Sleep History and Hypertension Burden in First-Generation Chinese Migrants Settled in Italy: The CHIinese in Prato Cross-Sectional Survey

Migration flows from China are largely directed towards the South of Europe, Chinese being now the third largest overseas-born population in Italy. The aim of the study was to investigate hypertension burden and self-reported sleep disorders among 1608 first-generation Chinese migrants aged 16 to 59 years settled in Prato and recruited in a cross-sectional survey. Hypertension was defined as systolic BP ≥140 mm Hg and/or diastolic BP ≥90 mm Hg or self-reported antihypertensive treatment; potential impact of sleep disorders was analyzed by logistic regression adjusted for age, sex, marital status, education, health insurance, current smoking, parental hypertension, alcohol drinking, overweight or obesity, central obesity, diabetes, high total cholesterol, and high triglycerides. Among the 1608 participants, 21.7% were hypertensive (age-standardized prevalence 19.2%; 95% Cl: 18.5–20.0); 54% of hypertensive subjects were aware of their condition; 70% of aware hypertensive subjects received drugs, and 39% of treated subjects had blood pressure controlled. Self-reported snoring increased the risk of hypertension; when compared with no snoring, the age- and sex-adjusted OR for hypertension of snoring 3 to 6 d/week was 2.11 (95% Cl: 1.48–3.01) and 2.48 (95% Cl: 1.79–3.46) of snoring every day. When compared with a sleep duration ≤5 hours, subjects with sleep duration of 7 hours had reduced risk of high triglycerides (adjusted OR: 0.66; 95% Cl: 0.43–0.95). Despite a high level of awareness, low treatment rates for hypertension were observed among Chinese participants, independently of health insurance. Sleep history is to be considered in screening and prevention programs

Prevalence, Awareness, Treatment, and Control of Hypertension among Chinese First-Generation Migrants and Italians in Prato, Italy: The CHIP Study

Data on health needs of Chinese living in the South of Europe are lacking. To compare prevalence, awareness, treatment, control, and risk factors for hypertension between Chinese migrants and Italian adults, a sample of 1200 first-generation Chinese migrants and 291 native Italians aged 35–59 years living in Prato (Italy) was recruited in a community-based participatory cross-sectional survey. Primary outcome measure was hypertension, diagnosed for blood pressure values ≥ 140/90 mmHg or current use of antihypertensive medications. Associations with exposures (including age, gender, body mass index, waist, education level, total cholesterol, and triglycerides) were examined using logistic regression. When compared with Italians, Chinese had higher hypertension prevalence (27.2% versus 21.3%, p<0.01), with comparable levels of awareness (57.4% and 48.4%) but lower treatment rates (70.6% and 90.0%, resp.). In both ethnic groups age and parental history of hypertension were predictors of awareness and treatment, body mass index being predictor of hypertension diagnosis. In Chinese participants, where the optimum cut-off point for body mass index was ≥23.9 kg/m2, the sensibility and specificity prediction for hypertension were 61.7% and 59.8%, respectively (area under the ROC curve = 0.629). Implementation of specific, culturally adapted health programs for the Chinese community is now needed

Prevalence, Awareness, Treatment, and Control of Hypertension among Chinese First-Generation Migrants and Italians in Prato, Italy: The CHIP Study

Data on health needs of Chinese living in the South of Europe are lacking. To compare prevalence, awareness, treatment, control, and risk factors for hypertension between Chinese migrants and Italian adults, a sample of 1200 first-generation Chinese migrants and 291 native Italians aged 35-59 years living in Prato (Italy) was recruited in a community-based participatory crosssectional survey. Primary outcome measure was hypertension, diagnosed for blood pressure values ≥ 140/90 mmHg or current use of antihypertensive medications. Associations with exposures (including age, gender, body mass index, waist, education level, total cholesterol, and triglycerides) were examined using logistic regression. When compared with Italians, Chinese had higher hypertension prevalence (27.2% versus 21.3%, &lt; 0.01), with comparable levels of awareness (57.4% and 48.4%) but lower treatment rates (70.6% and 90.0%, resp.). In both ethnic groups age and parental history of hypertension were predictors of awareness and treatment, body mass index being predictor of hypertension diagnosis. In Chinese participants, where the optimum cut-off point for body mass index was ≥23.9 kg/m 2 , the sensibility and specificity prediction for hypertension were 61.7% and 59.8%, respectively (area under the ROC curve = 0.629). Implementation of specific, culturally adapted health programs for the Chinese community is now needed

