Evidence map›Paper›PMID 30617709›Full record

ArticleWiener klinische Wochenschrift2019

Hypoalbuminemia as predictor of recurrence of Clostridium difficile infection.

Daniela Knafl, Matthias G Vossen, Christian Gerges, Elisabeth Lobmeyr, Mario Karolyi, Ludwig Wagner, Florian Thalhammer

Open access · hybridAbstract read
In one paragraph

Article in Wiener klinische Wochenschrift, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. International journal of molecular sciences · 2023
    Review
  4. Clinical Determinants PredictingAntibiotics (Basel, Switzerland) · 2022
    Article
  5. Article
  6. Hypoalbuminemia as Surrogate and Culprit of Infections.International journal of molecular sciences · 2021
    Review
  7. Article
  8. Risk Factors Associated with RecurrentHealthcare (Basel, Switzerland) · 2020
    Article
  9. Review
  10. Article
  11. Observational
  12. Updates in Treatment of RecurrentJournal of clinical medicine research · 2019
    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

7 authors at 2 institutions in 1 country.

Daniela KnaflDivision of Nephrology and Dialysis, Department of Medicine III, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria. daniela.knafl@meduniwien.ac.at.ORCID http://orcid.org/0000-0001-6810-615X
Matthias G VossenDivision of Infectious Diseases and Tropical Medicine, Department of Medicine I, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Christian GergesDivision of Cardiology, Department of Medicine II, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Elisabeth LobmeyrDepartment of Emergency Medicine, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Mario Karolyi4th Medical Department of Infectious Diseases and Tropical Medicine, Kaiser-Franz-Josef Hospital, Kundratstraße 3, 1100, Vienna, Austria.
Ludwig WagnerDivision of Nephrology and Dialysis, Department of Medicine III, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Florian ThalhammerDivision of Infectious Diseases and Tropical Medicine, Department of Medicine I, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Medical University of Vienna · ATKaiser-Franz-Josef-Spital · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNovel drugs for Clostridium difficile (C. difficile) infections have been proven to reduce recurrent infections. Because of their high financial costs, identification of patients at high risk for recurrence is essential to provide optimal treatment. The ATLAS score's ability to predict 90-day recurrence, disease complications and 1‑year all-cause mortality was evaluated.

methods144 consecutive symptomatic patients with positive stool test for C. difficile were enrolled. The ATLAS score (consisting of the variables age, temperature, leukocyte count, albumin, systemic antibiotics, serum creatinine) was calculated and patients were stratified into 4 subgroups according to their scores. A Cox regression model was used to estimate the extent to which ATLAS was associated with 90-day recurrence. Furthermore, the score was correlated with disease complications and one-year all-cause mortality.

resultsATLAS was unable to predict 90-day recurrence (p = 0.064, HR 1.134 [0.993;1.295]), but performed well for disease complications (D = 0.382, p < 0.001, HR 1.547 [1.266;1.889]) and mortality (p < 0.001, HR 1.374 [1.194;1.583]). Serum albumin was the only parameter able to predict 90-day recurrence (p = 0.016, HR 0.958 [0.926;0.992]) and was also a predictor of disease complications (p < 0.001, HR 0.865[0.809;0.924]) and one-year all-cause mortality (p < 0.001, HR 0.923 [0.896;0.950]). A threshold of 33.1g/L (sensitivity = 56%, specificity = 80%, AUC 0.683) and 29.2g/L (sensitivity = 75%, specificity = 70%, AUC 0.763) of serum albumin could be identified to be predictive for 90-day recurrence and one-year all-cause mortality, respectively.

conclusionsSerum albumin and ATLAS are predictors of disease complications and mortality, while only serum albumin is significantly associated with 90-day disease recurrence.

Indexed as

Clostridioides difficileClostridium InfectionsHypoalbuminemiaAgedAged, 80 and overComorbidityFemaleHumansMaleMiddle AgedRecurrenceAntibiotic associated diarrhoeaATLASClostridium difficileMortalityRecurrenceSerum albumin

Identifiers

PMID30617709
PMCPMC6394683
OpenAlexW2908766989

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.