Hospital frailty risk score is superior to legacy comorbidity indices for risk adjustment of in-hospital cirrhosis cases.
Hospital frailty risk score is superior to legacy comorbidity indices for risk adjustment of in-hospital cirrhosis cases.
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DOI：
10.1016/j.jhepr.2023.100955
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发表时间：
2024-01
期刊：
影响因子：
8.3
通讯作者：
Orman, Eric S.
中科院分区：
文献类型：
--
作者：
Desai, Archita P.;Parvataneni, Swetha;Knapp, Shannon M.;Nephew, Lauren D.;Chalasani, Naga;Ghabril, Marwan S.;Orman, Eric S.
医院虚弱风险评分（HFRS）识别老年患者预后不良的风险，并可能对肝硬化有价值。我们比较了Charlson（CCI）、Elixhauser（ECI）和肝硬化（CirCom）合并症指数与HFRS在预测肝硬化住院结局方面的差异。使用全国住院患者样本（2015-2019年第4季度），我们分析了肝硬化住院情况。对于每个指标，我们描述了共病的患病率和住院死亡率。我们比较了CCI、ECI、CirCom和HFRS预测住院死亡率的能力。使用受试者工作特征曲线下面积和赤池信息标准比较预测住院死亡率的原始模型和调整模型。该队列（N = 626，553）的中位年龄为61岁（IQR 52-68岁），60%为男性，43%的肝硬化由酒精引起，38%有腹水。中位合并症评分如下：ECI 4（IQR 3-6）、CCI 5（IQR 4-8）和HFRS 5.6（IQR 3.0-8.6）。最常见的CirCom评分为0 + 0（44%）。在每个指数的值范围内，我们观察到不同的死亡率范围：CCI 1.9- 13.1%，ECI 3.2- 8.7%，CirCom 4.9- 13.8%，HFRS 1.0- 15.2%。HFRS校正模型在预测死亡率方面具有最高的受试者工作特征曲线下面积（HFRS 0.782 vs. ECI 0.689，CCI 0.695和CirCom 0.692）。我们观察到在CCI、ECI和CirCom的每个水平内，HFRS死亡率的实质性变化。例如，对于ECI 4，随着HFRS从0增加到15，死亡率从0.6%增加到16.4%。合并症指数预测住院肝硬化死亡率，但HFRS表现优于CCI，ECI和CirCom。HFRS是一个理想的工具，用于测量并发症负担和疾病严重程度的风险调整，在管理数据库研究。我们比较了常用的合并症指数，最近描述的风险评分（医院虚弱风险评分[HFRS]）在肝硬化患者使用的国家样本的医院记录。合并症在肝硬化住院患者中很常见。在每个指数的范围内，死亡率有很大的差异。HFRS在预测住院死亡率方面优于Charlson合并症指数、Elixhauser合并症指数和CirCom（HFRS特异性合并症评分系统）。HFRS是住院管理数据库研究中风险调整的有价值指标。我们使用超过60万份肝硬化患者的出院记录，评估了风险调整工具的性能。HFRS和传统风险调整工具发现了高合并症发生率，并与住院死亡率相关。HFRS测量了多种共病情况，并证明与其他工具相比，显著改善了住院死亡率的预测。在ECI、CCI和CirCom的每个水平内，我们注意到可以通过HFRS识别的死亡率的显著变化。
The hospital frailty risk score (HFRS) identifies older patients at risk of poor outcomes and may have value in cirrhosis. We compared the Charlson (CCI), Elixhauser (ECI), and cirrhosis (CirCom) comorbidity indices with the HFRS in predicting outcomes for cirrhosis hospitalisations. Using the National Inpatient Sample (quarter 4 of 2015–2019), we analysed cirrhosis hospitalisations. For each index, we described the prevalence of comorbid conditions and inpatient mortality. We compared the ability of CCI, ECI, CirCom, and HFRS to predict inpatient mortality. Raw and adjusted models predicting inpatient mortality were compared using the area under the receiver operating characteristic curve and the Akaike information criterion. The cohort’s (N = 626,553) median age was 61 years (IQR 52–68 years), 60% were male, cirrhosis was caused by alcohol in 43%, and 38% had ascites. The median comorbidity scores are as follows: ECI 4 (IQR 3–6), CCI 5 (IQR 4–8), and HFRS 5.6 (IQR 3.0–8.6). The most common CirCom score was 0 + 0 (44%). Across the range of values of each index, we observed different mortality ranges: CCI 1.9–13.1%, ECI 3.2–8.7%, CirCom 4.9–13.8%, and HFRS 1.0–15.2%. An adjusted model with HFRS had the highest area under the receiver operating characteristic curve in predicting mortality (HFRS 0.782 vs. ECI 0.689, CCI 0.695, and CirCom 0.692). We observed substantial variation in mortality with HFRS within each level of CCI, ECI, and CirCom. For example, for ECI 4, mortality increased from 0.6 to 16.4%, as HFRS increased from 0 to 15. Comorbidity indices predict inpatient cirrhosis mortality, but HFRS performs better than CCI, ECI, and CirCom. HFRS is an ideal tool for measuring comorbidity burden and disease severity risk adjustment in cirrhosis-related administrative database studies. We compared commonly used comorbidity indices to a more recently described risk score (hospital frailty risk score [HFRS]) in patients with cirrhosis using a national sample of hospital records. Comorbid conditions are common in hospitalised patients with cirrhosis. There is significant variability in mortality across the range of each index. HFRS outperforms the Charlson comorbidity index, Elixhauser comorbidity index, and CirCom (cirrhosis-specific comorbidity scoring system) in predicting inpatient mortality. HFRS is a valuable index for risk adjustment in inpatient administrative database studies. Using over 600,000 hospital discharge records of cirrhosis, we assessed the performance of risk adjustment tools. HFRS and legacy risk adjustment tools capture high rates of comorbidities and are associated with inpatient mortality. HFRS measures a larger variety of comorbid conditions and demonstrated significantly improved prediction of inpatient mortality vs. other tools. Within each level of the ECI, CCI, and CirCom, we noted significant variations in mortality that could be identified by the HFRS.
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DOI：
10.1002/hep.31726
发表时间：
2021-07
期刊：
Hepatology (Baltimore, Md.)
影响因子：
--
作者：
Hagström H;Adams LA;Allen AM;Byrne CD;Chang Y;Grønbaek H;Ismail M;Jepsen P;Kanwal F;Kramer J;Lazarus JV;Long MT;Loomba R;Newsome PN;Rowe IA;Ryu S;Schattenberg JM;Serper M;Sheron N;Simon TG;Tapper EB;Wild S;Wong VW;Yilmaz Y;Zelber-Sagi S;Åberg F
通讯作者：
Åberg F
DOI：
10.1002/lt.26473
发表时间：
2022-09
期刊：
Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society
影响因子：
--
作者：
通讯作者：
--
影响因子：
7.2
作者：
DEYO, RA;CHERKIN, DC;CIOL, MA
通讯作者：
CIOL, MA
影响因子：
3.6
作者：
Desai，Archita P.;Gandhi，Devika;Orman，Eric S.
通讯作者：
Orman，Eric S.
DOI：
10.1093/gerona/glx229
发表时间：
2018-07-01
影响因子：
5.1
作者：
Kim, Dae Hyun;Schneeweiss, Sebastian;Avorn, Jerry
通讯作者：
Avorn, Jerry