University Hospital Basel, Department for Anaesthesia, Surgical Intensive Care, Prehospital Emergency Medicine and Pain Therapy, Basel, Switzerland.
University of Basel, Department of Public Health, Institute of Nursing Science, Basel, Switzerland.
Swiss Med Wkly. 2019 Sep 30;149:w20122. doi: 10.4414/smw.2019.20122. eCollection 2019 Sep 9.
Chronically critical illness is highly relevant in intensive care units, but the definitions in literature vary greatly. The timely detection of prolonged intensive care unit length of stay could support care planning for chronically critical ill patients.
To develop and validate a risk score for predicting prolonged length of stay in the surgical intensive care unit.
This single centre cohort study formed part of a nursing-led project in one surgical intensive care unit. We examined the performance of seven predefined predictive factors of prolonged (>20 days) intensive care unit length of stay in adults on the seventh day of stay in intensive care to develop (n = 304) and validate (n = 101) a risk score. Candidate variables (Charlson Comorbidity Index, Simplified Acute Physiology Score II, minimum plasma albumin, need for anti-infective drugs, time of mechanical ventilation, main feeding method and score on the Sedation-Agitation Scale) were analysed using multiple logistical regression analysis.
Our risk score assigned different points to the following conditions: Charlson Comorbidity Index >2, minimum albumin <20 g/l between days 1 and 7, mechanical ventilation >14 hr on day 7 and the need for parenteral nutrition on day 7. For a validation data set (n = 101), the area under the receiver operating characteristic curve was 0.89 (95% confidence interval 0.770.87). At a cut-off value of 100 points, the degree of sensitivity was 88%, the specificity 75%, the positive predictive value 53%, the negative predictive value 95%, and the model fit R2 0.40.
Our model allowed the timely detection of prolonged intensive care unit length of stay with four candidate predictive factors. The timely identification of patients with prolonged intensive care unit length of stay is possible and could influence the person-centred prevention of chronically critical illness and adequate resource allocation. (Trial registration no DRKS 00017073)
慢性危重病在重症监护病房中非常重要，但文献中的定义差异很大。及时发现长时间入住重症监护病房可以为慢性危重病患者的护理计划提供支持。
开发和验证一种预测外科重症监护病房患者住院时间延长的风险评分。
这项单中心队列研究是在一个外科重症监护病房进行的护理主导项目的一部分。我们检查了七个预先定义的预测因素在第七天入住重症监护病房的成年人中对延长（> 20 天）重症监护病房住院时间的表现，以开发（n = 304）和验证（n = 101）风险评分。候选变量（Charlson 合并症指数、简化急性生理学评分 II、最低血浆白蛋白、抗感染药物的需要、机械通气时间、主要喂养方法和镇静躁动评分）使用多元逻辑回归分析进行分析。
我们的风险评分对以下情况给予不同的分数：Charlson 合并症指数> 2、第 1 天至第 7 天之间的最低白蛋白< 20 g/l、第 7 天的机械通气时间> 14 小时和第 7 天的肠外营养需求。对于验证数据集（n = 101），接收者操作特征曲线下面积为 0.89（95%置信区间 0.77-0.87）。在 100 分的截断值下，敏感性为 88%，特异性为 75%，阳性预测值为 53%，阴性预测值为 95%，模型拟合 R2 为 0.40。
我们的模型使用四个候选预测因素能够及时检测到延长的重症监护病房住院时间。及时识别延长重症监护病房住院时间的患者是可能的，并且可以影响以患者为中心的预防慢性危重病和适当的资源分配。（试验注册号 DRKS 00017073）
