ArticleIntensive care medicine2009
Modeling the effect of time-dependent exposure on intensive care unit mortality.
Article in Intensive care medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Mortality outcomes and economic burden of antimicrobial-resistant bacterial bloodstream infections in a Nigerian tertiary hospital.BMC microbiology · 2026Article
- Spectrum, dose, and duration of antibiotic exposure and risk of intensive care unit-acquired carbapenem-resistant gram-negative bacteria: a prospective cohort study.Annals of intensive care · 2025Article
- Making Patient-Specific Treatment Decisions Using Prognostic Variables and Utilities of Clinical Outcomes.Cancers · 2021Review
- Mortality review as a tool to assess the contribution of healthcare-associated infections to death: results of a multicentre validity and reproducibility study, 11 European Union countries, 2017 to 2018.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2021Article
- Cytomegalovirus reactivation and mortality in patients with acute respiratory distress syndrome.Intensive care medicine · 2016Article
- Nutrition support practices in critically ill head-injured patients: a global perspective.Critical care (London, England) · 2016Article
- Investigation of continuous effect modifiers in a meta-analysis on higher versus lower PEEP in patients requiring mechanical ventilation--protocol of the ICEM study.Systematic reviews · 2014Article
- Prognostic consequences of borderline dysnatremia: pay attention to minimal serum sodium change.Critical care (London, England) · 2013Observational
- Outcome of ICU patients with Clostridium difficile infection.Critical care (London, England) · 2012Article
- How to handle mortality when investigating length of hospital stay and time to clinical stability.BMC medical research methodology · 2011Article
- Clinical impact of antimicrobial resistance in European hospitals: excess mortality and length of hospital stay related to methicillin-resistant Staphylococcus aureus bloodstream infections.Antimicrobial agents and chemotherapy · 2011Article
- Multiple-center evaluation of mortality associated with acute kidney injury in critically ill patients: a competing risks analysis.Critical care (London, England) · 2011Article
- Attributable mortality of ventilator-associated pneumonia: respective impact of main characteristics at ICU admission and VAP onset using conditional logistic regression and multi-state models.Intensive care medicine · 2010Article
- A note on statistical association and causality derived from epidemiological ICU data.Intensive care medicine · 2010Article
- Year in review in Intensive Care Medicine 2009: I. Pneumonia and infections, sepsis, outcome, acute renal failure and acid base, nutrition and glycaemic control.Intensive care medicine · 2010Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo illustrate modern survival models with focus on the temporal dynamics of intensive care data. A typical situation is given in which time-dependent exposures and competing events are present.
methodsWe briefly review the following established statistical methods: logistic regression, regression models for event-specific hazards and the subdistribution hazard. These approaches are compared by showing advantages as well as disadvantages. All methods are applied to real data from a study of day-by-day ICU surveillance.
resultsStandard logistic regression ignores the time-dependent nature of the data and is only a crude approach. Cumulative hazards and probability plots add important information and provide a deep insight into the temporal dynamics.
conclusionThis paper might help to encourage researchers working in hospital epidemiology to apply adequate statistical models to complex medical questions.
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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.