Observational studyBMC infectious diseases2014
A prediction tool for nosocomial multi-drug Resistant Gram-Negative Bacilli infections in critically ill patients - prospective observational study.
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.
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.
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.
Who cites it
34 citing papers in PubMed, 68 citations in OpenAlex.
- The Use of Step-Down Oral Antibiotic Therapy for Uncomplicated Gram-Negative Bacteremia and Risk Factors for Adverse Outcomes.Open forum infectious diseases · 2026Trial
- 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 · 2026Article
- Comparative evaluation of tigecycline susceptibility testing methods for carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii.Annals of clinical microbiology and antimicrobials · 2026Article
- A Risk Prediction Model for MDRJournal of multidisciplinary healthcare · 2026Article
- Epidemiology and risk factors of multidrug-resistant Gram-negative bacilli in healthcare-associated infections: development of an exploratory risk assessment model in a Moroccan regional hospital.BMC infectious diseases · 2025Article
- Machine Learning Models to Establish the Risk of Being a Carrier of Multidrug-Resistant Bacteria upon Admission to the ICU.Antibiotics (Basel, Switzerland) · 2025Article
- Predicting infections with multidrug-resistant organisms (MDROs) in neurocritical care patients with hospital-acquired pneumonia (HAP): development of a novel multivariate prediction model.Microbiology spectrum · 2025Article
- 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 · 2025Article
- Performance of Risk Models for Antimicrobial Resistance in Adult Patients With Sepsis.JAMA network open · 2024Article
- Incidence of Carbapenem-Resistant Gram-Negative Bacterial Infections in Critically Ill Patients with COVID-19 as Compared to Non-COVID-19 Patients: A Prospective Case-Control Study.Critical care research and practice · 2024Article
- A deep learning model for predicting multidrug-resistant organism infection in critically ill patients.Journal of intensive care · 2023Article
- Drug-resistant bacteria in the critically ill: patterns and mechanisms of resistance and potential remedies.Frontiers in antibiotics · 2023Review
- Tracking Epidemiological Characteristics and Risk Factors of Multi-Drug Resistant Bacteria in Intensive Care Units.Infection and drug resistance · 2023Article
- Establishment of a risk prediction model for multidrug-resistant bacteria in deceased organ donors: a retrospective cohort study in China.Frontiers in cellular and infection microbiology · 2023Article
- Quantifying Gram-Negative Resistance to Empiric Treatment After Repeat ExpoSure To AntimicRobial Therapy (RESTART).Open forum infectious diseases · 2022Article
- Prediction of Intracranial Infection in Patients under External Ventricular Drainage and Neurological Intensive Care: A Multicenter Retrospective Cohort Study.Journal of clinical medicine · 2022Article
- Bloodstream Infections Caused by Carbapenem-Resistant Pathogens in Intensive Care Units: Risk Factors Analysis and Proposal of a Prognostic Score.Pathogens (Basel, Switzerland) · 2022Article
- Derivation and Validation of a Predictive Scoring Model of Infections Due toInfection and drug resistance · 2022Article
- Recommendations for antibiotic selection for severe nosocomial infections.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2021Article
- Clinical Impact and Risk Factors of Nonsusceptibility to Third-Generation Cephalosporins Among Hospitalized Adults with MonomicrobialInfection and drug resistance · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.