Evidence map›Paper›PMID 25420613›Full record

Observational studyBMC infectious diseases2014

A prediction tool for nosocomial multi-drug Resistant Gram-Negative Bacilli infections in critically ill patients - prospective observational study.

Anupama Vasudevan, Amartya Mukhopadhyay, Jialiang Li, Eugene Goh Yu Yuen, Paul Ananth Tambyah

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC infectious diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

34 citing papers in PubMed, 68 citations in OpenAlex.

  1. Trial
  2. Development and Prospective Validation of a Machine Learning Tool for Predicting Multidrug-resistant Organism Infections in an Indian Critical Care Unit.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2026
    Article
  3. Article
  4. A Risk Prediction Model for MDRJournal of multidisciplinary healthcare · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. The Novel "RISC" Score as a Risk-prediction Model of Carbapenem-resistant Hospital-acquired Infections in Adult Sepsis Patients - A Prospective Observational Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Recommendations for antibiotic selection for severe nosocomial infections.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2021
    Article
  20. 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

5 authors at 2 institutions in 1 country.

Anupama Vasudevan
Amartya Mukhopadhyay
Jialiang Li
Eugene Goh Yu Yuen
Paul Ananth Tambyah
National University Health System · SGNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe widespread use of empiric broad spectrum antibiotics has contributed to the global increase of Resistant Gram-Negative Bacilli (RGNB) infections in intensive care units (ICU). The aim of this study was to develop a tool to predict nosocomial RGNB infections among ICU patients for targeted therapy.

methodsWe conducted a prospective observational study from August'07 to December'11. All adult patients who were admitted and stayed for more than 24 hours at the medical and surgical ICU's were included. All patients who developed nosocomial RGNB infections 48 hours after ICU admission were identified. A prediction score was formulated by using independent risk factors obtained from logistic regression analysis. This was prospectively validated with a subsequent cohort of patients admitted to the ICUs during the following time period of January-September 2012.

resultsSeventy-six patients with nosocomial RGNB Infection (31bacteremia) were compared with 1398 patients with Systemic Inflammatory Response Syndrome (SIRS) without any gram negative bacterial infection/colonization admitted to the ICUs during the study period. The following independent risk factors were obtained by a multivariable logistic regression analysis - prior isolation of Gram negative organism (coeff: 1.1, 95% CI 0.5-1.7); Surgery during current admission (coeff: 0.69, 95% CI 0.2-1.2); prior Dialysis with end stage renal disease (coeff: 0.7, 95% CI 0.1-1.1); prior use of Carbapenems (coeff: 1.3, 95% CI 0.3-2.3) and Stay in the ICU for more than 5 days (coeff: 2.4, 95% CI 1.6-3.2). It was validated prospectively in a subsequent cohort (n = 408) and the area-under-the-curve (AUC) of the GSDCS score for predicting nosocomial ICU acquired RGNB infection and bacteremia was 0.77 (95% CI 0.68-0.89 and 0.78 (95% CI 0.69-0.89) respectively. The GSDCS (0-4.3) score clearly differentiated the low (0-1.3), medium (1.4-2.3) and high (2.4-4.3) risk patients, both for RGNB infection (p:0.003) and bacteremia (p:0.009).

conclusionGSDCS is a simple bedside clinical score which predicts RGNB infection and bacteremia with high predictive value and differentiates low versus high risk patients. This score will help clinicians to choose appropriate, timely targeted antibiotic therapy and avoid exposure to unnecessary treatment for patients at low risk of nosocomial RGNB infection. This will reduce the selection pressure and help to contain antibiotic resistance in ICUs.

Indexed as

Intensive Care UnitsAcinetobacter baumanniiAcinetobacter InfectionsAdultAgedAnti-Bacterial AgentsBacteremiaCarbapenemsCohort StudiesCritical IllnessCross InfectionDecision Support TechniquesDrug Resistance, Multiple, BacterialEscherichia coliEscherichia coli InfectionsFemaleAnti-Bacterial AgentsCarbapenems

Identifiers

PMID25420613
PMCPMC4252002
OpenAlexW2067267279

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.