Evidence map›Paper›PMID 38495463›Full record

ArticleJournal of clinical and experimental hepatology

Comparison of a Novel Score "NOD-ACLF" to Other Established Prognostic Scores for Prediction of Mortality in APASL-ACLF Patients: A Cohort Study from a Tertiary Care Center of North India.

Ajay K Patwa, Khushboo Yadav, Virendra Atam, Kauser Usman, Satyendra K Sonkar, Shyam C Chaudhary, Vivek Kumar, Kamal K Sawlani, Kamlesh K Gupta, Munna L Patel and 10 more

Open access · greenAbstract read
In one paragraph

Article in Journal of clinical and experimental hepatology. 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
1.5field-weighted citation impact, top 20% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

20 authors at 2 institutions in 1 country.

Ajay K PatwaGastroenterology and Hepatology Unit, Department of Medicine, King George's Medical University, Lucknow, India.
Khushboo YadavDepartment of Medicine, King George's Medical University, Lucknow, India.
Virendra AtamDepartment of Medicine, King George's Medical University, Lucknow, India.
Kauser UsmanDepartment of Medicine, King George's Medical University, Lucknow, India.
Satyendra K SonkarDepartment of Medicine, King George's Medical University, Lucknow, India.
Shyam C ChaudharyDepartment of Medicine, King George's Medical University, Lucknow, India.
Vivek KumarDepartment of Medicine, King George's Medical University, Lucknow, India.
Kamal K SawlaniDepartment of Medicine, King George's Medical University, Lucknow, India.
Kamlesh K GuptaDepartment of Medicine, King George's Medical University, Lucknow, India.
Munna L PatelDepartment of Medicine, King George's Medical University, Lucknow, India.
Dandu H ReddyDepartment of Medicine, King George's Medical University, Lucknow, India.
Harish GuptaDepartment of Medicine, King George's Medical University, Lucknow, India.
Medhavi GautamDepartment of Medicine, King George's Medical University, Lucknow, India.
Satish KumarDepartment of Medicine, King George's Medical University, Lucknow, India.
Amit KumarDepartment of Medicine, King George's Medical University, Lucknow, India.
Ambuj YadavDepartment of Medicine, King George's Medical University, Lucknow, India.
Deepak BhagchandaniDepartment of Medicine, King George's Medical University, Lucknow, India.
Mahak LambaDepartment of Medicine, King George's Medical University, Lucknow, India.
Abhishek SinghDepartment of Community Medicine and Public Health, King George's Medical University, Lucknow, India.
Ajay K MishraDepartment of Hepatology, SGPGIMS, Lucknow, India.
King George's Medical University · INSanjay Gandhi Post Graduate Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Commonly used prognostic scores for acute on-chronic liver failure (ACLF) have complex calculations. We tried to compare the simple counting of numbers and types of organ dysfunction to these scores, to predict mortality in ACLF patients. Methods: In this prospective cohort study, ACLF patients diagnosed on the basis of Asia Pacific Association for Study of the Liver (APASL) definition were included. Severity scores were calculated. Prognostic factors for outcome were analysed. A new score, the Number of Organ Dysfunctions in Acute-on-Chronic Liver Failure (NOD-ACLF) score was developed. Results: Among 80 ACLF patients, 74 (92.5%) were male, and 6 were female (7.5%). The mean age was 41.0±10.7 (18-70) years. Profile of acute insult was; alcohol 48 (60%), sepsis 30 (37.5%), variceal bleeding 22 (27.5%), viral 8 (10%), and drug-induced 3 (3.8%). Profiles of chronic insults were alcohol 61 (76.3%), viral 20 (25%), autoimmune 3 (3.8%), and non-alcoholic steatohepatitis 2 (2.5%). Thirty-eight (47.5%) were discharged, and 42 (52.5%) expired. The mean number of organ dysfunction (NOD-ACLF score) was ->4.5, simple organ failure count (SOFC) score was >2.5, APASL ACLF Research Consortium score was >11.5, Model for End-Stage Liver Disease-Lactate (MELD-LA) score was >21.5, and presence of cardiovascular and respiratory dysfunctions were significantly associated with mortality. NOD-ACLF and SOFC scores had the highest area under the receiver operating characteristic to predict mortality among all these. Conclusion: The NOD-ACLF score is easy to calculate bedside and is a good predictor of mortality in ACLF patients performing similar or better to other scores.

Indexed as

cirrhosisliver failureorgan failureprognosisseverity assessment

Identifiers

PMID38495463
PMCPMC10940987
OpenAlexW4392125300

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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.