RESUMEN
A prospective cohort study investigating patients with obstructive sleep apnoea (OSA) was conducted to determine the prevalence of dysfunctional breathing and if continuous positive airway pressure (CPAP) therapy improves associated symptoms. Almost half of newly diagnosed patients with OSA had dysfunctional breathing and CPAP was not an effective treatment. Dysfunctional breathing is common in patients with OSA.
Asunto(s)
Presión de las Vías Aéreas Positiva Contínua , Apnea Obstructiva del Sueño , Humanos , Polisomnografía , Estudios Prospectivos , Apnea Obstructiva del Sueño/diagnóstico , Apnea Obstructiva del Sueño/epidemiología , Apnea Obstructiva del Sueño/terapia , Resultado del TratamientoRESUMEN
The causal effect of an exposure on an outcome of interest in an observational study cannot be estimated directly if the confounding variables are not controlled. Many approaches are available for estimating the causal effect of an exposure. In this manuscript, we demonstrate the advantages associated with using inverse probability weighting (IPW) and doubly robust estimation of the odds ratio in terms of reduced bias. IPW approach can be used to adjust for confounding variables and provide unbiased estimates of the exposure's causal effect. For cluster-structured data, as is common in animal populations, inverse conditional probability weighting (ICPW) approach can provide a robust estimation of the causal effect. Doubly robust estimation can provide a robust method even when the specification of the model form is uncertain. In this paper, the usage of IPW, ICPW, and doubly robust approaches are illustrated with a subset of data with complete covariates from the Australian-based National Bovine Respiratory Disease Initiative as well as simulated data. We evaluate the causal effect of prior bovine viral diarrhea exposure on bovine respiratory disease in feedlot cattle. The results show that the IPW, ICPW and doubly robust approaches would provide a more accurate estimation of the exposure effect than the traditional outcome regression model, and doubly robust approaches are the most preferable overall.