Department of Orthopedics Surgery, Icahn School of Medicine at Mount Sinai, New York, NY.
NeuroSpine Surgery Research Group, University of New South Wales, Sydney, Australia.
Spine (Phila Pa 1976). 2017 Oct 15;42(20):1538-1544. doi: 10.1097/BRS.0000000000002140.
Retrospective study of prospectively collected data.
To identify risk factors for nonhome patient discharge after elective anterior cervical discectomy and fusion (ACDF).
ACDF is one of the most performed spinal procedures and this is expected to increase in the coming years. To effectively deal with an increasing patient volume, identifying variables associated with patient discharge destination can expedite placement applications and subsequently reduce hospital length of stay.
The 2011 to 2014 ACS-NSQIP database was queried using Current Procedural Terminology (CPT) codes 22551 or 22554. Patients were divided into two cohorts based on discharge destination. Bivariate and multivariate logistic regression analyses were employed to identify predictors for patient discharge destination and extended hospital length of stay.
A total of 14,602 patients met the inclusion criteria for the study of which 498 (3.4%) had nonhome discharge. Multivariate logistic regression found that Hispanic versus Black race/ethnicity (odds ratio, OR =0.21, 0.05-0.91, P =0.037), American Indian or Alaska Native, Asian, Native Hawaiian or Pacific Islander versus Black race/ethnicity (OR = 0.52, 0.34-0.80, p-value = 0.003), White versus Black race/ethnicity (OR = 0.55, 0.42-0.71), elderly age ≥65 years (OR = 3.32, 2.72-4.06), obesity (OR = 0.77, 0.63-0.93, P = 0.008), diabetes (OR = 1.32, 1.06-1.65, P = 0.013), independent versus partially/totally dependent functional status (OR = 0.11, 0.08-0.15), operation time ≥4 hours (OR = 2.46, 1.87-3.25), cardiac comorbidity (OR = 1.38, 1.10-1.72, P = 0.005), and ASA Class ≥3 (OR = 2.57, 2.05-3.20) were predictive factors in patient discharge to a facility other than home. In addition, multivariate logistic regression analysis also found nonhome discharge to be the most predictive variable in prolonged hospital length of stay.
Several predictive factors were identified in patient discharge to a facility other than home, many being preoperative variables. Identification of these factors can expedite patient discharge applications and potentially can reduce hospital stay, thereby reducing the risk of hospital acquired conditions and minimizing health care costs.
前瞻性收集数据的回顾性研究。
确定择期前路颈椎间盘切除融合术（ACDF）后非家庭出院的风险因素。
ACDF 是最常进行的脊柱手术之一，预计未来几年这一数字还会增加。为了有效地应对不断增加的患者数量，确定与患者出院去向相关的变量可以加快安置申请的速度，从而缩短住院时间。
使用当前程序术语（CPT）代码 22551 或 22554 对 2011 年至 2014 年 ACS-NSQIP 数据库进行查询。根据出院去向将患者分为两组。采用二变量和多变量逻辑回归分析确定患者出院去向和延长住院时间的预测因素。
共有 14602 名患者符合本研究的纳入标准，其中 498 名（3.4%）非家庭出院。多变量逻辑回归发现，与黑人种族/民族相比，西班牙裔/黑人种族/民族（比值比，OR=0.21，0.05-0.91，P=0.037）、美国印第安人或阿拉斯加原住民、亚洲人、原住民夏威夷人或太平洋岛民/黑人种族/民族（OR=0.52，0.34-0.80，p 值=0.003）、白人/黑人种族/民族（OR=0.55，0.42-0.71）、年龄≥65 岁（OR=3.32，2.72-4.06）、肥胖（OR=0.77，0.63-0.93，P=0.008）、糖尿病（OR=1.32，1.06-1.65，P=0.013）、独立/部分/完全依赖的功能状态（OR=0.11，0.08-0.15）、手术时间≥4 小时（OR=2.46，1.87-3.25）、心脏合并症（OR=1.38，1.10-1.72，P=0.005）和美国麻醉师协会（ASA）分级≥3（OR=2.57，2.05-3.20）是患者出院到其他机构而不是家庭的预测因素。此外，多变量逻辑回归分析还发现，非家庭出院是延长住院时间的最具预测性变量。
确定了患者出院到其他机构（而非家庭）的几个预测因素，其中许多是术前变量。识别这些因素可以加快患者出院申请的速度，并可能缩短住院时间，从而降低医院获得性疾病的风险，最大限度地降低医疗保健成本。
3 级。
