![]() ![]() Days in hospital and days dead were then subtracted from the total potential follow-up time to arrive at DAOH for each patient. If a patient died, the number of days from their death to the end of the study was assigned as days dead. The total time spent in hospital was computed by adding the durations of each individual hospital stay. The number of nights spent in hospital over the previous 6 months was captured on the patient questionnaire at 6, 12, 18 and 24 months. Patients who were lost to follow-up had a censoring date of to determine potential follow-up time. The number of days alive and out of hospital (DAOH) was calculated for each patient as follows: 67 the total potential follow-up time was determined as the number of days from randomisation until the date of the final follow-up time point (if alive) or the end of study date,, if the patient had died. A covariance pattern mixed model was used similar to that described for the primary analysis including a variable for treatment with the three levels.Ī non-significant difference was observed between the NOT and LTOT arms in a pairwise comparison from this model therefore, these arms were combined and compared against the BMT arm on the primary outcome using a similar analysis, and including only patients randomised up to the time that the NOT arm was dropped from the study. This was to ensure comparability of the treatment groups. We conducted an exploratory analysis on the primary outcome including all three treatment arms, which included only contemporaneously recruited patients, that is only patients in any arm randomised up to the date at which the randomisation to the NOT arm was closed. In April 2013, the decision was made to stop recruitment to the NOT arm, although patients in this group continued to be followed up. Initially, the HOT trial recruited patients to three trial arms: BMT, LTOT and NOT. An overall effect of the intervention across all included time points was not extracted.Ĭomparisons with the nocturnal oxygen therapy subgroup Estimates for the other time points serve as secondary outcomes. The primary end point is the treatment effect estimate at 6 months. Participants were naturally included in the model only if they had full data for the baseline covariates and outcome data for at least one post-randomisation time point (3, 6 or 12 months).Įstimates of the adjusted mean difference (AMD) between treatment groups in MLwHF questionnaire scores were extracted from the model for all time points with 95% confidence intervals (CIs) and p-values. Diagnostics including Akaike’s information criterion 65 were compared for each model (smaller values are preferred). NT-proBNP data were found to be significantly positively skewed and so were log transformed.ĭifferent covariance structures for the repeated measurements, which are available as part of Stata version 13, were explored and the most appropriate pattern used for the final model. Age, NT-proBNP levels and creatinine levels were all continuous variables as assessed at baseline. The model included as fixed effects baseline MLwHF questionnaire score, age, log-NT-proBNP level, creatinine level, treatment group, time and a treatment group–time interaction term. The outcome modelled was total MLwHF questionnaire scores at 3, 6 and 12 months. Our primary analysis compared MLwHF questionnaire scores between the LTOT and BMT treatment groups using a covariance pattern mixed model, where effects of interest and baseline covariates are specified as fixed effects, and the correlation of observations within patients is modelled by a covariance structure. Where the mean was less than 0 or greater than 5 (the range of permitted scores for the MLwHF questionnaire) it was replaced with the nearest permitted value. The mean of the imputed values for each patient was used to replace the missing item. Linear regression was used to perform the imputation and five imputed data sets were created. Multiple imputation using chained equations was used to fill in missing questionnaire items, where there were fewer than four missing item responses, using other items in the questionnaire ( ). ![]() The number of missing MLwHF questionnaire responses was examined at each time point. The MLwHF questionnaire consists of 21 items and a total score is obtained by summing the item scores, where all 21 items have a response. A lower MLwHF questionnaire score indicates a better QoL. The primary outcome was health-related quality of life (HRQoL) as measured by the MLwHF questionnaire scores at 6 months. ![]()
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