Parashar Lokesh, Shekhar Himanshu, Arya Hina, Vig Shankar Lal, Prasad Jagdish, Meshram Girish Gulab
Department of Statistics, Amity School of Applied Sciences, Amity University, Jaipur 303002, Rajasthan, India.
Department of Community Medicine, Shri Atal Bihari Vajpayee Government Medical College, Chhainsa, Faridabad 121001, Haryana, India.
Acta Inform Med. 2025;33(1):23-29. doi: 10.5455/aim.2024.33.23-29.
The coronavirus disease 2019 (COVID-19) pandemic significantly impacted global health, with India experiencing one of the highest case and death tolls. However, data specific to India's sociodemographic and clinical factors influencing COVID-19 mortality remains limited.
This study aimed to identify sociodemographic and clinical factors associated with COVID-19 mortality in India.
This retrospective, cross-sectional study analyzed medical records of 4961 adult COVID-19 patients admitted to a tertiary care center in North India, from April 2020 to December 2021. Sociodemographic and clinical data were captured using a structured proforma. Univariate analysis (chi-square test) and Kaplan-Meier survival analysis were performed to identify factors associated with mortality.
Of the 4961 patients, 557 (11.2%) died, and 4404 (88.8%) survived. Increased age, rural residency, professional occupation, and comorbidities (diabetes and hypertension), multimorbidity, increased disease severity, cold and flu symptoms, breathlessness, and the need for intensive care unit (ICU) admission and ventilator support were significantly (P <0.05) associated with higher COVID-19 mortality. While some associations were observed with sociodemographic factors like religion, education level, and monthly family income in univariate analysis, these were not significant in survival analysis.
In this cohort of COVID-19 patients in India, advanced age, rural residency, professional occupation, comorbidities, multimorbidity, severe symptoms, and the need for ICU admission and ventilator support were identified as significant risk factors for mortality. Early identification and intervention for these high-risk groups may improve survival rates.
2019年冠状病毒病（COVID-19）大流行对全球健康产生了重大影响，印度是病例数和死亡人数最多的国家之一。然而，关于影响印度COVID-19死亡率的社会人口统计学和临床因素的具体数据仍然有限。
本研究旨在确定印度与COVID-19死亡率相关的社会人口统计学和临床因素。
这项回顾性横断面研究分析了2020年4月至2021年12月期间入住印度北部一家三级护理中心的4961例成年COVID-19患者的病历。使用结构化表格收集社会人口统计学和临床数据。进行单因素分析（卡方检验）和Kaplan-Meier生存分析以确定与死亡率相关的因素。
在4961例患者中，557例（11.2%）死亡，4404例（88.8%）存活。年龄增加、农村居住、职业、合并症（糖尿病和高血压）、多种合并症、疾病严重程度增加、感冒和流感症状、呼吸困难以及需要入住重症监护病房（ICU）和呼吸机支持与较高的COVID-19死亡率显著相关（P<0.05）。虽然在单因素分析中观察到一些与宗教、教育水平和家庭月收入等社会人口统计学因素的关联，但在生存分析中这些并不显著。
在印度的这一队列COVID-19患者中，高龄、农村居住、职业、合并症、多种合并症、严重症状以及需要入住ICU和呼吸机支持被确定为死亡率的重要危险因素。对这些高危人群进行早期识别和干预可能会提高生存率。
