Evidence map›Paper›PMID 33901655›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2022

Development and validation of the CoV19-OM intensive care unit score: An early ICU identification for laboratory-confirmed SARS-CoV-2 patients from a retrospective cohort study in Oman.

Eduardo M Lacap, Abraham Varghese, Faryal Khamis, Maher Al Bahrani, Hamed Al Naamani, Shajidmon Kolamban, Samata Al Dowaiki, Huda Salim Al Shuaily

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Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Eduardo M LacapDepartment of Information Technology, University of Technology and Applied Science - HCT, Oman.
Abraham VargheseDepartment of Information Technology, University of Technology and Applied Science - HCT, Oman.
Faryal KhamisInfectious Diseases Department, Royal Hospital, Oman. Electronic address: khami001@gmail.com.
Maher Al BahraniAnesthesia and Critical Care Department, Royal Hospital, Oman.
Hamed Al NaamaniPharmaceutical Care Department, Royal Hospital, Oman.
Shajidmon KolambanDepartment of Information Technology, University of Technology and Applied Science - HCT, Oman.
Samata Al DowaikiInfectious Diseases Department, Royal Hospital, Oman.
Huda Salim Al ShuailyDepartment of Information Technology, University of Technology and Applied Science - HCT, Oman.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop and validate a clinical score that will identify potential admittance to an intensive care unit (ICU) for a coronavirus disease 2019 (COVID-19) case. MATERIALS AND

methodsThe clinical scoring system was developed using a least absolute shrinkage and selection operator logistic regression. The prediction algorithm was constructed and cross-validated using a development cohort of 313 COVID-19 patients, and was validated using an independent retrospective set of 64 COVID-19 patients.

resultsThe majority of patients were Omani in nationality (n = 181, 58%). Multivariate logistic regression identified eight independent predictors of ICU admission that were included in the clinical score: hospitalization (OR, 1.079; 95% CI, 1.058-1.100), absolute lymphocyte count (OR, 0.526; 95% CI, 0.379-0.729), C-reactive protein (OR, 1.009; 95% CI, 1.006-1.011), lactate dehydrogenase (OR, 1.0008; 95% CI, 1.0004-1.0012), CURB-65 score (OR, 2.666; 95% CI, 2.212-3.213), chronic kidney disease with an estimated glomerular filtration rate of less than 70 (OR, 0.249; 95% CI, 0.155-0.402), shortness of breath (OR, 3.494; 95% CI, 2.528-6.168), and bilateral infiltrates in chest radiography (OR, 6.335; 95% CI, 3.427-11.713). The mean area under a curve (AUC) for the development cohort was 0.86 (95% CI, 0.85-0.87), and for the validation cohort, 0.85 (95% CI, 0.82-0.88).

conclusionThis study presents a web application for identifying potential admittance to an ICU for a COVID-19 case, according to a clinical risk score based on eight significant characteristics of the patient (http://3.14.27.202/cov19-icu-score/).

Indexed as

COVID-19SARS-CoV-2Cohort StudiesHospitalizationHumansIntensive Care UnitsOmanRetrospective StudiesClinical scoreCOVID-19Intensive care unitOmanRisk factorSARS-CoV-2

Identifiers

PMID33901655
PMCPMC8065243

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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.