Department of Neurology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany.
Nursing Headquarters, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
BMC Geriatr. 2020 Feb 21;20(1):75. doi: 10.1186/s12877-020-1443-1.
The rising number of older multimorbid in-patients has implications for medical care. There is a growing need for the identification of factors predicting the needs of older patients in hospital environments. Our aim was to evaluate the use of clinical and functional patient characteristics for the prediction of medical needs in older hospitalized patients.
Two hundred forty-two in-patients (57.4% male) aged 78.4 ± 6.4 years, who were consecutively admitted to internal medicine departments of the University Hospital Essen between July 2015 and February 2017, were prospectively enrolled. Patients were assessed upon admission using the Identification of Seniors at Risk (ISAR) screening followed by comprehensive geriatric assessment (CGA). The CGA included standardized instruments for the assessment of activities of daily living (ADL), cognition, mobility, and signs of depression upon admission. In multivariable regressions we evaluated the association of clinical patient characteristics, the ISAR score and CGA results with length of hospital stay, number of nursing hours and receiving physiotherapy as indicators for medical needs. We identified clinical characteristics and risk factors associated with higher medical needs.
The 242 patients spent [median(Q1;Q3)]:9.0(4.0;16.0) days in the hospital, needed 2.0(1.5;2.7) hours of nursing each day, and 34.3% received physiotherapy. In multivariable regression analyses including clinical patient characteristics, ISAR and CGA domains, the factors age (β = - 0.19, 95% confidence interval (CI) = - 0.66;-0.13), number of admission diagnoses (β = 0.28, 95% CI = 0.16;0.41), ADL impairment (B = 6.66, 95% CI = 3.312;10.01), and signs of depression (B = 6.69, 95% CI = 1.43;11.94) independently predicted length of hospital stay. ADL impairment (B = 1.14, 95%CI = 0.67;1.61), cognition impairment (B = 0.57, 95% CI = 0.07;1.07) and ISAR score (β =0.26, 95% CI = 0.01;0.28) independently predicted nursing hours. The number of admission diagnoses (risk ratio (RR) = 1.06, 95% CI = 1.04;1.08), ADL impairment (RR = 3.54, 95% CI = 2.29;5.47), cognition impairment (RR = 1.77, 95% CI = 1.20;2.62) and signs of depression (RR = 1.99, 95% CI = 1.39;2.85) predicted receiving physiotherapy.
Among older in-patients at risk for functional decline, the number of comorbidities, reduced ADL, cognition impairment and signs of depression are important predictors of length of hospital stay, nursing hours, and receiving physiotherapy during hospital stay.
随着越来越多的老年多病住院患者的出现，医疗保健面临着挑战。因此，需要确定预测老年患者在医院环境中需求的因素。我们的目的是评估临床和功能患者特征在预测老年住院患者医疗需求方面的作用。
2015 年 7 月至 2017 年 2 月，我们连续纳入了 242 名（57.4%为男性）年龄为 78.4±6.4 岁的内科住院患者。入院时使用识别老年人风险（ISAR）筛查进行评估，然后进行全面的老年评估（CGA）。CGA 包括评估日常生活活动（ADL）、认知、移动能力和入院时抑郁症状的标准化工具。在多变量回归中，我们评估了临床患者特征、ISAR 评分和 CGA 结果与住院时间、护理时间和接受物理治疗之间的关系，这些都是医疗需求的指标。我们确定了与更高医疗需求相关的临床特征和危险因素。
242 名患者平均住院时间为 9.0（4.0；16.0）天，每天需要护理 2.0（1.5；2.7）小时，34.3%的患者接受物理治疗。在包括临床患者特征、ISAR 和 CGA 领域的多变量回归分析中，年龄（β=-0.19，95%置信区间（CI）=-0.66；-0.13）、入院诊断次数（β=0.28，95%CI=0.16；0.41）、ADL 障碍（B=6.66，95%CI=3.312；10.01）和抑郁症状（B=6.69，95%CI=1.43；11.94）是住院时间的独立预测因素。ADL 障碍（B=1.14，95%CI=0.67；1.61）、认知障碍（B=0.57，95%CI=0.07；1.07）和 ISAR 评分（β=0.26，95%CI=0.01；0.28）是护理时间的独立预测因素。入院诊断次数（风险比（RR）=1.06，95%CI=1.04；1.08）、ADL 障碍（RR=3.54，95%CI=2.29；5.47）、认知障碍（RR=1.77，95%CI=1.20；2.62）和抑郁症状（RR=1.99，95%CI=1.39；2.85）是接受物理治疗的独立预测因素。
在有功能下降风险的老年住院患者中，合并症数量、ADL 下降、认知障碍和抑郁症状是预测住院时间、护理时间和住院期间接受物理治疗的重要因素。
