Parkinson Hastalığında Bilişsel Bozulmanın Tanımlanması İçin Uyku Anketi ile Birleştirilmiş Rutin Kan Göstergeleri: Sızıntısız Yuvalı Modelleme Çerçevesine Sahip Bir Kesitsel Çalışma.

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BackgroundCognitive impairment (CI) is a prevalent non-motor complication of Parkinson's disease (PD), yet accessible and reliable screening aids remain limited. This cross-sectional study aimed to quantify the strength of association and the cross-sectional classification value of routine blood indicators combined with standardized sleep questionnaires for prevalent CI in PD, using a strictly leakage-free model-development pipeline.MethodsA total of 347 PD patients were enrolled and classified into PD-CI (n = 143) and PD-NCI (n = 204) groups based on the Montreal Cognitive Assessment (MoCA ResultsThe training-set LASSO retained 10 predictors: education, disease duration, Hoehn-Yahr stage, platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), homocysteine, C-reactive protein (CRP), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ). In the untouched test set, the full logistic regression model achieved an AUC of 0.943 (95% CI: 0.896-0.990) in the test set, higher than baseline (0.844), and comparable to the baseline-plus-blood (0.937) and baseline-plus-sleep (0.889) models; the incremental gain over baseline was statistically significant (DeLong p = 0.009). Repeated cross-validation gave a more conservative AUC of 0.921 (SD = 0.029). RF (0.956) and gradient boosting (0.944) did not outperform logistic regression. Calibration was acceptable (slope 1.18, intercept 0.03; test Brier 0.086, 95% CI 0.057-0.120) and findings were stable across alternative MoCA cut-offs (AUC 0.909-0.931).ConclusionCombining routine blood indicators and sleep questionnaires is cross-sectionally associated with prevalent CI in PD and adds information beyond clinical variables alone. Because the design is cross-sectional, single-center, and only internally validated, the model should be regarded as a candidate screening aid that requires external, preferably multicenter and prospective, validation before any clinical use.

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