Evidence map›Paper›PMID 36626326›Full record

ArticleAge and ageing2023

A novel prognostic nomogram for older patients with acute-on-chronic liver diseases (AoCLD): a nationwide, multicentre, prospective cohort study.

Ju Zou, Hai Li, Guohong Deng, Xianbo Wang, Xin Zheng, Jinjun Chen, Zhongji Meng, Yubao Zheng, Yanhang Gao, Zhiping Qian and 6 more

Open access · hybridAbstract readMulticenter Study
In one paragraph

Article in Age and ageing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

16 authors at 15 institutions in 1 country.

Ju ZouDepartment of Infectious Diseases, Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, China.
Hai LiDepartment of Gastroenterology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China.
Guohong DengChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Xianbo WangChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Xin ZhengChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Jinjun ChenChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Zhongji MengChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Yubao ZhengChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Yanhang GaoChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Zhiping QianChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Feng LiuChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Xiaobo LuChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Yu ShiChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Jia ShangChinese Chronic Liver Failure (CLIF) Consortium, Shanghai, China.
Yan HuangDepartment of Infectious Diseases, Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, China.
Ruochan ChenDepartment of Infectious Diseases, Hunan Key Laboratory of Viral Hepatitis, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNArmy Medical University · CNBeijing Ditan Hospital · CNFirst Affiliated Hospital of Xinjiang Medical University · CNHenan Provincial People's Hospital · CNHubei University of Medicine · CNJilin University · CNRenji Hospital · CNSecond Hospital of Shandong University · CNShanghai Public Health Clinical Center · CNSouthern Medical University · CNSun Yat-sen University · CNUnion Hospital · CNXiangya Hospital Central South University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundthe incidence of acute-on-chronic liver disease (AoCLD) is increasing.

objectiveto investigate the clinical features and risk factors of AoCLD and construct an effective prognostic nomogram model for older patients with AoCLD.

methodsdata from 3,970 patients included in the CATCH-LIFE study were used, including 2,600 and 1,370 patients in the training and validation sets, respectively. Multivariate Cox regression analyses were performed to identify predictive risk factors in older individuals, and an easy-to-use nomogram was established. Performance was assessed using area under the curve, calibration plots and decision curve analysis (DCA).

resultsof the 3,949 patients with AoCLD, 809 were older with a higher proportion of autoimmune-related abnormalities, hepatitis C viral infection and schistosomiasis. In the older patient group, the incidence of cirrhosis, hepatic encephalopathy (HE), infection, ascites and gastrointestinal bleeding; neutrophil-to-lymphocyte ratio (NLR), aspartate-to-alanine transaminase ratio (AST/ALT), creatinine and blood urea nitrogen levels were higher, whereas incidence of acute-on-chronic liver failure, white blood cell, platelet and haemoglobin levels; albumin, total bilirubin (TB), AST and ALT levels; international normalised ratio (INR), estimated glomerular filtration rate and blood potassium levels were lower than in the younger group. The final nomogram was developed based on the multivariate Cox analysis in training cohort using six risk factors: ascites, HE grades, NLR, TB, INR and AST/ALT. Liver transplantation-free mortality predictions were comparable between the training and validation sets. DCA showed higher net benefit for the nomograph than the treat-all or treat-none strategies, with wider threshold probabilities ranges.

conclusionsour analysis will assist clinical predictions and prognoses in older patients with AoCLD.

Indexed as

AscitesNomogramsAgedHumansLiver CirrhosisPrognosisProspective Studiesnomogramolder peopleprognosisrisk factors

Identifiers

PMID36626326
PMCPMC9831261
OpenAlexW4314447474

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LicenceCC BY-NC-ND
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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.