Despite the growing interest in precision medicine-based therapies for Alzheimer\'s disease (AD), little research has been conducted on how individual AD risk factors influence changes in cognitive function following transcranial direct current stimulation (tDCS). This study evaluates the cognitive effects of sequential tDCS on 63 mild cognitive impairment (MCI) patients, considering AD risk factors such as amyloid-beta deposition, APOE ε4, BDNF polymorphism, and sex. Using both frequentist and Bayesian methods, we assessed the interaction of tDCS with these risk factors on cognitive performance. Notably, we found that amyloid-beta deposition significantly interacted with tDCS in improving executive function, specifically Stroop Word-Color scores, with strong Bayesian support for this finding. Memory enhancements were differentially influenced by BDNF Met carrier status. However, sex and APOE ε4 status did not show significant effects. Our results highlight the importance of individual AD risk factors in modulating cognitive outcomes from tDCS, suggesting that precision medicine may offer more effective tDCS treatments tailored to individual risk profiles in early AD stages.

UNASSIGNED: Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in the state of Paraná (Brazil), using spatial analysis to identify areas with higher risk based on socioeconomic, demographic and health variables.
UNASSIGNED: This is an ecological study based on secondary and retrospective IHD hospitalization and mortality data obtained from the Brazilian Hospitalization and Mortality Information Systems during the 2010-2021 period. Data were analyzed for 399 municipalities and 22 health regions in the state of Paraná. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software.
UNASSIGNED: A total of 333,229 hospitalizations and 73,221 deaths occurred in the analyzed period, and elevated RR of hospitalization (RR = 27.412, CI 21.801; 34.466) and mortality (RR = 15.673, CI 2.148; 114.319) from IHD occurred in small-sized municipalities. In addition, medium-sized municipalities also presented elevated RR of hospitalization (RR = 6.533, CI 1.748; 2.006) and mortality (RR = 6.092, CI 1.451; 2.163) from IHD. Hospitalization and mortality rates were higher in white men aged 40-59 years. A negative association was found between Municipal Performance Index (IPDM) and IHD hospitalization and mortality.
UNASSIGNED: Areas with increased risk of hospitalization and mortality from IHD were found in small and medium-sized municipalities in the state of Paraná, Brazil. These results suggest a deficit in health care attention for IHD cases in these areas, potentially due to a low distribution of health care resources.

BACKGROUND: Frailty is a multifactorial syndrome; through this study, we aimed to investigate the physiological, psychological, and social factors associated with frailty and frailty worsening in community-dwelling older adults.
METHODS: We conducted a cross-sectional and longitudinal study using data from the \"Community Empowerment and Well-Being and Healthy Long-term Care: Evidence from a Cohort Study (CEC),\" which focuses on community dwellers aged 65 and above in Japan. The sample of the cross-sectional study was drawn from a CEC study conducted in 2014 with a total of 673 participants. After excluding those who were frail during the baseline assessment (2014) and at the 3-year follow-up (2017), the study included 373 participants. Frailty assessment was extracted from the Kihon Checklist, while social relationships were assessed using the Social Interaction Index (ISI). Variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression and their predictive abilities were tested. Factors associated with frailty status and worsening were identified through the Maximum-min Hillclimb algorithm applied to Bayesian networks (BNs).
RESULTS: At baseline, 14.1% (95 out of 673) participants were frail, and 24.1% (90 out of 373) participants experienced frailty worsening at the 3-years follow up. LASSO regression identified key variables for frailty. For frailty identification (cross-sectional), the LASSO model\'s AUC was 0.943 (95%CI 0.913-0.974), indicating good discrimination, with Hosmer-Lemeshow (H-L) test p = 0.395. For frailty worsening (longitudinal), the LASSO model\'s AUC was 0.722 (95%CI 0.656-0.788), indicating moderate discrimination, with H-L test p = 0.26. The BNs found that age, multimorbidity, function status, and social relationships were parent nodes directly related to frailty. It revealed an 85% probability of frailty in individuals aged 75 or older with physical dysfunction, polypharmacy, and low ISI scores; however, if their social relationships and polypharmacy status improve, the probability reduces to 50.0%. In the longitudinal-level frailty worsening model, a 75% probability of frailty worsening in individuals aged 75 or older with declined physical function and ISI scores was noted; however, if physical function and ISI improve, the probability decreases to 25.0%.
CONCLUSIONS: Frailty and its progression are prevalent among community-dwelling older adults and are influenced by various factors, including age, physical function, and social relationships. BNs facilitate the identification of interrelationships among these variables, quantify the influence of key factors. However, further research is required to validate the proposed model.

