Mayo Burn Center/Plastic & Reconstructive Surgery Department, Mayo Hospital, Lahore, Pakistan.
Mayo Burn Center/Plastic & Reconstructive Surgery Department, Mayo Hospital, Lahore, Pakistan.
J Surg Res. 2022 Nov;279:575-585. doi: 10.1016/j.jss.2022.06.044. Epub 2022 Aug 1.
To explore candidate parameters for their ability to predict survival and length of hospital stay (LOS) in thermal burns patients, to prepare multivariate predictive models for these two outcomes, and to compare performance of native models to other models.
A retrospective cohort study was undertaken based on record review. Data was extracted from files of patients admitted to a tertiary-care burn center in Lahore, Pakistan from January 1, 2020 to October 31, 2020. After univariate preselection, we prepared multivariate logistic regression models for each outcome of interest (survival and LOS). Multivariate models were tested and compared to other models.
Increasing total body surface area (TBSA) of burn was associated with reduced survival and prolonged length of hospital stay. Advancing age and full-thickness burns independently predicted decreased survival. Burn etiology showed prognostic value: petrol-flame burns predicted decreased survival and prolonged LOS; scald was associated with improved survival-odds and shorter LOS. The Survival-model consisted of (1) Baux score, (2) TBSA>40% and (3) serum albumin <3.5 g/dL (AUC = 0.968, Nagelkerke R = 0.797). The LOS-model consisted of (1) TBSA and (2) serum albumin concentration (AUC = 0.832, Nagelkerke R = 0.408). In tests of discrimination and calibration, native models prepared for survival and LOS outperformed other models applicable to our dataset.
Data from a South Asian burn center has been used to explore factors influencing prognosis for their utility in predictive models for survival and the duration of hospital stay. The significant prognostic roles of TBSA, age, inhalational injury, burn-depth, etiology of burn, anatomic site of burn, hypoalbuminemia, and other biochemical parameters were observed. These tools hold significance in guiding healthcare policy and in communications with patients and their families.
本研究旨在探索能够预测热烧伤患者生存和住院时间（LOS）的候选参数，为这两个结局构建多变量预测模型，并比较本地模型与其他模型的性能。
本研究采用回顾性队列研究，基于病历回顾进行数据提取。数据来自于 2020 年 1 月 1 日至 10 月 31 日期间在巴基斯坦拉合尔的一家三级烧伤中心接受治疗的患者。在进行单变量预筛选后，我们为每个感兴趣的结局（生存和 LOS）构建了多变量逻辑回归模型。对多变量模型进行了测试并与其他模型进行了比较。
烧伤总面积（TBSA）的增加与生存降低和住院时间延长有关。年龄的增加和全层烧伤独立预测生存降低。烧伤病因具有预后价值：汽油火焰烧伤预测生存降低和 LOS 延长；烫伤与生存几率增加和 LOS 缩短有关。生存模型由（1）Baux 评分、（2）TBSA>40%和（3）血清白蛋白<3.5g/dL 组成（AUC=0.968，Nagelkerke R=0.797）。 LOS 模型由（1）TBSA 和（2）血清白蛋白浓度组成（AUC=0.832，Nagelkerke R=0.408）。在判别和校准测试中，为生存和 LOS 准备的本地模型优于适用于我们数据集的其他模型。
本研究利用南亚烧伤中心的数据，探索影响预后的因素，为预测生存和住院时间的模型提供依据。观察到 TBSA、年龄、吸入性损伤、烧伤深度、烧伤病因、烧伤部位、低白蛋白血症和其他生化参数的显著预后作用。这些工具对于指导医疗保健政策以及与患者及其家属沟通具有重要意义。
