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Analysis of Deaths and Favorable Developments of Patients with SARS-CoV-2 Hospitalized in the Largest Hospital for Infectious Diseases and Pneumo-Phthisiology in the West of the Country. | LitMetric

AI Article Synopsis

  • Romania experienced severe impacts from COVID-19, with over 1.91 million cases and 59,257 deaths, prompting a study to identify death predictors in hospitalized patients.
  • The study included 139 deceased patients and 275 who were discharged, employing statistical methods like logistic regression and Cox regression to analyze data.
  • Key predictors of death identified were coagulopathy history, high neutrophil percentage, low blood oxygenation levels, and factors like dyspnea, ICU admission, and heart damage that influenced patient outcomes.

Article Abstract

Purpose: Romania is one of the European countries that has been hit the hardest by the severe acute respiratory syndrome caused by the new coronavirus SARS-CoV-2, with over 1.91 million reported cases and over 59,257 deaths. The aim of this study was to identify the main predictors of death in hospitalized patients.

Patients And Methods: In the period from 1 March 2020 to 30 June 2021, an observational, retrospective, randomized, case-control study was conducted, which included a sample of 139 patients who died in hospital and another sample of 275 patients who had been discharged in an improved or healed condition. Confirmation of COVID-19 cases was performed by RT-PCR from nasopharyngeal and oropharyngeal exudates. Statistical data were analyzed by logistic regression, Cox regression and a comparison of survival curves by the log-rank (Mantel-Cox) test.

Results: The most powerful logistic regression model identified the following independent predictors of death: history of coagulopathy HR = 30.73 [1.94-487.09], p = 0.015; high percentage of neutrophils HR = 1.09 [1.01-1.19], p = 0.027; and decreased blood-oxygenation HR = 53881.97 [1762.24-1647489.44], p < 0.001. Cox regression identified the following factors that influenced the evolution of cases: history of coagulopathy HR = 2.44 [1.38-4.35], p = 0.000; O saturation HR = 0.98 [0.96-0.99], p = 0.043; serum creatinine HR = 1.23 [1.08-1.39], p = 0.001; dyspnea on admission HR = 2.99 [1.42-6.30], p = 0.004; hospitalization directly in the ICU HR = 3.803 [1.97-7.33], p < 0.001; heart damage HR = 16.76 [1.49-188.56], p = 0.022; and decreased blood-oxygenation HR = 35.12 [5.92-208.19], p < 0.001.

Conclusion: Knowledge of the predictors of death in hospitalized patients allows for the future optimization of triage and therapeutic case management for COVID-19.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976499PMC
http://dx.doi.org/10.2147/IJGM.S359483DOI Listing

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