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Hereafter this dataset is referred to as the model derivation dataset.
From now on, we will refer to this dataset as the model derivation dataset.
Eligible patients admitted at OUH-U between 1 August 2000 and 31 July 2006 formed the model derivation dataset.
Figure 3A shows the list of selected candidate genes, and a summary of their expression responses in the model derivation dataset.
In this visualisation we also plot the probe-specific expression levels for those genes with multiple microarray probes in the model derivation dataset.
As in our model derivation dataset, Kizil et al.'s dataset was obtained from microarray measurements from a heart amputation model in zebrafish.
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Given the importance of vital sign data in prior literature in this field, the availability of vital sign data was an important consideration for the definition of the model derivation datasets, as described below.
Options for validation depend on the information available in the publication describing the multivariable model for the derivation dataset.
We used a Cox proportional hazards model in the derivation dataset to estimate the coefficients and hazard ratios associated with each potential risk factor for the first ever recorded diagnosis of diabetes for men and women separately.
As in previous studies, 17 we used the Cox proportional hazards model in the derivation dataset to estimate the coefficients and hazard ratios (HRs) associated with each potential risk factor for the first recorded emergency admission to hospital for males and females separately.
As in previous analyses, 5 we used the Cox proportional hazards model in the derivation dataset to estimate the coefficients and hazard ratios associated with each potential risk factor for the first ever recorded diagnosis of stroke or transient ischaemic attack for males and females separately.
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Justyna Jupowicz-Kozak
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