Objective: To establish the diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) when screening externally validated cognition in Parkinson disease (PD), by comparison with a PD-focused test (Scales for Outcomes in Parkinson disease–Cognition [SCOPA-COG]) and the standardized Mini-Mental State Examination (S-MMSE) as benchmarks. Methods: A convenience sample of 114 patients with idiopathic PD and 47 healthy controls was examined in a movement disorders center. The 21 patients with dementia (PD-D) were diagnosed using Movement Disorders Society criteria, externally validated by detailed independent functional and neuropsychological tests. The 21 patients with mild cognitive impairment (PD-MCI) scored 1.5 SD or more below normative data in at least 2 measures in 1 of 4 cognitive domains. Other patients had normal cognition (PD-N). Results: Primary outcomes using receiver operating characteristic (ROC) curve analyses showed that all 3 mental status tests produced excellent discrimination of PD-D from patients without dementia (area under the curve [AUC], 87%–91%) and PD-MCI from PD-N patients (AUC, 78%–90%), but the MoCA was generally better suited across both assessments. The optimal MoCA screening cutoffs were <21/30 for PD-D (sensitivity 81%; specificity 95%; negative predictive value [NPV] 92%) and <26/30 for PD-MCI (sensitivity 90%; specificity 75%; NPV 95%). Further support that the MoCA is at least equivalent to the SCOPA-COG, and superior to the S-MMSE, came from the simultaneous classification of the 3 PD patient groups (volumes under a 3-dimensional ROC surface, chance = 17%: MoCA 79%, confidence interval [CI] 70%–89%; SCOPA-COG 74%, CI 62%–86%; MMSE-Sevens item 56%, CI 44%–68%; MMSE-World item 62%, CI 50%–73%). Conclusions: The MoCA is a suitably accurate, brief test when screening all levels of cognition in PD.

Background Radiomic features calculated from routine medical images show great potential for personalised medicine in cancer. Patients with systemic sclerosis (SSc), a rare, multiorgan autoimmune disorder, have a similarly poor prognosis due to interstitial lung disease (ILD). Here, our objectives were to explore computed tomography (CT)-based high-dimensional image analysis (“radiomics”) for disease characterisation, risk stratification and relaying information on lung pathophysiology in SSc-ILD. Methods We investigated two independent, prospectively followed SSc-ILD cohorts (Zurich, derivation cohort, n=90; Oslo, validation cohort, n=66). For every subject, we defined 1355 robust radiomic features from standard-of-care CT images. We performed unsupervised clustering to identify and characterise imaging-based patient clusters. A clinically applicable prognostic quantitative radiomic risk score (qRISSc) for progression-free survival (PFS) was derived from radiomic profiles using supervised analysis. The biological basis of qRISSc was assessed in a cross-species approach by correlation with lung proteomic, histological and gene expression data derived from mice with bleomycin-induced lung fibrosis. Results Radiomic profiling identified two clinically and prognostically distinct SSc-ILD patient clusters. To evaluate the clinical applicability, we derived and externally validated a binary, quantitative radiomic risk score (qRISSc) composed of 26 features that accurately predicted PFS and significantly improved upon clinical risk stratification parameters in multivariable Cox regression analyses in the pooled cohorts. A high qRISSc score, which identifies patients at risk for progression, was reverse translatable from human to experimental ILD and correlated with fibrotic pathway activation. Conclusions Radiomics-based risk stratification using routine CT images provides complementary phenotypic, clinical and prognostic information significantly impacting clinical decision making in SSc-ILD.

Lipoprotein(a) [Lp(a)] is a recognized causal risk factor for atherosclerotic cardiovascular disease but its role for acute ischaemic stroke (AIS) is controversial. In this study, we evaluated the association of Lp(a) with large artery atherosclerosis (LAA) stroke and risk of recurrent cerebrovascular events in AIS patients. For this analysis of the prospective, observational, multicentre BIOSIGNAL cohort study we measured Lp(a) levels in plasma samples of 1733 primarily Caucasian (98.6%) AIS patients, collected within 24 h after symptom onset. Primary outcomes were LAA stroke aetiology and recurrent cerebrovascular events (ischaemic stroke or transient ischaemic attack) within 1 year. We showed that Lp(a) levels are independently associated with LAA stroke aetiology [adjusted odds ratio 1.48, 95% confidence interval (CI) 1.14-1.90, per unit log₁₀Lp(a) increase] and identified age as a potent effect modifier (P_interaction =0.031) of this association. The adjusted odds ratio for LAA stroke in patients aged <60 years was 3.64 (95% CI 1.76–7.52) per unit log₁₀Lp(a) increase and 4.04 (95% CI 1.73–9.43) using the established cut-off ≥100 nmol/l. For 152 recurrent cerebrovascular events, we did not find a significant association in the whole cohort. However, Lp(a) levels ≥100 nmol/l were associated with an increased risk for recurrent events among patients who were either <60 years [adjusted hazard ratio (HR) 2.40, 95% CI 1.05–5.47], had evident LAA stroke aetiology (adjusted HR 2.18, 95% CI 1.08–4.40), or had no known atrial fibrillation (adjusted HR 1.60, 95% CI 1.03–2.48). Elevated Lp(a) was independently associated with LAA stroke aetiology and risk of recurrent cerebrovascular events among primarily Caucasian individuals aged <60 years or with evident arteriosclerotic disease.