A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Sociodemographic and clinical characteristics associated with COVID mortality among hospitalized patients in Rajasthan: A retrospective observational study. | LitMetric

Background: It has been over a year since the declaration of novel coronavirus disease (COVID-19) as pandemic by World Health Organization on March 11, 2020. Although mortality in India is low, as compared to western countries, the steady increase in the number of cases is still a worrying sign. The objectives of this study were to identify and quantify the association between sociodemographic and clinical characteristics with mortality among patients, suffering from COVID-19 at a tertiary care hospital in Udaipur, Rajasthan.

Material And Methods: This retrospective observational study involved 824 patients hospitalized for COVID 19 at a tertiary hospital in Udaipur, who were discharged or had died. Electronic health records of the patients were accessed to retrieve the sociodemographic information (age, gender, residence, religion, socioeconomic status), history of exposure, clinical characteristics on admission, comorbidities, and outcomes (recovery or death). The Cox regression model was used to calculate associations between mortality and baseline characteristics in the form of hazard ratios (HRs).

Results: Mortality in this study was found to be 5.82%. The mean age of the patients was 48.14 ± 16.2 years. The median time from time of admission to discharge was 8 days (interquartile range (IQR) 5-11), whereas the median time to death was 5 days (IQR 4-10). The variables found to be associated with higher mortality were age (HR 1.17; 95% confidence interval (CI) 1.15-1.24), residing in urban area (HR 1.29; 95% CI 1.17-2.15), diabetes mellitus (HR 1.3; CI 1.02-5.57), and patients having both diabetes and hypertension (HR 2.4; CI 1.69-3.14).

Conclusion: Sociodemographic variables and comorbidities impact the mortality among COVID 19 patients. The variables most clearly associated with a greater hazard of death were older age, urban area, diabetes, and having both diabetes and hypertension.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565107PMC
http://dx.doi.org/10.4103/jfmpc.jfmpc_445_21DOI Listing

Publication Analysis

Top Keywords

clinical characteristics
12
sociodemographic clinical
8
retrospective observational
8
observational study
8
hospital udaipur
8
median time
8
urban area
8
diabetes hypertension
8
mortality
7
patients
7

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!