Where data from non-randomised studies were included, the results for each outcome were presented separately for each study or meta-analysed if appropriate. 4.3.3 Methods of combining clinical studies 4.3.3.1 Data synthesis for intervention reviews Where possible, meta-analyses were conducted using Cochrane Review Manager (RevMan5)283 software to combine the data given in all studies for each of the outcomes of interest for the review question. For some questions stratification was used, and this is documented in the individual review question protocols (see appendix A). Analysis of different types of data Chronic Heart Failure Methods NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Dichotomous outcomes Fixed-effects (Mantel-Haenszel) techniques were used to calculate risk ratios (relative risk, RR) for the binary outcomes, which included: All-cause mortality Cardiovascular mortality Unplanned hospitalisation HF related hospitalisation Adverse events (for example stroke, bradycardia, hypotension, arrhythmic events, hyperkalaemia) Change in NYHA class Change in management HF medication use HF advanced therapy use, including disease specific therapies Repeat testing or additional testing Additional revascularisation events Patient and carer satisfaction Successful administration of intervention Withdrawal due to adverse events/tolerability Medicine optimisation and adherence Dying in preferred place of death (for palliative care patients) Adherence to intervention Health service use The absolute risk difference was also calculated using GRADEpro138 software, using the median event rate in the control arm of the pooled results. For binary variables where there were zero events in either arm or a less than 1% event rate, Peto odds ratios, rather than risk ratios, were calculated. Peto odds ratios are more appropriate for data with a low number of events. Continuous outcomes Continuous outcomes were analysed using an inverse variance method for pooling weighted mean differences. 