Validity of machine learning in predicting giant cell arteritis flare after glucocorticoids tapering

BackgroundInferential statistical methods failed in identifying reliable biomarkers and risk factors for relapsing giant cell arteritis (GCA) after glucocorticoids (GCs) tapering. A ML approach allows to handle complex non-linear relationships between patient attributes that are hard to model with traditional statistical methods, merging them to output a forecast or a probability for a given outcome. ObjectiveThe objective of the study was to assess whether ML algorithms can predict GCA relapse after GCs tapering. MethodsGCA patients who underwent GCs therapy and regular follow-up visits for at least 12 months, were retrospectively analyzed and used for implementing 3 ML algorithms, namely, Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF). The outcome of interest was disease relapse within 3 months during GCs tapering. After a ML variable selection method, based on a XGBoost wrapper, an attribute core set was used to train and test each algorithm using 5-fold cross-validation. The performance of each algorithm in both phases was assessed in terms of accuracy and area under receiver operating characteristic curve (AUROC). ResultsThe dataset consisted of 107 GCA patients (73 women, 68.2%) with mean age ( +/- SD) 74.1 ( +/- 8.5) years at presentation. GCA flare occurred in 40/107 patients (37.4%) within 3 months after GCs tapering. As a result of ML wrapper, the attribute core set with the least number of variables used for algorithm training included presence/absence of diabetes mellitus and concomitant polymyalgia rheumatica as well as erythrocyte sedimentation rate level at GCs baseline. RF showed the best performance, being significantly superior to other algorithms in accuracy (RF 71.4% vs LR 70.4% vs DT 62.9%). Consistently, RF precision (72.1%) was significantly greater than those of LR (62.6%) and DT (50.8%). Conversely, LR was superior to RF and DT in recall (RF 60% vs LR 62.5% vs DT 47.5%). Moreover, RF AUROC (0.76) was more significant compared to LR (0.73) and DT (0.65). ConclusionsRF algorithm can predict GCA relapse after GCs tapering with sufficient accuracy. To date, this is one of the most accurate predictive modelings for such outcome. This ML method represents a reproducible tool, capable of supporting clinicians in GCA patient management

Interstitial lung disease with and without progressive fibrosing phenotype in patients with idiopathic inflammatory myopathies: data from a large multicentric cohort

Objectives: Patients with connective tissue diseases can develop interstitial lung disease (ILD), leading to a progressive fibrosing ILD (PF-ILD) phenotype in some cases. We aimed to investigate the occurrence of PF-ILD in idiopathic inflammatory myopathies (IIMs), and factors potentially predicting this phenotype. Secondary aims were to assess the radiological pattern and factors associated with IIMs-ILD. Methods: Patients with IIMs from our multicentric prospective cohort were retrospectively evaluated. Data were recorded at IIMs and ILD diagnosis, and during follow-up. Patients with ILD were classified according to the predominant high-resolution CT (HRCT) pattern: non-specific interstitial pneumonia (NSIP), usual interstitial pneumonia (UIP) and organising pneumonia (OP). PF-ILD was defined according to the 2022 American Thoracic Society (ATS), European Respiratory Society (ERS), Japanese Respiratory Society (JRS) and Latin American Thoracic Society (ALAT) guidelines. Univariate and multivariate analyses were performed to identify factors associated to ILD and to PF-ILD. Results: Of 253 patients with IIMs, 125 (49%) had ILD: 99 (78%) at IIMs diagnosis and 26 (22%) during follow-up (21/26 within 5 years). Multivariate analysis identified anti-Jo-1, anti-MDA5, anti-Ro52, high score on manual muscle test, mechanic's hands and Raynaud's phenomenon as independently associated with ILD. The predominant HRCT pattern was NSIP (50% of patients), followed by UIP (28%) and OP (22%). At 1-year follow-up, PF-ILD occurred in 18% of IIMs-ILD. PF-ILD was predicted by anti-MDA5, heliotropic rash, xerostomia and xerophthalmia at univariate but not at multivariate analysis. Conclusion: Patients with IIM should be carefully screened for ILD at IIMs diagnosis and yearly during follow-up. All patients with IIMs-ILD should be carefully monitored to capture ILD progression since a consistent proportion of them are expected to develop PF-ILD