From the Department of Anesthesiology and Critical Care, Columbia University College of Physicians and Surgeons, New York, New York.
Department of Biostatistics, Icahn School of Medicine at Mt Sinai, New York, New York.
Anesth Analg. 2019 Jun;128(6):1286-1291. doi: 10.1213/ANE.0000000000003770.
Surgical care is essential to improving population health, but metrics to monitor and evaluate the continuum of surgical care delivery have rarely been applied in low-resource settings, and improved efforts at benchmarking progress are needed. The objective of this study was to measure the intraoperative mortality at a Central Referral Hospital in Malawi, evaluate whether there have been changes in intraoperative mortality between 2 time periods, and assess factors associated with intraoperative mortality.
This was a retrospective cohort study of patients undergoing surgery at Kamuzu Central Hospital in Lilongwe, Malawi. Data describing daily consecutive operative cases were collected prospectively during 2 time periods: 2004-2006 (early cohort) and 2015-2016 (late cohort). The primary outcome was intraoperative mortality. Inverse probability of treatment weighting was used to analyze the association of intraoperative mortality with time using logistic regression models. Multivariable logistic models were performed to evaluate factors associated with intraoperative mortality.
There were 21,090 surgeries performed during the 2 time periods, with 15,846 (75%) and 5244 (25%) completed from 2004 to 2006 and 2015 to 2016, respectively. Intraoperative mortality in the early cohort was 57 deaths per 100,000 surgeries (95% confidence interval [CI], 26-108) and in the late cohort was 133 per 100,000 surgeries (95% CI, 56-286), with 76 per 100,000 surgeries (95% CI, 44-124) overall. After applying inverse probability of treatment weighting, there was no evidence of an association between time periods and intraoperative mortality (odds ratio [OR], 1.6; 95% CI, 0.9-2.8; P = .08). Factors associated with intraoperative mortality, adjusting for demographics, included American Society of Anesthesiology physical status III or IV versus I or II (OR, 4.4; 95% CI, 1.5-12.5; P = .006) and emergency versus elective surgery (OR, 7.7; 95% CI, 2.5-23.6; P < .001).
Intraoperative mortality in the study hospital in Malawi is high and has not improved over time. These data demonstrate an urgent need to improve the safety and quality of perioperative care in developing countries and integrate perioperative care into global health efforts.
外科护理对改善人口健康至关重要，但在资源匮乏的环境中，很少有监测和评估外科护理连续性的指标，需要改进基准评估进展的工作。本研究的目的是测量马拉维中央转诊医院的术中死亡率，评估两个时期之间术中死亡率是否有所变化，并评估与术中死亡率相关的因素。
这是一项对马拉维利隆圭卡姆祖中央医院接受手术的患者进行的回顾性队列研究。在两个时期（2004-2006 年（早期队列）和 2015-2016 年（晚期队列））前瞻性收集描述每日连续手术病例的数据。主要结局是术中死亡率。采用逆概率处理加权法（inverse probability of treatment weighting），通过逻辑回归模型分析术中死亡率与时间的关系。进行多变量逻辑模型以评估与术中死亡率相关的因素。
两个时期共进行了 21090 例手术，2004-2006 年完成 15846 例（75%），2015-2016 年完成 5244 例（25%）。早期队列的术中死亡率为每 100000 例手术 57 例死亡（95%置信区间[CI]，26-108），晚期队列为每 100000 例手术 133 例死亡（95%CI，56-286），总体为每 100000 例手术 76 例死亡（95%CI，44-124）。应用逆概率处理加权后，时期与术中死亡率之间无关联证据（比值比[OR]，1.6；95%CI，0.9-2.8；P =.08）。在调整人口统计学因素后，与术中死亡率相关的因素包括美国麻醉医师协会身体状况 III 或 IV 级与 I 或 II 级（OR，4.4；95%CI，1.5-12.5；P =.006）和急症与择期手术（OR，7.7；95%CI，2.5-23.6；P <.001）。
马拉维研究医院的术中死亡率很高，且随时间无改善。这些数据表明，迫切需要提高发展中国家围手术期护理的安全性和质量，并将围手术期护理纳入全球卫生工作中。
