In order to allow validation, we applied WNA to a derivation dataset consisting of a random selection of two-thirds (n=430) of ALTOS patients, with the remaining one-third (n=215) reserved for validation.
#SUBTYPE TIME CALC VIEW TRIAL#
We dealt with the rare missing data in the trial dataset predictors, as outlined in our initial work, with multivariate single imputation before initiation of analysis we did not impute any outcome data. The present work thus focuses on identifying subtypes among ARDS outcomes, characterising the subtypes and building prediction models for subtype membership. 22 The present work builds on, and differs from, that preliminary work by performing a cluster analysis of the limited predictor set and merging those clusters with the outcome data.
#SUBTYPE TIME CALC VIEW PROFESSIONAL#
That initial work identified nine predictors associated with 6-month health utility: age, sex, Latino ethnicity, current smoking at the time of hospital admission, body mass index, pulmonary comorbidity, AIDS comorbidity, nadir respiratory rate on the day of study enrolment and residential independence at time of hospital admission (ie, whether the patient resided at home with no help, at home with informal help or required either professional help at home or resided in a healthcare facility). 26 This first step allowed us to reduce the number of candidate predictors to facilitate subsequent clustering. We began this work with a penalised regression model of 6-month health utility scores obtained from the EQ-5D-3L QOL instrument, 23–25 the results of which have been published. This work represents the first essential step in endotyping: the identification and definition of apparent subtypes among ARDS survivors. Hence, to advance the understanding of post-ARDS patient outcomes, especially the associations among physical, cognitive and mental health status, we performed a cluster analysis of ARDS survivors enrolled in a national, multicentre study to identify outcome subtypes. 13 Identifying endotypes also may allow targeted studies of causal mechanisms and therapeutic interventions in a way that is not currently possible when evaluating more heterogeneous patient groups. 12 If multiple post-ARDS outcome endotypes exist, identifying such endotypes could facilitate research directed at understanding the pathophysiology, natural history and response to therapy within the larger pool of ARDS survivors. Those subtypes that ultimately prove to be associated with a biological mechanism are then considered endotypes. 11 The discovery of endotypes is a multistep process that begins with the identification of apparent subtypes (sometimes called subgroups or phenotypes). 10 Distinct syndromes within larger clinical phenomena-when they include biological mechanisms paired with specific phenotypes-are commonly termed endotypes. Some researchers suggest that survivors’ post-ICU health status impairments represent not one syndrome but many. 8 9 Despite substantial epidemiological research describing impairments in these outcome domains, the patterns and co-occurrence across domains of impairment are poorly understood. 3 4 ARDS survivors frequently experience persistent impairments in physical (eg, muscle weakness), cognitive (eg, impaired memory) and mental health (eg, anxiety) status, coupled with reduced quality of life (QOL), 5–7 known as the postintensive care syndrome. Recent advances have reduced short-term mortality for patients with acute respiratory distress syndrome (ARDS), 1 2 with an increasing focus on the postdischarge morbidities commonly experienced by ARDS survivors.
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