Alternative discharge destination following lobectomy: Analysis of a national quality improvement database

Victoria Yin MD, MPH , Sean C. Wightman MD , Takashi Harano MD , Scott M. Atay MD , Anthony W. Kim MD
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Abstract

Objective

To determine factors significantly associated with alternative discharge destination (ADCD) following lobectomy, including the modified 5-item Frailty Index (mFI-5).

Methods

Patients in the 2017-2020 NSQIP who underwent elective lobectomy and were admitted from home were included, with ADCD defined as a patient who was discharged to any nonhome location. Four multivariable logistic regression models for ADCD were evaluated for predictive power. Model A was created from backward selection of variables significantly associated with ADCD in bivariate analyses, model B was the mFI-5, model C was mFI-5 and a minimally invasive approach, and model D was mFI-5 and age group.

Results

Among the 15,868 patients, 687 (4.3%) experienced ADCD. Model A identified older age, hypertension, dyspnea, history of chronic obstructive pulmonary disease, and increased length of stay as significantly associated with ADCD. A minimally invasive approach was significantly protective of ADCD. Model A had the best predictive power of the models tested (C-statistic = 0.785). Model B, which assessed mFI-5 alone, had fair predictive power (C-statistic = 0.637). Adding surgical approach (C-statistic = 0.673; model C) or age group (C-statistic = 0.682; model D) as independent variables with mFI-5 improved model fit.

Conclusions

Patients who were frail or age >75 years were more likely to have postlobectomy ADCD. Although the variables identified in model A better predict ADCD, consideration of surgical approach or age with mFI-5 can help surgeons anticipate discharge destination following lobectomy.
肺叶切除术后的出院选择:国家质量改进数据库分析
目的 确定与肺叶切除术后替代出院目的地(ADCD)明显相关的因素,包括改良的 5 项虚弱指数(mFI-5)。方法 纳入 2017-2020 年 NSQIP 中接受择期肺叶切除术并从家中入院的患者,ADCD 定义为出院到任何非家庭所在地的患者。评估了 ADCD 的四个多变量逻辑回归模型的预测能力。模型 A 是根据双变量分析中与 ADCD 显著相关的变量逆向选择创建的,模型 B 是 mFI-5,模型 C 是 mFI-5 和微创方法,模型 D 是 mFI-5 和年龄组。模型 A 发现年龄较大、高血压、呼吸困难、慢性阻塞性肺病病史和住院时间延长与 ADCD 显著相关。微创方法对 ADCD 有明显保护作用。在所测试的模型中,模型 A 的预测能力最强(C 统计量 = 0.785)。单独评估 mFI-5 的模型 B 预测能力一般(C 统计量 = 0.637)。将手术方式(C-统计量=0.673;模型 C)或年龄组(C-统计量=0.682;模型 D)作为 mFI-5 的自变量可提高模型的拟合度。虽然模型 A 中确定的变量能更好地预测 ADCD,但考虑手术方式或年龄与 mFI-5 可以帮助外科医生预测肺叶切除术后的出院去向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.70
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