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There were no missing mortality data.
Five patients with missing mortality data were excluded.
In addition, we imputed missing mortality data and conducted a sensitivity analysis to assess the impact of missing mortality data on the mortality prediction of SHARE-FI.
The item 'completeness of follow-up' was fulfilled if ≤10% of patients had been excluded because of missing mortality data.
A limitation of our prospective validation was the significant proportion of missing mortality data in the baseline SHARE Wave 1 sample.
34 The fact that missing mortality data were associated with being older and more frail suggests that in reality, the frailty-associated mortality rates may be higher than the ones estimated by this study.
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The release of wave 2 data contains a variable that informs whether respondents were still alive in wave 3, deceased between wave 2 and wave 3, or with missing mortality information (ie, 2-year mortality data).
The proportion of missing mortality and meteorological data was very low.
Of these, 698 (5.4%) were excluded: 222 (1.7%) had missing arterial blood gas data, 382 (3.0%) had missing hospital mortality data and 94 (0.7%) were ICU readmissions.
Due to study attrition, missing data, or mortality, data were available from fewer patients at the 1 (96%), 3 (89%), 6 (82%), and 12 (78%) month follow-up assessments.
Two algorithms were developed, a conservative approach whereby status in matched data needed to be recorded as Indigenous in the majority of instances for an individual with missing status in mortality data to be considered Indigenous, and a more inclusive approach which classified a person as Indigenous if they had ever been identified as Indigenous in any of the linked databases.
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