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(1) Background: Predicting chronic low back pain (LBP) is of clinical and economic interest as LBP leads to disabilities and health service utilization. This study aims to build a competitive and interpretable prediction model; (2) Methods: We used clinical and claims data of 3837 participants of a population-based cohort study to predict future LBP consultations (ICD-10: M40.XX-M54.XX). Best subset selection (BSS) was applied in repeated random samples of training data (75% of data); scoring rules were used to identify the best subset of predictors. The rediction accuracy of BSS was compared to randomforest and support vector machines (SVM) in the validation data (25% of data); (3) Results: The best subset comprised 16 out of 32 predictors. Previous occurrence of LBP increased the odds for future LBP consultations (odds ratio (OR) 6.91 [5.05; 9.45]), while concomitant diseases reduced the odds (1 vs. 0, OR: 0.74 [0.57; 0.98], >1 vs. 0: 0.37 [0.21; 0.67]). The area-under-curve (AUC) of BSS was acceptable (0.78 [0.74; 0.82]) and comparable with SVM (0.78 [0.74; 0.82]) and randomforest (0.79 [0.75; 0.83]); (4) Conclusions: Regarding prediction accuracy, BSS has been considered competitive with established machine-learning approaches. Nonetheless, considerable misclassification is inherent and further refinements are required to improve predictions.
Extinction learning is suggested to be a central mechanism during exposure-based cognitive behavioralpsychotherapy. A positive association between the patients’pretreatment extinction learning performance andtreatment outcome would corroborate the hypothesis. Indeed, there isfirst correlational evidence between reducedextinction learning and therapy efficacy. However, the results of these association studies may be hampered byextinction-training protocols that do not match treatment procedures. Therefore, we developed an extinction-trainingprotocol highly tailored to the procedure of exposure therapy and tested it in two samples of 46 subjects in total. Byusing instructed fear acquisition training, including a consolidation period overnight, we wanted to ensure that theconditioned fear response was well established prior to extinction training, which is the case in patients with anxietydisorders prior to treatment. Moreover, the extinction learning process was analyzed on multiple response levels,comprising unconditioned stimulus (US) expectancy ratings, autonomic responses, defensive brain stem reflexes, andneural activation using functional magnetic resonance imaging. Using this protocol, we found robust fearconditioning and slow-speed extinction learning. We also observed within-group heterogeneity in extinction learning,albeit a stable fear response at the beginning of the extinction training. Finally, we found discordance betweendifferent response systems, suggesting that multiple processes are involved in extinction learning. The paradigmpresented here might help to ameliorate the association between extinction learning performance assessed in thelaboratory and therapy outcomes and thus facilitate translational science in anxiety disorders
In 2009, the Democratic Republic of Congo (DRC) started its journey towards achieving Universal Health Coverage (UHC). This study examines the evolution of financial risk protection and health outcomes indicators in the context of the commitment of DRC to UHC. To measure the effects of such a commitment on financial risk protection and health outcomes indicators, we analyse whether changes have occurred over the last two decades and, if applicable, when these changes happened. Using five variables as indicators for the measurement of the financial risk protection component, there as well retained three indicators to measure health outcomes. To identify time-related effects, we applied the parametric approach of breakpoint regression to detect whether the UHC journey has brought change and when exactly the change has occurred.
Although there is a slight improvement in the financial risk protection indicators, we found that the adopted strategies have fostered access to healthcare for the wealthiest quantile of the population while neglecting the majority of the poorest. The government did not thrive persistently over the past decade to meet its commitment to allocate adequate funds to health expenditures. In addition, the support from donors appears to be unstable, unpredictable and unsustainable. We found a slight improvement in health outcomes attributable to direct investment in building health centres by the private sector and international organizations. Overall, our findings reveal that the prevention of catastrophic health expenditure is still not sufficiently prioritized by the country, and mostly for the majority of the poorest. Therefore, our work suggests that DRC’s UHC journey has slightly contributed to improve the financial risk protection and health outcomes indicators but much effort should be undertaken.
Variability of Thyroid Measurements from Ultrasound and Laboratory in a Repeated Measurements Study
(2020)
Background: Variability of measurements in medical research can be due to different sources. Quantification of measurement errors facilitates probabilistic sensitivity analyses in future research to minimize potential bias in epidemiological studies. We aimed to investigate the variation of thyroid-related outcomes derived from ultrasound (US) and laboratory analyses in a repeated measurements study. Subjects and Methods: Twenty-five volunteers (13 females, 12 males) aged 22–70 years were examined once a month over 1 year. US measurements included thyroid volume, goiter, and thyroid nodules. Laboratory measurements included urinary iodine concentrations and serum levels of thyroid-stimulating hormone (TSH), free triiodothyronine (fT3), free thyroxine (fT4), and thyroglobulin. Variations in continuous thyroid markers were assessed as coefficient of variation (CV) defined as mean of the individual CVs with bootstrapped confidence intervals and as intraclass correlation coefficients (ICCs). Variations in dichotomous thyroid markers were assessed by Cohen’s kappa. Results: CV was highest for urinary iodine concentrations (56.9%), followed by TSH (27.2%), thyroglobulin (18.2%), thyroid volume (10.5%), fT3 (8.1%), and fT4 (6.3%). The ICC was lowest for urinary iodine concentrations (0.42), followed by fT3 (0.55), TSH (0.64), fT4 (0.72), thyroid volume (0.87), and thyroglobulin (0.90). Cohen’s kappa values for the presence of goiter or thyroid nodules were 0.64 and 0.70, respectively. Conclusion: Our study provides measures of variation for thyroid outcomes, which can be used for probabilistic sensitivity analyses of epidemiological data. The low intraindividual variation of serum thyroglobulin in comparison to urinary iodine concentrations emphasizes the potential of thyroglobulin as marker for the iodine status of populations.