Internal Medicine, "Maggiore" Hospital, Bologna, Italy.
Department of Internal Medicine, Careggi Hospital, Florence, Italy.
PLoS One. 2019 Jul 24;14(7):e0219767. doi: 10.1371/journal.pone.0219767. eCollection 2019.
Recently we defined a user-friendly tool (FADOI-COMPLIMED scores-FCS) to assess complexity of patients hospitalized in medical wards. FCS-1 is an average between the Barthel Index and the Exton-Smith score, while FCS-2 is obtained by using the Charlson score. The aim of this paper is to assess the ability of the FCS to predict mortality in-hospital and after 1-3-6-12-months. In this perspective, we performed comparisons with the validated Multidimensional Prognostic Index (MPI).
It is a multicenter, prospective observational study, enrolling patients aged over 40, suffering from at least two chronic diseases and consecutively admitted to Internal Medicine departments. For each patient, data from 13 questionnaires were collected. Survival follow-up was conducted at 1-3-6-12 months after discharge. The relationships between cumulative incidences of death with FCS were investigated with logistic regression analyses. ROC curve analyses were performed in order to compare the predictiveness of the logistic models based on FCS with respect to those with MPI taken as reference.
A cohort of 541 patients was evaluated. A 10-point higher value for FCS-1 and FCS-2 leads to an increased risk of 1-year death equal to 25.0% and 27.1%, respectively. In case of in-hospital mortality, the relevant percentages were 63.1% and 15.3%. The logistic model based on FCS is significantly more predictive than the model based on MPI (which requires an almost doubled number of items) for all the time-points considered.
Assessment of prognosis of patients has the potential to guide clinical decision-making and lead to better care. We propose a new, efficient and easy-to-use instrument based on FCS, which demonstrated a good predictive power for mortality in patients hospitalized in medical wards. This tool may be of interest for clinical practice, since it well balances feasibility (requiring the compilation of 34 items, taking around 10 minutes) and performance.
最近，我们定义了一种用户友好的工具（FADOI-COMPLIMED 评分-FCS），用于评估住院患者的复杂性。FCS-1 是 Barthel 指数和 Exton-Smith 评分的平均值，而 FCS-2 则通过 Charlson 评分获得。本文旨在评估 FCS 预测住院和 1-3-6-12 个月后死亡率的能力。在这方面，我们与经过验证的多维预后指数（MPI）进行了比较。
这是一项多中心、前瞻性观察性研究，纳入年龄超过 40 岁、患有至少两种慢性病且连续入住内科病房的患者。为每位患者收集了 13 份问卷的数据。出院后 1-3-6-12 个月进行生存随访。使用逻辑回归分析研究了 FCS 与死亡率累积发生率之间的关系。为了比较基于 FCS 的逻辑模型与以 MPI 为参考的逻辑模型的预测能力，进行了 ROC 曲线分析。
评估了 541 例患者的队列。FCS-1 和 FCS-2 每增加 10 分，1 年死亡的风险分别增加 25.0%和 27.1%。在住院期间死亡的情况下，相关百分比分别为 63.1%和 15.3%。基于 FCS 的逻辑模型在所有考虑的时间点上都明显比基于 MPI 的模型（需要两倍以上的项目）更具预测性。
对患者预后的评估有可能指导临床决策，并提供更好的护理。我们提出了一种新的、高效且易于使用的基于 FCS 的工具，该工具在预测住院患者的死亡率方面表现出良好的预测能力。该工具可能对临床实践感兴趣，因为它在可行性（需要编制 34 项内容，大约需要 10 分钟）和性能之间取得了很好的平衡。
