ArticleBMC infectious diseases2017
The predictors of 3- and 30-day mortality in 660 MERS-CoV patients.
Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 5 of them syntheses that pooled it.
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Who cites it
57 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Major bat-borne zoonotic viral epidemics in Asia and Africa: A systematic review and meta-analysis.Veterinary medicine and science · 2022Pooled it
- Predictors of mortality in patients with coronavirus disease 2019: a systematic review and meta-analysis.BMC infectious diseases · 2021Pooled it
- Impact of coronavirus syndromes on physical and mental health of health care workers: Systematic review and meta-analysis.Journal of affective disorders · 2020Pooled it
- Comparison of confirmed COVID-19 with SARS and MERS cases - Clinical characteristics, laboratory findings, radiographic signs and outcomes: A systematic review and meta-analysis.Reviews in medical virology · 2020Pooled it
- MERS transmission and risk factors: a systematic review.BMC public health · 2018Pooled it
- The Role of Immunosenescence and Inflammaging in the Susceptibility of Older Adults to SARS-CoV-2 Infection.Current pharmaceutical biotechnology · 2026Review
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- Lessons learnt from broad-spectrum coronavirus antiviral drug discovery.Expert opinion on drug discovery · 2024Review
- COVID-19: Clinical features, case fatality, and the effect of symptoms on mortality in hospitalized cases in Iran.Journal of Taibah University Medical Sciences · 2022Article
- An extended motif in the SARS-CoV-2 spike modulates binding and release of host coatomer in retrograde trafficking.Communications biology · 2022Article
- Dispersion of SARS-CoV-2 in air surrounding COVID-19-infected individuals with mild symptoms.Indoor air · 2022Article
- A Predictive Nomogram for Predicting Improved Clinical Outcome Probability in Patients with COVID-19 in Zhejiang Province, China.Engineering (Beijing, China) · 2022Article
- Over 60 years of age as an independent prognostic factor of in-hospital mortality among COVID-19 patients: a cohort study in an Iranian high-incidence area.Public health · 2021Article
- Risk factors associated with severe hospital burden of COVID-19 disease in Regione Lombardia: a cohort study.BMC infectious diseases · 2021Observational
- The effects of aging on host resistance and disease tolerance to SARS-CoV-2 infection.The FEBS journal · 2021Review
- Middle East Respiratory Syndrome (MERS) Virus-Pathophysiological Axis and the Current Treatment Strategies.AAPS PharmSciTech · 2021Review
- Genome-wide analysis of 10664 SARS-CoV-2 genomes to identify virus strains in 73 countries based on single nucleotide polymorphism.Virus research · 2021Article
- Outcome of Middle East Respiratory Syndrome (MERS) in hematology and oncology patients: A case series in Saudi Arabia.Journal of infection and public health · 2021Article
- Comparison of the clinical characteristics and mortality of adults infected with human coronaviruses 229E and OC43.Scientific reports · 2021Article
- Comparative profile for COVID-19 cases from China and North America: Clinical symptoms, comorbidities and disease biomarkers.World journal of clinical cases · 2021Article
Corrections and comments
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Authors and funding
1 author.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe mortality rate of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) patients is a major challenge in all healthcare systems worldwide. Because the MERS-CoV risk-standardized mortality rates are currently unavailable in the literature, the author concentrated on developing a method to estimate the risk-standardized mortality rates using MERS-CoV 3- and 30-day mortality measures.
methodsMERS-CoV data in Saudi Arabia is publicly reported and made available through the Saudi Ministry of Health (SMOH) website. The author studied 660 MERS-CoV patients who were reported by the SMOH between December 2, 2014 and November 12, 2016. The data gathered contained basic demographic information (age, gender, and nationality), healthcare worker, source of infection, pre-existing illness, symptomatic, severity of illness, and regions in Saudi Arabia. The status and date of mortality were also reported. Cox-proportional hazard (CPH) models were applied to estimate the hazard ratios for the predictors of 3- and 30-day mortality.
results3-day, 30-day, and overall mortality were found to be 13.8%, 28.3%, and 29.8%, respectively. According to CPH, multivariate predictors of 3-day mortality were elderly, non-healthcare workers, illness severity, and hospital-acquired infections (adjusted hazard ratio (aHR) =1.7; 8.8; 6.5; and 2.8, respectively). Multivariate predictors of 30-day mortality were elderly, non-healthcare workers, pre-existing illness, severity of illness, and hospital-acquired infections (aHR =1.7; 19.2; 2.1; 3.7; and 2.9, respectively).
conclusionsSeveral factors were identified that could influence mortality outcomes at 3 days and 30 days, including age (elderly), non-healthcare workers, severity of illness, and hospital-acquired infections. The findings can serve as a guide for healthcare practitioners by appropriately identifying and managing potential patients at high risk of death.
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