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A much smaller number of patients were identified as maximum-risk using the RISC [ 21].
Multilog was used to estimate person location (θ, reflecting participants' perceived risk) using maximum a posteriori (MAP) estimation.
Summary estimates were obtained by pooling the city specific relative risks using a restricted maximum likelihood random effects model [ 17].
The study and the control groups were compared for severity of disease using the Simplified Acute Physiology Score 3 (SAPS 3) score [ 21], for organ failure and dysfunction using the Sepsis-related Organ Failure Assessment (SOFA) score from the first 24 hours [ 22] and for acute kidney injury using the maximum Risk, Injury, Failure, Loss and End Stage (RIFLE) score during the study [ 23].
Targeting limited resources, to medium and high-risk individuals (maximum risk), could improve efficiency in the use of limited healthcare resources [ 43].
The use of Manual NB provides a maximum risk score of 4 for four countries, whereas with Jenks NB three countries presented a risk score of 5.
When the mean number of risk alleles in the population was used as the reference (in the model including the significant seven SNPs), the maximum risk increase was 1.42 (95% CI: 1.22 1.66) for ⩾3 risk alleles above mean and a maximum protection of 0.67 (0.58–0.78) for women with ⩾2 risk alleles below mean.
Of patients predicted at baseline to be at maximum-risk of institutionalisation, using the RISC, 30/96 (31.3 %) were admitted to LTC in the first year compared to 49/686 (7.1 %) of those scored minimum-risk, p < 0.001.
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