Hajj Albert El, Labban Muhieddine, Ploussard Guillaume, Zarka Jabra, Abou Heidar Nassib, Mailhac Aurelie, Tamim Hani
Division of Urology, Department of Surgery, American University of Beirut, Beirut, Lebanon.
Department of Urology, La Croix du Sud Hospital, Quint-Fonsegrives, France.
Ther Adv Urol. 2022 Mar 18;14:17562872221080737. doi: 10.1177/17562872221080737. eCollection 2022 Jan-Dec.
The objective of this study is to determine the preoperative patient characteristics predicting prolonged length of hospital stay (pLOS) following robotic-assisted radical prostatectomy (RARP).
The National Surgical Quality Improvement Program (NSQIP) database was used to select patients who underwent RARP without other concomitant surgeries between 2008 and 2016. Patients' demographics, comorbidities, and laboratory markers were collected to evaluate their role in predicting pLOS. The pLOS was defined as length of stay (LOS) >2 days. A multinomial logistic regression was constructed adjusting for postoperative surgical complications to assess for the predictors of pLOS.
We obtained data for 31,253 patients of which 20,774 (66.5%) patients stayed ⩽1 day, 6993 (22.4%) patients stayed for 2 days, and 3486 (11.2%) patients stayed for >2 days. Demographic variables - including body mass index (BMI) <18.5: odds ratio (OR) = 2.8, 95% confidence interval (CI) = [1.7-4.8]; smoking: OR = 1.2, 95% CI = [1.1-1.4]; and dependent functional status: OR = 3.1, 95% CI = [1.6-6.0] - were predictors of pLOS. Comorbidities - such as heart failure: OR = 4.6, 95% CI = [2.0-10.8]; being dialysis dependent: OR = 2.7, 95% CI = [1.4-5.0]; and predisposition to bleeding: OR = 2.0, 95% CI = [1.5-2.7] - were the strongest predictors of extended hospitalization. In addition, pLOS was more likely to be associated with postoperative bleeding, renal, or pulmonary complications.
Preoperative patient characteristics and comorbidities can predict pLOS. These findings can be used preoperatively for risk assessment and patient counseling.
本研究的目的是确定机器人辅助根治性前列腺切除术（RARP）后预测住院时间延长（pLOS）的术前患者特征。
使用国家外科质量改进计划（NSQIP）数据库选择2008年至2016年间接受RARP且无其他同期手术的患者。收集患者的人口统计学、合并症和实验室指标，以评估它们在预测pLOS中的作用。pLOS定义为住院时间（LOS）>2天。构建多项逻辑回归模型，并对术后手术并发症进行校正，以评估pLOS的预测因素。
我们获得了31253例患者的数据，其中20774例（66.5%）患者住院时间≤1天，6993例（22.4%）患者住院2天，3486例（11.2%）患者住院时间>2天。人口统计学变量——包括体重指数（BMI）<18.5：比值比（OR）=2.8，95%置信区间（CI）=[1.7-4.8]；吸烟：OR=1.2，95%CI=[1.1-1.4]；以及依赖性功能状态：OR=3.1，95%CI=[1.6-6.0]——是pLOS的预测因素。合并症——如心力衰竭：OR=4.6，95%CI=[2.0-IO.8]；依赖透析：OR=2.7，95%CI=[1.4-5.0]；以及出血倾向：OR=2.0，95%CI=[1.5-2.7]——是延长住院时间的最强预测因素。此外，pLOS更可能与术后出血、肾脏或肺部并发症相关。
术前患者特征和合并症可预测pLOS。这些发现可在术前用于风险评估和患者咨询。
