The proportional odds model for ordinal logistic regression provides a useful extension of the binary logistic model to situations where the response variable takes on values in a set of ordered categories. The model may be represented by a series of logistic regressions for dependent binary variables, with common regression parameters reflecting the proportional odds assumption. Key to the valid application of the model is the assessment of the proportionality assumption. An approach is described arising from comparisons of the separate (correlated) fits to the binary logistic models underlying the overall model. Based on asymptotic distributional results, formal goodness-of-fit measures are constructed to supplement informal comparisons of the different fits. A number of proposals, including application of bootstrap simulation, are discussed and illustrated with a data example.

The ELISAs in general dominate the comparative ranking among the d-dimer assays for sensitivity and negative likelihood ratio. For excluding PE or DVT, a negative result on quantitative rapid ELISA is as diagnostically useful as a normal lung scan or negative duplex ultrasonography finding.

Nocturnal polysomnography, the standard diagnostic test for sleep apnea, is an expensive and limited resource. In order to help identify the urgency of need for treatment, we determined which clinical features were most useful for establishing an accurate estimate of the probability that a patient had sleep apnea. Of 263 physician-referred patients, 200 were eligible for the study and 180 (90%) completed it. All patients had their histories recorded with a standard questionnaire, and underwent anthropomorphic measurements and nocturnal polysomnography. Sleep apnea was defined as more than 10 episodes of apnea or hypopnea per hour of sleep. Multiple linear and logistic regression models predictive of sleep apnea were compared with physicians' subjective impressions and previously reported models. Likelihood ratios were calculated for several levels of a sleep apnea clinical score produced by one of the linear models. Predictors of sleep apnea in the final model (R2 = 0.34) included neck circumference, hypertension, habitual snoring, and bed partner reports of nocturnal gasping/choking respirations. This model was superior to physician impression, slightly inferior to more detailed linear and logistic models, and comparable to previously reported models. A sleep apnea clinical score of less than 5 had a likelihood ratio of 0.25 (95% CI: 0.15 to 0.42) and a corresponding posttest probability of 17%, while a score of greater than 15 had a likelihood ratio of 5.17 (95% CI: 2.54 to 10.51) and posttest probability of 81%. These likelihood ratios can simply and accurately determined the probability of whether a patient has sleep apnea.

Campbell, B. C.V. et al. (2019) Penumbral imaging and functional outcome in patients with anterior circulation ischaemic stroke treated with endovascular thrombectomy versus medical therapy: a meta-analysis of individual patient-level data.ABSTRACT Background: CT-perfusion (CTP) and MRI may assist patient selection for endovascular thrombectomy. We aimed to establish whether imaging assessments of ischaemic core and penumbra volumes were associated with functional outcomes and treatment effect.

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