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Aim: This Norwegian case study examines groups at risk of drug overdose deaths, evidence-based harm reduction interventions, low-threshold services and treatment implemented, as well as trends in drug overdose deaths between 2010 and 2021. We aimed to explore the relevance of interventions for at-risk groups and discuss their potential impact on drug overdose trends. Method/data: Using an ecological approach, we analysed the following: (1) groups identified through latent profile analysis (LPA) among a sample of 413 high-risk drug users collected in 2010–2012, supplemented with other relevant studies up to 2021; (2) published information on harm-reduction interventions, low-threshold services and treatment in Norway; and (3) nationwide drug overdose mortality figures supplemented with published articles on the topic. Results: High-risk drug users in 2010–2012 commonly engaged in frequent illegal drug use, injecting and poly-drug use (including pharmaceutical opioids), which continued into following decade. The interventions implemented between 2010 and 2021 were relevant for at-risk groups identified in the surveys. However, there was no decrease in the trend of drug overdose deaths up to 2021. While relevant interventions may have mitigated a theoretical increase in mortality, new at-risk groups may have contributed to fatal outcomes associated with pharmaceutical opioids. Conclusion: The interventions were relevant to the risk groups identified among high-risk drug users and potentially effective in preventing an increase in drug overdose trends. However, tailored interventions are needed for individuals at risk of death from prescribed opioids. Comprehensive studies encompassing all at-risk populations, including both legal and non-medical users of prescription opioids, are needed. [ABSTRACT FROM AUTHOR]

Aim: To assess whether stroke diagnoses in national health registers are sufficiently correct and complete to replace manual collection of endpoint data for the Tromsø Study, a population-based epidemiological study. Method: Using the Tromsø Study Cardiovascular Disease Register for 2013–2014 as the gold standard, we calculated correctness (defined as positive predictive value, PPV) and completeness (defined as sensitivity) of stroke cases in four different data subsets derived from the Norwegian Patient Register and the Norwegian Stroke Register. We calculated the sensitivity and PPV with 95% confidence intervals (CIs) assuming a normal approximation of the binomial distribution. Results: In the Norwegian Stroke Register we found a sensitivity of 79.8% (95% CI 74.2–85.4) and a PPV of 97.5% (95% CI 95.1–99.9). In the Norwegian Patient Register the sensitivity was 86.4% (95% CI 81.6–91.1) and the PPV was 84.2% (95% CI 79.2–89.2). The overall highest levels were found in a subset based on a linkage between the Norwegian Stroke Register and the Norwegian Patient Register, with a sensitivity of 88.9% (95% CI 84.5–93.3), and a PPV of 89.3% (95% CI 85.0–93.6). Conclusions: Data from the Norwegian Patient Register and from the linked data set between the Norwegian Patient Register and the Norwegian Stroke Register had acceptable levels of correctness and completeness to be considered as endpoint sources for the Tromsø Study Cardiovascular Disease Register. The benefits of using data from national registers as endpoints in epidemiological studies must be weighed against the impact of potentially decreased data quality. [ABSTRACT FROM AUTHOR]

Background: Physical activity (PA) is associated with reduced mortality. However, whether there is an added benefit of long‐term endurance training is unclear. Thus, we aimed to examine 10‐year mortality in older male endurance athletes compared with an older male general population. Method: Male athletes (n = 503) participating in an annual long‐distance ski race (median years of participation: 14, range: 1–53) from the Norwegian Birkebeiner Aging study (BiAS), and non‐athletic men (n = 1867) attending the sixth Tromsø Study (Tromsø6) aged ≥65 years were included. Associations with endurance sport practice and joint exposures of endurance sport practice and self‐reported leisure‐time PA with all‐cause mortality were examined. We analyzed the data with Cox proportional hazard models and regression standardization. Results: After 10 years (median: 10.4, range: 0.5–11.1) the mortality rate was lower in athletes (hazard ratio (HR) 0.34, 95% confidence interval (CI): 0.24–0.49) compared with non‐athletes, corresponding to a 15% (95% CI: 12–19%) absolute risk reduction associated with endurance sport practice. In joint analyses categorized according to PA and endurance sport practice, we observed an inverse dose–response relationship with mortality (p < 0.001). Compared to inactive non‐athletes, PA was associated with lower mortality in both active non‐athletes and athletes. However, the observed benefit among participants reporting moderate‐to‐vigorous PA was larger in athletes (HR: 0.21, 95% CI: 0.14–0.32) than non‐athletes (HR: 0.43, 95% CI: 0.31–0.59) (p < 0.01). Conclusion: Endurance sport practice was associated with reduced 10‐year mortality, beyond the effect of PA in older men. This study suggests that long‐term endurance sport practice maintained into older adulthood promotes longevity. [ABSTRACT FROM AUTHOR]

Simple Summary: Cervical cancer is the fourth most common cancer in women worldwide. Persistent high-risk human papillomavirus (HPV) can cause invasive cervical cancer through a series of precancerous lesions. Screening women with either cytology examinations or a test detecting HPV infection can prevent cervical cancer. HPV tests are substituting cytology examinations in cervical cancer screening, but more knowledge is needed about the screening performance of HPV tests, especially among younger women. We aimed to determine the long-term performance of a five-type HPV mRNA test to predict CIN3+. These results contribute to the knowledge of the reliability of HPV mRNA testing in cervical cancer screening. Our findings suggest that women with a negative result may extend the screening interval up to 10 years. Background: The study's purpose was to evaluate the performance of a five-type HPV mRNA test to predict cervical intraepithelial neoplasia grade 3 or worse (CIN3+) during up to 12 years of follow-up. Methods: Overall, 19,153 women were recruited by gynecologists and general practitioners in different parts of Norway between 2003 and 2004. The study population comprised 9582 women of these women, aged 25–69 years with normal cytology and a valid five-type HPV mRNA test at baseline. Follow-up for CIN3+ through 2015 was conducted in the Norwegian Cervical Cancer Screening Programme. Results: The cumulative incidence of CIN3+ by baseline status for HPV mRNA-positive and mRNA-negative women were 20.8% and 1.1%, respectively (p < 0.001). Age did not affect the long-term ability of the HPV mRNA test to predict CIN3+ during follow-up. Conclusion: The low long-term risk of CIN3+ among HPV mRNA-negative women and the high long-term risk among HPV mRNA-positive women strengthen the evidence that the five-type HPV mRNA test is an appropriate screening test for women of all ages. Our findings suggest that women with a negative result may extend the screening interval up to 10 years. [ABSTRACT FROM AUTHOR]

