Cano-Escalera Guillermo, Graña Manuel, Irazusta Jon, Labayen Idoia, Gonzalez-Pinto Ana, Besga Ariadna
Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018 Donostia-San Sebastian, Spain.
Computational Intelligence Group, University of the Basque Country (UPV/EHU), 20018 Donostia-San Sebastian, Spain.
J Clin Med. 2023 Apr 24;12(9):3103. doi: 10.3390/jcm12093103.
Frailty is characterized by a progressive decline in the physiological functions of multiple body systems that lead to a more vulnerable condition, which is prone to the development of various adverse events, such as falls, hospitalization, and mortality. This study aims to determine whether frailty increases mortality compared to pre-frailty and to identify variables associated with a higher risk of mortality.
Two cohorts, frail and pre-frail subjects, are evaluated according to the Fried phenotype. A complete examination of frailty, cognitive status, comorbidities and pharmacology was carried out at hospital admission and was extracted through electronic health record (EHR). Mortality was evaluated from the EHR.
Kaplan-Meier estimates of survival probability functions were calculated at two years censoring time for frail and pre-frail cohorts. The log-rank test assessed significant differences between survival probability functions. Significant variables for frailty ( < 0-05) were extracted by independent sample -test. Further selection was based on variable significance found in multivariate logistic regression discrimination between frail and pre-frail subjects. Cox regression over univariate -test-selected variables was calculated to identify variables associated with higher proportional hazard risks (HR) at two years.
Frailty is associated with greater mortality at two years censoring time than pre-frailty (log-rank test, < 0.0001). Variables with significant ( < 0.05) association with mortality identified in both cohorts (HR 95% (CI in the frail cohort) are male sex (0.44 (0.29-0.66)), age (1.05 (1.01-1.09)), weight (0.98 (0.96-1.00)), and use of proton-pump inhibitors (PPIs) (0.60 (0.41-0.87)). Specific high-risk factors in the frail cohort are readmission at 30 days (0.50 (0.33-0.74)), SPPB sit and stand (0.62 (0.45-0.85)), heart failure (0.67 (0.46-0.98)), use of antiplatelets (1.80 (1.19-2.71)), and quetiapine (0.31 (0.12-0.81)). Specific high-risk factors in the pre-frail cohort are Barthel's score (120 (7.7-1700)), Pfeiffer test (8.4; (2.3-31)), Mini Nutritional Assessment (MNA) (1200 (18-88,000)), constipation (0.025 (0.0027-0.24)), falls (18,000 (150-2,200,000)), deep venous thrombosis (8400 (19-3,700,000)), cerebrovascular disease (0.01 (0.00064-0.16)), diabetes (360 (3.4-39,000)), thyroid disease (0.00099 (0.000012-0.085)), and the use of PPIs (0.062 (0.0072-0.54)), Zolpidem (0.000014 (0.0000000021-0.092)), antidiabetics (0.00015 (0.00000042-0.051)), diuretics (0.0003 (0.000004-0.022)), and opiates (0.000069 (0.00000035-0.013)).
Frailty is associated with higher mortality at two years than pre-frailty. Frailty is recognized as a systemic syndrome with many links to older-age comorbidities, which are also found in our study. Polypharmacy is strongly associated with frailty, and several commonly prescribed drugs are strongly associated with increased mortality. It must be considered that frail patients need coordinated attention where the diverse specialist taking care of them jointly examines the interactions between the diversity of treatments prescribed.
衰弱的特征是多个身体系统的生理功能逐渐衰退,导致身体更易受伤害,容易发生各种不良事件,如跌倒、住院和死亡。本研究旨在确定与衰弱前期相比,衰弱是否会增加死亡率,并确定与较高死亡风险相关的变量。
根据弗里德表型对两个队列,即衰弱和衰弱前期受试者进行评估。在入院时对衰弱、认知状态、合并症和用药情况进行全面检查,并通过电子健康记录(EHR)提取相关信息。从EHR中评估死亡率。
计算衰弱和衰弱前期队列在两年 censoring 时间的 Kaplan-Meier 生存概率函数估计值。对数秩检验评估生存概率函数之间的显著差异。通过独立样本检验提取衰弱的显著变量(<0.05)。进一步的选择基于在衰弱和衰弱前期受试者之间的多变量逻辑回归判别中发现的变量显著性。对单变量检验选择的变量进行 Cox 回归计算,以确定与两年时较高比例风险(HR)相关的变量。
在两年 censoring 时间,衰弱比衰弱前期与更高的死亡率相关(对数秩检验,<0.0001)。在两个队列中确定的与死亡率有显著(<0.05)关联的变量(HR 95%(衰弱队列中的置信区间))为男性(0.44(0.29 - 0.66))、年龄(1.05(1.01 - 1.09))、体重(0.98(0.96 - 1.00))和使用质子泵抑制剂(PPIs)(0.60(0.41 - 0.87))。衰弱队列中的特定高危因素为 30 天再入院(0.50(0.33 - 0.74))、简短体能状况量表(SPPB)坐立测试(0.62(0.45 - 0.85))、心力衰竭(0.67(0.46 - 0.98))、使用抗血小板药物(1.80(1.19 - 2.71))和喹硫平(0.31(0.12 - 0.81))。衰弱前期队列中的特定高危因素为巴氏指数(120(7.7 - 1700))、 Pfeiffer 测试(8.4;(2.3 - 31))、微型营养评定量表(MNA)(1200(18 - 88,000))、便秘(0.025(0.0027 - 0.24))、跌倒(18,000(150 - 2,200,000))、深静脉血栓形成(8400(19 - 3,700,0,00))、脑血管疾病(0.01(0.00064 - 0.16))、糖尿病(360(3.4 - 39,000))、甲状腺疾病(0.00099(0.000012 - 0.085))以及使用 PPIs(0.062(0.0072 - 0.54))、唑吡坦(0.000014(0.0000000021 - 0.092))、抗糖尿病药物(0.00015(0.00000042 - 0.051))、利尿剂(0.0003(0.000004 - 0.022))和阿片类药物(0.000069(0.00000035 - 0.013))。
与衰弱前期相比衰弱在两年时与更高的死亡率相关。衰弱被认为是一种与老年合并症有许多关联的全身性综合征,这在我们的研究中也有发现。多重用药与衰弱密切相关,几种常用药物与死亡率增加密切相关。必须考虑到衰弱患者需要协调关注,由不同的专科医生共同检查所开多种治疗之间的相互作用。