Evidence map›Paper›PMID 40554363›Full record

ArticleThe journal of nutrition, health & aging2025

Hospital frailty risk score in predicting outcomes after simultaneous colon and liver resection for colorectal cancer liver metastasis in older adults: Evidence from the Nationwide Inpatient Sample 2015-2018.

Haohao Huang, Weidong Jin, Huiling Sun, Bo Diao, Ping Wang, Jiankun Jia, Dandan Ma, Yi Zhang

Abstract read
In one paragraph

Article in The journal of nutrition, health & aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Haohao HuangDepartment of Neurosurgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China; General Hospital Of Central Theater Command and Hubei Key Laboratory of Central Nervous System Tumor and Intervention, Wuhan, Hubei 430070, China; Wuhan University of Science and Technology, Wuhan, Hubei, China.
Weidong JinDepartment of General Surgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China.
Huiling SunDepartment of General Surgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China.
Bo DiaoGeneral Hospital Of Central Theater Command and Hubei Key Laboratory of Central Nervous System Tumor and Intervention, Wuhan, Hubei 430070, China.
Ping WangDepartment of General Surgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China.
Jiankun JiaDepartment of General Surgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China.
Dandan MaDepartment of General Surgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China.
Yi ZhangDepartment of General Surgery, General Hospital of Central Theater Command of PLA, Wuhan 430071, Hubei, China; General Hospital Of Central Theater Command and Hubei Key Laboratory of Central Nervous System Tumor and Intervention, Wuhan, Hubei 430070, China; Wuhan University of Science and Technology, Wuhan, Hubei, China. Electronic address: zhangyihero@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigated the impact of clinical frailty on short-term outcomes of simultaneous colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) resections. SETTING AND

participantsData of older patients ≥ 60 years old undergoing simultaneous CRC/CRLM resections between 2005 and 2018 were identified in the United States (US) Nationwide Inpatient Sample (NIS) database.

methodsFrailty was determined using the Hospital Frailty Risk Score (HFRS) according to the International Classification of Diseases Ninth and Tenth (ICD-9 and ICD-10) codes. Study outcomes included mortality, prolonged hospital stay (LOS), non-routine discharge, and complications.

resultsData of 4514 patients were analyzed. Frailty was significantly associated with increased risks of in-hospital mortality (adjusted odds ratio [aOR] = 3.65, 95% confidence interval [CI]: 2.52, 5.28), non-routine discharge (aOR = 2.44, 95% CI: 2.08, 2.87), prolonged LOS (aOR = 3.07, 95% CI: 2.60, 3.61), overall complications (aOR = 3.47, 95% CI: 3.03, 3.97), sepsis (aOR = 13.73, 95% CI: 9.76, 19.31), respiratory failure (aOR = 4.99, 95% CI: 3.80, 6.57), acute kidney injury (AKI) (aOR = 6.42, 95% CI: 4.83, 8.52), and acute liver failure (aOR = 2.10, 95% CI: 1.38, 3.21), as well as 32.69 thousand USD higher total hospital costs (95% CI: 28.41, 36.97) than no frailty. Incorporating frailty with traditional demographic and clinical risk factors improved in-hospital mortality prediction (area under ROC curve [AUC]: 0.765 to 0.799).

conclusionsIn older patients aged ≥ 60 years undergoing simultaneous CRC and CRLM resection, HFRS-defined frailty is a significant predictor of adverse in-hospital outcomes. The addition of HFRS-defined frailty to demographic and clinical variables in predictive models improved the AUC for mortality prediction. Incorporating frailty assessment into the preoperative risk stratification and decision-making process for these patients may support surgeons in delivering more personalized and effective care.

Indexed as

Colorectal NeoplasmsFrailtyHepatectomyLiver NeoplasmsAgedAged, 80 and overFemaleHospital MortalityHumansInpatientsLength of StayMaleMiddle AgedPostoperative ComplicationsRisk AssessmentRisk FactorsColorectal cancer (CRC)Colorectal cancer liver metastasis (CRLM)FrailtyHospital Frailty Risk Score (HFRS)Simultaneous resection

Identifiers

PMID40554363
PMCPMC12402386

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.