Cargando…
A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan
BACKGROUND: The number of COVID-19 infected patients has been soaring in the Middle East countries. The disease poses a significant threat, decisions about prioritizing care should be made in accordance with the proven risk factors for complications. OBJECTIVE: The present study provides the first b...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936757/ https://www.ncbi.nlm.nih.gov/pubmed/33984658 http://dx.doi.org/10.1016/j.jiph.2021.02.010 |
_version_ | 1783661252964253696 |
---|---|
author | Odeh, Mohanad M. Al Qaissieh, Rami Tarifi, Amjed A. Kilani, Muna M. Tadros, Ramzy E. Al khashman, Abedrazzaq I. Alzoubi, Karem H. |
author_facet | Odeh, Mohanad M. Al Qaissieh, Rami Tarifi, Amjed A. Kilani, Muna M. Tadros, Ramzy E. Al khashman, Abedrazzaq I. Alzoubi, Karem H. |
author_sort | Odeh, Mohanad M. |
collection | PubMed |
description | BACKGROUND: The number of COVID-19 infected patients has been soaring in the Middle East countries. The disease poses a significant threat, decisions about prioritizing care should be made in accordance with the proven risk factors for complications. OBJECTIVE: The present study provides the first bespoke prediction model in the Middle East to identify COVID-19 patients, who are at higher risk for complications. METHOD: A case-control study design was adopted to compare the characteristics of successfully recovered patients with those who had complications. Complications were defined as admission to the intensive care unit, mechanical ventilation, sepsis or septic shock, pneumonia or respiratory failure, and death. The prediction model was created through multivariable logistic regression. Overall statistical significance tests for the model were carried out. RESULTS: All COVID-19 infected hospitalized patients (n = 133) in Amman – Jordan were included in the study. Successfully recovered were 125 patients. The median age (IRQ) was 26 (10–40). Almost 30% were >40 years. Patients with complications were eight patients, age 63 (51.5–71.5). The prediction model identified the following variables as risk factors: diabetes (OR = 59.7; 95% CI: 3.5–1011.5, p = 0.005), fever (OR = 24.8; 95% CI: 1.4–447.3, p = 0.029), SHORTNESS OF BREATH (OR = 15.9; 95% CI: 1.3–189.7, p = 0.029), body mass index (OR = 0.74; 95% CI: 0.61–0.88, p = 0.001), abnormal Neutrophils (OR = 16.8; 95% CI: 1.0–292.0, p = 0.053). Prediction model was statistically significant, χ(2)(5) = 86.1, p < 0.0005. CONCLUSIONS: Unlike reports from China, the most influential variables that led to disease progression in Jordanian patients were diabetes, fever, shortness of breath, body mass index, and abnormal neutrophils. Similar to reports from the USA, smoking was not a leading factor for complications. Comorbidities and patient health status, rather than age, were the primary risk factors for complications. Treatment with Hydroxychloroquine showed no protective effect. |
format | Online Article Text |
id | pubmed-7936757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79367572021-03-08 A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan Odeh, Mohanad M. Al Qaissieh, Rami Tarifi, Amjed A. Kilani, Muna M. Tadros, Ramzy E. Al khashman, Abedrazzaq I. Alzoubi, Karem H. J Infect Public Health Article BACKGROUND: The number of COVID-19 infected patients has been soaring in the Middle East countries. The disease poses a significant threat, decisions about prioritizing care should be made in accordance with the proven risk factors for complications. OBJECTIVE: The present study provides the first bespoke prediction model in the Middle East to identify COVID-19 patients, who are at higher risk for complications. METHOD: A case-control study design was adopted to compare the characteristics of successfully recovered patients with those who had complications. Complications were defined as admission to the intensive care unit, mechanical ventilation, sepsis or septic shock, pneumonia or respiratory failure, and death. The prediction model was created through multivariable logistic regression. Overall statistical significance tests for the model were carried out. RESULTS: All COVID-19 infected hospitalized patients (n = 133) in Amman – Jordan were included in the study. Successfully recovered were 125 patients. The median age (IRQ) was 26 (10–40). Almost 30% were >40 years. Patients with complications were eight patients, age 63 (51.5–71.5). The prediction model identified the following variables as risk factors: diabetes (OR = 59.7; 95% CI: 3.5–1011.5, p = 0.005), fever (OR = 24.8; 95% CI: 1.4–447.3, p = 0.029), SHORTNESS OF BREATH (OR = 15.9; 95% CI: 1.3–189.7, p = 0.029), body mass index (OR = 0.74; 95% CI: 0.61–0.88, p = 0.001), abnormal Neutrophils (OR = 16.8; 95% CI: 1.0–292.0, p = 0.053). Prediction model was statistically significant, χ(2)(5) = 86.1, p < 0.0005. CONCLUSIONS: Unlike reports from China, the most influential variables that led to disease progression in Jordanian patients were diabetes, fever, shortness of breath, body mass index, and abnormal neutrophils. Similar to reports from the USA, smoking was not a leading factor for complications. Comorbidities and patient health status, rather than age, were the primary risk factors for complications. Treatment with Hydroxychloroquine showed no protective effect. The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2021-06 2021-03-06 /pmc/articles/PMC7936757/ /pubmed/33984658 http://dx.doi.org/10.1016/j.jiph.2021.02.010 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Odeh, Mohanad M. Al Qaissieh, Rami Tarifi, Amjed A. Kilani, Muna M. Tadros, Ramzy E. Al khashman, Abedrazzaq I. Alzoubi, Karem H. A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan |
title | A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan |
title_full | A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan |
title_fullStr | A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan |
title_full_unstemmed | A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan |
title_short | A prediction model of risk factors for complications among SARS-CoV2 positive patients: Cases from Jordan |
title_sort | prediction model of risk factors for complications among sars-cov2 positive patients: cases from jordan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936757/ https://www.ncbi.nlm.nih.gov/pubmed/33984658 http://dx.doi.org/10.1016/j.jiph.2021.02.010 |
work_keys_str_mv | AT odehmohanadm apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT alqaissiehrami apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT tarifiamjeda apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT kilanimunam apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT tadrosramzye apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT alkhashmanabedrazzaqi apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT alzoubikaremh apredictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT odehmohanadm predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT alqaissiehrami predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT tarifiamjeda predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT kilanimunam predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT tadrosramzye predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT alkhashmanabedrazzaqi predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan AT alzoubikaremh predictionmodelofriskfactorsforcomplicationsamongsarscov2positivepatientscasesfromjordan |