Centre for Community Medicine, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Department of Pulmonary, Critical Care and Sleep Medicine, AIIMS, New Delhi, India.
Am J Trop Med Hyg. 2023 Mar 13;108(4):727-733. doi: 10.4269/ajtmh.22-0705. Print 2023 Apr 5.
Severe acute respiratory syndrome coronavirus 2 disease (COVID-19) has caused more than 6 million deaths globally. Understanding predictors of mortality will help in prioritizing patient care and preventive approaches. This was a multicentric, unmatched, hospital-based case-control study conducted in nine teaching hospitals in India. Cases were microbiologically confirmed COVID-19 patients who died in the hospital during the period of study and controls were microbiologically confirmed COVID-19 patients who were discharged from the same hospital after recovery. Cases were recruited sequentially from March 2020 until December-March 2021. All information regarding cases and controls was extracted retrospectively from the medical records of patients by trained physicians. Univariable and multivariable logistic regression was done to assess the association between various predictor variables and deaths due to COVID-19. A total of 2,431 patients (1,137 cases and 1,294 controls) were included in the study. The mean age of patients was 52.8 years (SD: 16.5 years), and 32.1% were females. Breathlessness was the most common symptom at the time of admission (53.2%). Increasing age (adjusted odds ratio [aOR]: 46-59 years, 3.4 [95% CI: 1.5-7.7]; 60-74 years, 4.1 [95% CI: 1.7-9.5]; and ≥ 75 years, 11.0 [95% CI: 4.0-30.6]); preexisting diabetes mellitus (aOR: 1.9 [95% CI: 1.2-2.9]); malignancy (aOR: 3.1 [95% CI: 1.3-7.8]); pulmonary tuberculosis (aOR: 3.3 [95% CI: 1.2-8.8]); breathlessness at the time of admission (aOR: 2.2 [95% CI: 1.4-3.5]); high quick Sequential Organ Failure Assessment score at the time of admission (aOR: 5.6 [95% CI: 2.7-11.4]); and oxygen saturation < 94% at the time of admission (aOR: 2.5 [95% CI: 1.6-3.9]) were associated with mortality due to COVID-19. These results can be used to prioritize patients who are at increased risk of death and to rationalize therapy to reduce mortality due to COVID-19.
严重急性呼吸综合征冠状病毒 2 型疾病(COVID-19)已在全球造成超过 600 万人死亡。了解死亡的预测因素将有助于优先考虑患者护理和预防措施。这是一项在印度 9 所教学医院进行的多中心、不匹配、基于医院的病例对照研究。病例为研究期间在医院死亡的经微生物学证实的 COVID-19 患者,对照为从同一医院康复出院的经微生物学证实的 COVID-19 患者。病例于 2020 年 3 月至 2021 年 12 月期间连续招募。由经过培训的医生从患者的病历中回顾性提取所有关于病例和对照的信息。采用单变量和多变量逻辑回归评估各种预测变量与 COVID-19 死亡之间的关联。共纳入 2431 例患者(1137 例病例和 1294 例对照)。患者的平均年龄为 52.8 岁(标准差:16.5 岁),32.1%为女性。入院时最常见的症状是呼吸困难(53.2%)。年龄增长(调整后的优势比[aOR]:46-59 岁,3.4[95%可信区间:1.5-7.7];60-74 岁,4.1[95%可信区间:1.7-9.5];≥75 岁,11.0[95%可信区间:4.0-30.6]);合并糖尿病(aOR:1.9[95%可信区间:1.2-2.9]);恶性肿瘤(aOR:3.1[95%可信区间:1.3-7.8]);肺结核(aOR:3.3[95%可信区间:1.2-8.8]);入院时呼吸困难(aOR:2.2[95%可信区间:1.4-3.5]);入院时快速序贯器官衰竭评估(SOFA)评分较高(aOR:5.6[95%可信区间:2.7-11.4]);入院时血氧饱和度<94%(aOR:2.5[95%可信区间:1.6-3.9])与 COVID-19 死亡相关。这些结果可用于优先考虑死亡风险增加的患者,并合理治疗以降低 COVID-19 死亡率。