OBJECTIVE: This study aimed to summarize validity estimates of International Classification of Diseases (ICD) codes in identifying opioid overdose (OOD) among patient data from emergency rooms, emergency medical services, inpatient, outpatient, administrative, medical claims, and mortality, and estimate the sensitivity and specificity of the algorithms in the absence of a perfect reference standard.
METHODS: We systematically reviewed studies published before December 8, 2023, and identified with Medline and Embase. Studies reporting sufficient details to recreate a 2 × 2 table comparing the ICD algorithms to a reference standard in diagnosing OOD-related events were included. We used Bayesian latent class models (BLCM) to estimate the posterior sensitivity and specificity distributions of five ICD-10 algorithms and of the imperfect coroner\'s report review (CRR) in detecting prescription opioid-related deaths (POD) using one included study.
RESULTS: Of a total of 1990 studies reviewed, three were included. The reported sensitivity estimates of ICD algorithms for OOD were low (range from 25.0% to 56.8%) for ICD-9 in diagnosing non-fatal OOD-related events and moderate (72% to 89%) for ICD-10 in diagnosing POD. The last included study used ICD-9 for non-fatal and fatal and ICD-10 for fatal OOD-related events and showed high sensitivity (i.e. above 97%). The specificity estimates of ICD algorithms were good to excellent in the three included studies. The misclassification-adjusted ICD-10 algorithm sensitivity estimates for POD from BLCM were consistently higher than reported sensitivity estimates that assumed CRR was perfect.
CONCLUSIONS: Evidence on the performance of ICD algorithms in detecting OOD events is scarce, and the absence of bias correction for imperfect tests leads to an underestimation of the sensitivity of ICD code estimates.
RéSUMé: OBJECTIFS: Cette étude avait pour objectifs de recenser les estimations de la validité des codes de Classification Internationale des Maladies (CIM) à diagnostiquer les cas de surdose aux opioïdes (SDO) chez des patients en utilisant les données de salles d’urgence, services médicaux d’urgence, hospitalisations, soins ambulatoires, services administratifs, demandes de remboursement de frais médicaux, ainsi que de mortalité, et d’estimer la sensibilité et la spécificité d’algorithmes utilisant la CIM en l’absence d’un test de référence parfait. MéTHODES: Nous avons examiné systématiquement les études publiées avant le 8 décembre 2023, et identifiées dans Medline et Embase. Les études rapportant suffisamment de détails permettant de recréer un tableau 2 × 2 comparant les algorithmes de la CIM à un test de référence pour le diagnostic d’événements liés aux SDO ont été incluses. Les données d’une étude éligible ont été utilisées pour estimer, avec des modèles Bayésiens de classes latentes (MBCL), les distributions a posteriori de la sensibilité et de la spécificité de cinq algorithmes de la CIM-10 et du test imparfait de révision du rapport du coroner (RRC) dans la détection des décès liés aux opioïdes de prescription (DOP). RéSULTATS: Trois parmi les 1 990 études examinées ont été retenues. Les estimations rapportées de la sensibilité des codes CIM étaient faibles (variant de 25,0 % à 56,8 %) pour CIM-9 dans le diagnostic des événements liés aux SDO non-fatales dans une étude, et modérées (72 % à 89 %) pour CIM-10 dans le diagnostic des DOP dans une autre étude. La dernière étude incluse combinait des codes CIM-9 pour les cas non-fatals et fatals et CIM-10 pour les cas fatals et démontrait des estimations de sensibilité élevées (c.à.d. supérieures à 97 %). Les estimations de la spécificité étaient bonnes à excellentes dans les trois études. Les estimations de la sensibilité des algorithmes de la CIM-10 corrigées pour les erreurs de classification pour les décès liés aux opioïdes, obtenues à partir de nos MBCL, étaient systématiquement plus élevées que celles rapportées et qui supposaient que RRC était un test parfait. CONCLUSION: Les évidences sur la performance des algorithmes de la CIM dans la détection des cas de SDO sont rares, et l’absence de correction de biais pour des tests diagnostiques imparfaits conduit à une sous-estimation de la sensibilité des codes de la CIM.