Aims: Atrial fibrillation (AF) is becoming increasingly common. Traditional cardiovascular risk factors (CVRF) do not explain all AF cases. Blood‐based biomarkers reflecting cardiac injury such as high‐sensitivity troponin I (hsTnI) may help close this gap. Methods: We investigated the predictive ability of hsTnI for incident AF in 45,298 participants (median age 51.4 years, 45.0% men) across European community cohorts in comparison to CVRF and established biomarkers (C‐reactive protein, N‐terminal pro B‐type natriuretic peptide). Results: During a median follow‐up of 7.7 years, 1734 (3.8%) participants developed AF. Those in the highest hsTnI quarter (≥4.2 ng/L) had a 3.91‐fold (95% confidence interval (CI) 3.30, 4.63; p <.01) risk for developing AF compared to the lowest quarter (<1.4 ng/L). In multivariable‐adjusted Cox proportional hazards models a statistically significant association was seen between hsTnI and AF (hazard ratio (HR) per 1 standard deviation (SD) increase in log10(hsTnI) 1.08; 95% CI 1.01, 1.16; p =.03). Inclusion of hsTnI did improve model discrimination (C‐index CVRF 0.811 vs. C‐index CVRF and hsTnI 0.813; p <.01). Higher hsTnI concentrations were associated with heart failure (HR per SD 1.37; 95% CI 1.12, 1.68; p <.01) and overall mortality (HR per SD 1.24; 95% CI 1.09, 1.41; p <.01). Conclusion: hsTnI as a biomarker of myocardial injury does not improve prediction of AF incidence beyond classical CVRF and NT‐proBNP. However, it is associated with the AF‐related disease heart failure and mortality likely reflecting underlying subclinical cardiovascular impairment. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) methods have become important for enhancing the performance of decision-support predictive models. However, class imbalance is one of the main challenges for developing ML models, because it may bias the learning process and the model generalization ability. In this paper, we consider oversampling methods for generating synthetic categorical clinical data aiming to improve the predictive performance in ML models, and the identification of risk factors for cardiovascular diseases (CVDs). We performed a comparative study of several categorical synthetic data generation methods, including Synthetic Minority Oversampling Technique Nominal (SMOTEN), Tabular Variational Autoencoder (TVAE) and Conditional Tabular Generative Adversarial Networks (CTGANs). Then, we assessed the impact of combining oversampling strategies and linear and nonlinear supervised ML methods. Lastly, we conducted a post-hoc model interpretability based on the importance of the risk factors. Experimental results show the potential of GAN-based models for generating high-quality categorical synthetic data, yielding probability mass functions that are very close to those provided by real data, maintaining relevant insights, and contributing to increasing the predictive performance. The GAN-based model and a linear classifier outperform other oversampling techniques, improving the area under the curve by 2%. These results demonstrate the capability of synthetic data to help with both determining risk factors and building models for CVD prediction. [ABSTRACT FROM AUTHOR]

Aims To identify robust circulating predictors for incident atrial fibrillation (AF) using classical regressions and machine learning (ML) techniques within a broad spectrum of candidate variables. Methods and results In pooled European community cohorts (n = 42 280 individuals), 14 routinely available biomarkers mirroring distinct pathophysiological pathways including lipids, inflammation, renal, and myocardium-specific markers (N-terminal pro B-type natriuretic peptide [NT-proBNP], high-sensitivity troponin I [hsTnI]) were examined in relation to incident AF using Cox regressions and distinct ML methods. Of 42 280 individuals (21 843 women [51.7%]; median [interquartile range, IQR] age, 52.2 [42.7, 62.0] years), 1496 (3.5%) developed AF during a median follow-up time of 5.7 years. In multivariable-adjusted Cox-regression analysis, NT-proBNP was the strongest circulating predictor of incident AF [hazard ratio (HR) per standard deviation (SD), 1.93 (95% CI, 1.82–2.04); P < 0.001]. Further, hsTnI [HR per SD, 1.18 (95% CI, 1.13–1.22); P < 0.001], cystatin C [HR per SD, 1.16 (95% CI, 1.10–1.23); P < 0.001], and C-reactive protein [HR per SD, 1.08 (95% CI, 1.02–1.14); P = 0.012] correlated positively with incident AF. Applying various ML techniques, a high inter-method consistency of selected candidate variables was observed. NT-proBNP was identified as the blood-based marker with the highest predictive value for incident AF. Relevant clinical predictors were age, the use of antihypertensive medication, and body mass index. Conclusion Using different variable selection procedures including ML methods, NT-proBNP consistently remained the strongest blood-based predictor of incident AF and ranked before classical cardiovascular risk factors. The clinical benefit of these findings for identifying at-risk individuals for targeted AF screening needs to be elucidated and tested prospectively. [ABSTRACT FROM AUTHOR]