Evidence map›Paper›PMID 38192536›Full record

ArticleJHEP reports : innovation in hepatology2024

Hospital frailty risk score is superior to legacy comorbidity indices for risk adjustment of in-hospital cirrhosis cases.

Archita P Desai, Swetha Parvataneni, Shannon M Knapp, Lauren D Nephew, Naga Chalasani, Marwan S Ghabril, Eric S Orman

Open access · goldAbstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. High Hospitalization Rates and Risk Factors Among Frail Patients With Cirrhosis: A 10-year Population-based Cohort Study.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Archita P DesaiDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Swetha ParvataneniDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Shannon M KnappDivision of Cardiovascular Medicine, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Lauren D NephewDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Naga ChalasaniDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Marwan S GhabrilDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Eric S OrmanDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Indiana University School of MedicineIndiana University Health · US

Funding

The Intersection of Personalized Medicine and Implementation Science to Improve Healthcare Utilization in CirrhosisK23DK123408 · NIDDK · INDIANA UNIVERSITY INDIANAPOLIS · PI DESAI, ARCHITA P. · 2020 to 2024
$903k
NIDDK NIH HHS K23 DK123408NIDDK NIH HHS L30 DK122508
6 · The paper itself

Abstract

Background & Aims: 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. Methods: 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. Results: 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 Conclusions: 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. Impact and Implications: 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.

Indexed as

CirrhosisComorbidityFrailtyRisk adjustment

Identifiers

PMID38192536
PMCPMC10772247
OpenAlexW4388304452

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.