ArticleBMC medical research methodology2017
Basic parametric analysis for a multi-state model in hospital epidemiology.
Article in BMC medical research methodology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Modeling chronic kidney disease progression using a continuous-time multistate Markov model: Transition dynamics and covariate effects.The Journal of international medical research · 2026Article
- Article
- Testing Similarity of Parametric Competing Risks Models for Identifying Potentially Similar Pathways in Healthcare.Statistics in medicine · 2024Article
- Predicting the effect of nosocomial infection prevention on neonatal mortality and hospital stay in Ethiopia: a prospective longitudinal study.BMC infectious diseases · 2024Article
- Assessing the impact of Delta and Omicron in German intensive care units: a retrospective, nationwide multistate analysis.BMC health services research · 2024Article
- Tracing In-Hospital COVID-19 Outcomes: A Multistate Model Exploration (TRACE).Life (Basel, Switzerland) · 2024Article
- Investigation of multiple nosocomial infections using a semi-Markov multi-state model.Antimicrobial resistance and infection control · 2024Article
- Stacked probability plots of the extended illness-death model using constant transition hazards - an easy to use shiny app.BMC medical research methodology · 2024Article
- Ventilator-Associated Events Cost in ICU Patients Receiving Mechanical Ventilation: A Multi-State Model.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2024Article
- Lessons learned: avoiding bias via multi-state analysis of patients' trajectories in real-time.Frontiers in medicine · 2024Article
- Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis.Scientific reports · 2023Article
- Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19.Life (Basel, Switzerland) · 2023Article
- Reply by Charles-Hervé Vacheron.American journal of respiratory and critical care medicine · 2023Article
- Semi-parametric time-to-event modelling of lengths of hospital stays.Journal of the Royal Statistical Society. Series C, Applied statistics · 2022Article
- Attributable Mortality of Ventilator-associated Pneumonia Among Patients with COVID-19.American journal of respiratory and critical care medicine · 2022Article
- Relaxing the assumption of constant transition rates in a multi-state model in hospital epidemiology.BMC medical research methodology · 2021Article
- Estimands to quantify prolonged hospital stay associated with nosocomial infections.BMC medical research methodology · 2019Article
- The wild bootstrap for multivariate Nelson-Aalen estimators.Lifetime data analysis · 2019Review
- Simulation shows undesirable results for competing risks analysis with time-dependent covariates for clinical outcomes.BMC medical research methodology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe extended illness-death model is a useful tool to study the risks and consequences of hospital-acquired infections (HAIs). The statistical quantities of interest are the transition-specific hazard rates and the transition probabilities as well as attributable mortality (AM) and the population-attributable fraction (PAF). In the most general case calculation of these expressions is mathematically complex.
methodsWhen assuming time-constant hazards calculation of the quantities of interest is facilitated. In this situation the transition probabilities can be expressed in closed mathematical forms. The estimators for AM and PAF can be easily derived from these forms.
resultsIn this paper, we show how to explicitly calculate all the transition probabilities of an extended-illness model with constant hazards. Using a parametric model to estimate the time-constant transition specific hazard rates of a data example, the transition probabilities, AM and PAF can be directly calculated. With a publicly available data example, we show how the approach provides first insights into principle time-dynamics and data structure.
conclusionAssuming constant hazards facilitates the understanding of multi-state processes. Even in a non-constant hazards setting, the approach is a helpful first step for a comprehensive investigation of complex data.
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.