The sweet chestnut (Castanea sativa Mill.) is subject to the progressive disappearance of its traditional chestnut groves. In the northern part of Italy, where distribution of the sweet chestnut is fragmented, many local varieties continue to be identified mostly by oral tradition. We characterised by SSRs eleven historically recognised varieties of sweet chestnut in the area surrounding Lake Como, with the goal of giving a genetic basis to the traditional classification. We performed classical analysis about differentiation and used Bayesian approaches to detect population structure and to reconstruct demography. The results revealed that historical and genetic classifications are loosely linked when chestnut fruits are just \"castagne\", that is, normal fruits, but increasingly overlap where \"marroni\" (the most prized fruits) are concerned. Bayesian classification allowed us to identify a homogeneous gene cluster not recognised in the traditional assessment of the varieties and to reconstruct possible routes used for the propagation of sweet chestnut. We also reconstructed ancestral relationships between the different gene pools involved and dated ancestral lineages whose results fit with palynological data. We suggest that conservation strategies based on a genetic evaluation of the resource should also rely on traditional cultural heritage, which could reveal new sources of germplasm.

When investigating unobservable, complex traits, data collection and aggregation processes can introduce distinctive features to the data such as boundedness, measurement error, clustering, outliers, and heteroscedasticity. Failure to collectively address these features can result in statistical challenges that prevent the investigation of hypotheses regarding these traits. This study aimed to demonstrate the efficacy of the Bayesian beta-proportion generalized linear latent and mixed model (beta-proportion GLLAMM) (Rabe-Hesketh et al., Psychometrika, 69(2), 167-90, 2004a, Journal of Econometrics, 128(2), 301-23, 2004c, 2004b; Skrondal and Rabe-Hesketh 2004) in handling data features when exploring research hypotheses concerning speech intelligibility. To achieve this objective, the study reexamined data from transcriptions of spontaneous speech samples initially collected by Boonen et al. (Journal of Child Language, 50(1), 78-103, 2023). The data were aggregated into entropy scores. The research compared the prediction accuracy of the beta-proportion GLLAMM with the normal linear mixed model (LMM) (Holmes et al., 2019) and investigated its capacity to estimate a latent intelligibility from entropy scores. The study also illustrated how hypotheses concerning the impact of speaker-related factors on intelligibility can be explored with the proposed model. The beta-proportion GLLAMM was not free of challenges; its implementation required formulating assumptions about the data-generating process and knowledge of probabilistic programming languages, both central to Bayesian methods. Nevertheless, results indicated the superiority of the model in predicting empirical phenomena over the normal LMM, and its ability to quantify a latent potential intelligibility. Additionally, the proposed model facilitated the exploration of hypotheses concerning speaker-related factors and intelligibility. Ultimately, this research has implications for researchers and data analysts interested in quantitatively measuring intricate, unobservable constructs while accurately predicting the empirical phenomena.

Pediatric cancer consists of a diverse group of rare diseases. Due to limited patient populations, standard randomized and controlled trials are often infeasible. As a result, single-arm trials are common in pediatric oncology and the use of external controls is often desirable or necessary to help generate actionable evidence and contextualize trial results. In this paper, we illustrate unique features in pediatric oncology clinical trials and describe their impact on the use of external controls. Various types of relevant external control data sources are described in terms of their utility and drawbacks. Statistical methodologies and design implications with external control are discussed. Two recent case studies using external controls to support pediatric oncology drug development are described in detail.

A large-scale study was carried out in the Polish goat population in 2014-2021 to determine the herd-level true seroprevalence (HTP) of caseous lymphadenitis (CLA) caused by Corynebacterium pseudotuberculosis (Cp) and paratuberculosis (PTB) caused by Mycobacterium avium ssp. paratuberculosis (Map). Two-stage cluster sampling was applied to herds counting at least 20 adult goats (aged >1 year) and in each herd all males and 10-13 females were tested. At least one seropositive goat regardless of its sex was necessary to consider the herd as infected. HTP was estimated using the Bayesian approach with the Gibbs sampler in the EpiTools and reported as the median and 95 % credibility interval (95 % CrI). A total of 1282 adult goats from 86 herds were serologically tested using two commercial ELISAs (Cp-ELISA and Map-ELISA). At least 1 seropositive result of Cp-ELISA and Map-ELISA was obtained in 73/86 herds (84.9 %) and 40/86 herds (46.5 %), respectively. HTP of CLA was estimated at 73.3 % (95 % CrI: 65.0 %, 80.4 %) and HTP of PTB was estimated at 42.9 % (95 % CrI: 25.8 %, 58.0 %). There was a significant positive association between the occurrence of CLA and PTB in the herds (odds ratio 6.0, 95 % confidence interval: 1.2, 28.8; p = 0.010). Probability of the seropositive result for PTB was also significantly higher in Cp-seropositive goats than in Cp-seronegative goats (odds ratio 3.9, 95 % confidence interval: 2.4, 6.3; p < 0.001) which could indicate either a higher risk of co-infection or a higher rate of false positive results for PTB in Cp-positive goats. To investigate this issue, optical densities obtained in Map-ELISA were compared between Cp-positive and Cp-negative goats and results of Map-ELISA were adjusted accordingly. Map-negative sera from Cp-positive goats turned out to have significantly higher optical densities than Map-negative sera from Cp-negative goats (p < 0.001). After the adjustment, the herd-level apparent seroprevalence of PTB was 41.9 % (36/86 herds) so it still fell within the 95 % CrI of HTP of PTB calculated before the adjustment. Concluding, CLA appears to be widespread in the Polish goat population. In many of them it may be subclinical at the moment, however will likely emerge in the future as the disease follows cyclic pattern in Poland. On the other hand, given the total lack of clinical PTB in Polish goats, an explanation for a high HTP of PTB remains unclear and warrants further studies using tests of higher analytical specificity than ELISA.

