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AbstractBackground and objectivePleuroscopy with pleural biopsy has a high sensitivity for malignant pleural effusion (MPE). Because MPEs tend to recur, concurrent diagnosis and treatment of MPE during pleuroscopy is desired. However, proceeding directly to treatment at the time of pleuroscopy requires confidence in the on‐site diagnosis. The study's primary objective was to create a predictive model to estimate the probability of MPE during pleuroscopy.MethodsA prospective observational multicentre cohort study of consecutive patients undergoing pleuroscopy was conducted. We used a logistic regression model to evaluate the probability of MPE with relation to visual assessment, rapid on‐site evaluation (ROSE) of touch preparation and presence of pleural nodules/masses on computed tomography (CT). To assess the model's prediction accuracy, a bootstrapped training/testing approach was utilized to estimate the cross‐validated area under the receiver operating characteristic curve.ResultsOf the 201 patients included in the study, 103 had MPE. Logistic regression showed that higher level of malignancy on visual assessment is associated with higher odds of MPE (OR = 34.68, 95% CI = 9.17–131.14,p < 0.001). The logistic regression also showed that higher level of malignancy on ROSE of touch preparation is associated with higher odds of MPE (OR = 11.63, 95% CI = 3.85–35.16,p < 0.001). Presence of pleural nodules/masses on CT is associated with higher odds of MPE (OR = 6.61, 95% CI = 1.97–22.1,p = 0.002). A multivariable logistic regression model of final pathologic status with relation to visual assessment, ROSE of touch preparation and presence of pleural nodules/masses on CT had a cross‐validated AUC of 0.94 (95% CI = 0.91–0.97).ConclusionA prediction model using visual assessment, ROSE of touch preparation and CT scan findings demonstrated excellent predictive accuracy for MPE. Further validation studies are needed to confirm our findings.

Respiratory tissue resident–like CD8 + T cells are associated with chronic lung sequelae post-acute COVID-19.

Objective The aim of this study was to search for genes/variants that modify the effect of LRRK2 mutations in terms of penetrance and age‐at‐onset of Parkinson's disease. Methods We performed the first genomewide association study of penetrance and age‐at‐onset of Parkinson's disease in LRRK2 mutation carriers (776 cases and 1,103 non‐cases at their last evaluation). Cox proportional hazard models and linear mixed models were used to identify modifiers of penetrance and age‐at‐onset of LRRK2 mutations, respectively. We also investigated whether a polygenic risk score derived from a published genomewide association study of Parkinson's disease was able to explain variability in penetrance and age‐at‐onset in LRRK2 mutation carriers. Results A variant located in the intronic region of CORO1C on chromosome 12 (rs77395454; p value = 2.5E‐08, beta = 1.27, SE = 0.23, risk allele: C) met genomewide significance for the penetrance model. Co‐immunoprecipitation analyses of LRRK2 and CORO1C supported an interaction between these 2 proteins. A region on chromosome 3, within a previously reported linkage peak for Parkinson's disease susceptibility, showed suggestive associations in both models (penetrance top variant: p value = 1.1E‐07; age‐at‐onset top variant: p value = 9.3E‐07). A polygenic risk score derived from publicly available Parkinson's disease summary statistics was a significant predictor of penetrance, but not of age‐at‐onset. Interpretation This study suggests that variants within or near CORO1C may modify the penetrance of LRRK2 mutations. In addition, common Parkinson's disease associated variants collectively increase the penetrance of LRRK2 mutations. ANN NEUROL 2021;90:82–94