health Services, Tel-Aviv 6473817, Israel.
Eli MagenLeumit Health Services, Tel-Aviv 6473817, Israel.ORCID 0000-0002-7713-423X
Avivit Golan-CohenLeumit Health Services, Tel-Aviv 6473817, Israel.
Shlomo VinkerLeumit Health Services, Tel-Aviv 6473817, Israel.
Eytan RuppinCancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Tel Aviv University · ILNational Cancer Institute · USAriel University · ILBen-Gurion University of the Negev · ILClalit Health Services · IL

Funding

Discovering Affective Drug Combinations for Treating Covid-19ZIABC012000 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI RUPPIN, EYTAN · 2020 to 2022
$2.3M
NCI NIH HHS Intramural Research Program
6 · The paper itself

Abstract

Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model's performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online.

Indexed as

calculatorCOVID-19diabetesdisease severitykidney diseaseobesity

Identifiers

PMID35744754
PMCPMC9229599
OpenAlexW4283076384

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.