Extant birds stand out among vertebrates in the diversity of parental care types they present, spanning absence of care to uniparental care by either sex, biparental or even cooperative care. Despite years of research, key questions remain regarding parental care evolution in birds. Firstly, the parental care type in the most recent ancestor of extant birds is a matter of controversy, with proposed ancestral states including no care, uniparental male or female care, and biparental care. Another unsolved question is the direction, order, and frequency of transitions between parental care types. We address these key questions using a database of 5,438 bird species (~50% of extant diversity) and modern phylogenetic comparative methods controlling simultaneously for model and phylogenetic uncertainty as well as potential confounding effects of state-dependent diversification. Our results indicate that the most likely ancestral state for extant birds is male-only care, with a posterior probability of 0.8. Transition rates across parental care types were generally low and heterogenous; loss of parental care virtually never occurs and transitions away from female only or cooperative care most often lead to biparental care. Given the low transition rates, future research should analyze the factors favoring the maintenance of care types.

BACKGROUND: In the United States, leading medical societies recommend 81 mg of aspirin daily for the prevention of preeclampsia (PE) in women at risk, whereas the NICE guidelines in the UK recommend a dose as high as 150 mg of aspirin. Recent data also suggest that in the obese population, inadequate dosing or aspirin resistance may impact the efficacy of aspirin at the currently recommend doses.
OBJECTIVE: We evaluated whether daily administration of 162 mg aspirin would be more effective compared to 81 mg in decreasing the rate of PE with severe features in high-risk obese pregnant individuals.
METHODS: We performed a randomized trial between May 2019 and November 2022. Individuals at 12 to 20-weeks gestational age (GA) with a BMI ≥ 30 kg/m2 at time to enrollment, and at least one of three high risk factors: history of PE in a prior pregnancy, at least stage I hypertension documented in the index pregnancy, pre-gestational diabetes or gestational diabetes diagnosed prior to 20 weeks GA were randomized to either 162 mg or 81 mg of aspirin daily till delivery, participants were not blinded to treatment allocation. Exclusion criteria were: multifetal gestation, known major fetal anomalies, seizure disorder, baseline proteinuria, on aspirin due to other indications, or contraindication to aspirin. The primary outcome was PE with severe features (PE or superimposed PE with severe features, eclampsia, or HELLP). Secondary outcomes included rates of preterm birth due to PE, small for gestational age (SGA), postpartum hemorrhage, abruption, and medication side effects. A sample size of 220 was needed using a preplanned Bayesian analysis of the primary outcome to estimate the posterior probability of benefit or harm with a neutral informative prior.
RESULTS: Of 343 eligible individuals, 220 (64.1%) were randomized. The primary outcome was available for 209/220 (95%). Baseline characteristics were similar between groups, median gestational age at enrollment was 15.9 weeks in the 162 mg aspirin group and 15.6 weeks in the 81 mg aspirin group. Enrollment prior to 16 weeks occurred in 55/110 of those assigned to 162 mg and 58/110 of those assigned to 81 mg of aspirin. The primary outcome occurred in 35% in the 162 mg aspirin group and in 40% in the 81 mg aspirin group (posterior relative risk, 0.88; 95% credible interval, 0.64-1.22). Bayesian analysis indicated a 78% probability of a reduction in the primary outcome with 162 mg aspirin compared to 81 mg aspirin dose. Rates of indicated preterm birth due to preeclampsia (21% vs 21%), SGA (6.5% vs 2.9%), abruption (2.8% vs 3.0%) and postpartum hemorrhage (10% vs 8.8%) were similar between groups. Medication adverse effects were also similar.
CONCLUSIONS: Among high-risk obese individuals, there was 78% probability of benefit that 162 mg aspirin compared to 81 mg will decrease the rate of PE with severe features. With a best estimate of a 12% reduction when using 162 mg of aspirin in comparison to 81 mg of aspirin in this population. This trial supports doing a larger multicenter trial.