ArticleBMJ open2024
Nomogram for predicting moderate-to-severe sleep-disordered breathing in patients with acute ischaemic stroke: a retrospective cohort study.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesModerate-to-severe sleep-disordered breathing (SDB) is prevalent in patients with acute ischaemic stroke (AIS) and is associated with an increased risk of unfavourable prognosis. We aimed to develop and validate a reliable scoring system for the early screening of moderate-to-severe SDB in patients with AIS, with the objective of improving the management of those patients at risk. STUDY
designWe developed and validated a nomogram model based on univariate and multivariate logistic analyses to identify moderate-to-severe SDB in AIS patients. Moderate-to-severe SDB was defined as an apnoea-hypopnoea index (AHI) ≥15. To evaluate the effectiveness of our nomogram, we conducted a comparison with the STOP-Bang questionnaire by analysing the area under the receiver operating characteristic curve.
settingLarge stroke centre in northern Shanghai serving over 4000 inpatients, 100 000 outpatients and emergency visits annually.
participantsWe consecutively enrolled 116 patients with AIS from the Shanghai Tenth People's Hospital.
resultsFive variables were independently associated with moderate-to-severe SDB in AIS patients: National Institutes of Health Stroke Scale score (OR=1.20; 95% CI 0.98 to 1.47), neck circumference (OR=1.50; 95% CI 1.16 to 1.95), presence of wake-up stroke (OR=21.91; 95% CI 3.08 to 156.05), neuron-specific enolase level (OR=1.27; 95% CI 1.05 to 1.53) and presence of brainstem infarction (OR=4.21; 95% CI 1.23 to 14.40). We developed a nomogram model comprising these five variables. The C-index was 0.872, indicated an optimal agreement between the observed and predicted SDB patients.
conclusionsOur nomogram offers a practical approach for early detection of moderate-to-severe SDB in AIS patients. This tool enables individualised assessment and management, potentially leading to favourable outcomes.
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