Evidence map›Paper›PMID 26860903›Full record

ArticleBMC gastroenterology2016

Mortality Risk for Acute Cholangitis (MAC): a risk prediction model for in-hospital mortality in patients with acute cholangitis.

Jochen Schneider, Alexander Hapfelmeier, Sieglinde Thöres, Andreas Obermeier, Christoph Schulz, Dominik Pförringer, Simon Nennstiel, Christoph Spinner, Roland M Schmid, Hana Algül and 2 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC gastroenterology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

25 citing papers in PubMed, 57 citations in OpenAlex.

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  7. Morbidity and mortality in patients with stage IV pancreatic adenocarcinoma and acute cholangitis: Outcomes and risk prognostication.Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2024
    Observational
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  15. Review
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  18. Specificities of acute cholangitis in patients with cancer: a retrospective comparative study of 130 episodes.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2022
    Article
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  20. Review
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

12 authors at 2 institutions in 1 country.

Jochen SchneiderII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. jochen.schneider@tum.de.
Alexander HapfelmeierInstitute of Medical Statistics and Epidemiology, Technische Universität München, München, Germany. alexander.hapfelmeier@tum.de.
Sieglinde ThöresII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. sieglinde.thoeres@tum.de.
Andreas ObermeierKlinik für Orthopädie, Labor für Infektionsforschung, Klinikum rechts der Isar, Technische Universität München, München, Germany. andreas.obermeier@tum.de.
Christoph SchulzInstitut für klinische Chemie und Pathobiochemie, Klinikum rechts der Isar, Technische Universität München, München, Germany. christoph.schulz@tum.de.
Dominik PförringerI. Chirurgische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. dominik.pfoerringer@tum.de.
Simon NennstielII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. simon.nennstiel@tum.de.
Christoph SpinnerII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. christoph.spinner@tum.de.
Roland M SchmidII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. roland.schmid@tum.de.
Hana AlgülII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. hana.alguel@tum.de.
Wolfgang HuberII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. wolfgang.huber@tum.de.
Andreas WeberII. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Germany. andreas.weber@mri.tum.de.
Technical University of Munich · DEKlinikum rechts der Isar · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute cholangitis is a life-threatening bacterial infection of the biliary tract. Main focus of this study was to create a useful risk prediction model that helps physicians to assign patients with acute cholangitis into different management groups.

methods981 cholangitis episodes from 810 patients were analysed retrospectively at a German tertiary center.

resultsOut of eleven investigated statistical models fit to 22 predictors, the Random Forest model achieved the best (cross-)validated performance to predict mortality. The receiver operating characteristics (ROC) curve revealed a mean area under the curve (AUC) of 91.5 %. Dependent on the calculated mortality risk, we propose to stratify patients with acute cholangitis into a high and low risk group. The mean sensitivity, specificity, positive and negative predictive value of the corresponding optimal cutpoint were 82.9 %, 85.1 %, 19.0 % and 99.3 %, respectively. All of these results emerge from nested (cross-)validation and are supposed to reflect the model's performance expected for external data. An implementation of our risk prediction model including the specific treatment recommendations adopted from the Tokyo guidelines is available on http://www2.imse.med.tum.de:3838/ .

conclusionOur risk prediction model for mortality appears promising to stratify patients with acute cholangitis into different management groups. Additional validation of its performance should be provided by further prospective trails.

Indexed as

Hospital MortalityModels, StatisticalAcute DiseaseAdultAgedAged, 80 and overAge FactorsArea Under CurveCholangitisFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk Assessment

Identifiers

PMID26860903
PMCPMC4746925
OpenAlexW2272518351

What OpenQuestion holds

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LicenceCC BY
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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.