Bivariate Model Research Articles

Sex differences in symptoms following the administration of BNT162b2 mRNA COVID-19 vaccine in children below 5 years of age in Germany (CoVacU5): a retrospective cohort study

BackgroundSex differences exist not only in the efficacy but also in adverse event rates of many vaccines. Here we compared the safety of BNT162b2 vaccine administered off-label in female and male children younger than 5 years in Germany.MethodsThis is a retrospective cohort study, in which we performed a post-hoc analysis of a dataset collected through an authentication-based survey of individuals having registered children aged 0-<5 years for vaccination against SARS-CoV-2 in six private practices and/or two lay person-initiated vaccination campaigns. We analyzed the safety profiles of the first 3 doses of 3–10 µg BNT162b2. Primary outcome was comparison in frequencies of 4 common post-vaccination symptom categories such as local, general, musculoskeletal symptoms and fever. Data were analyzed according to sex in bivariate analyses and regression models adjusting for age, weight, and dosage. Interaction between sex and BNT162b2 dosage was assessed. An active-comparator analysis was applied to compare post-vaccination symptoms after BNT162b2 versus non-SARS-CoV-2 vaccines.ResultsThe dataset for the present analysis consisted of 7801 participants including 3842 females (49%) and 3977 males (51%) with an age of 3 years (median, interquartile: 2 years). Among individuals receiving 3 µg BNT162b2, no sex differences were noted, but after a first dose of 5–10 µg BNT162b2, local injection-site symptoms were more prevalent in girls compared to boys. In logistic regression, female sex was associated with higher odds of local symptoms, odds ratio (OR) of 1.33 (95% confidence interval [CI]: 1.15–1.55, p < 0.05) and general symptoms with OR 1.21 (95% CI: 1.01–1.44, p < 0.05). Following non-BNT162b2 childhood vaccinations, female sex was associated with a lower odds of post-vaccination musculoskeletal symptoms (OR: 0.29, 95% CI: 0.11–0.82, p < 0.05). An active comparator analysis between BNT162b2 and non-SARS-CoV-2 vaccinations revealed that female sex positively influenced the association between BNT162b2 vaccine type and musculoskeletal symptoms.ConclusionsSex differences exist in post-vaccination symptoms after BNT162b2 administration even in young children. These are of importance for the conception of approval studies, for post-vaccination monitoring and for future vaccination strategies (German Clinical Trials Register ID: DRKS00028759).

Diagnostic Accuracy of Neuromuscular Ultrasound vs. Electrodiagnostic Studies for Carpal Tunnel Syndrome: Systematic Review and Meta-analysis of Paired Accuracy Studies.

This systematic review with meta-analysis compared the diagnostic accuracy of neuromuscular ultrasound (NMUS) and electrodiagnostic studies (EDX) as confirmatory tests for carpal tunnel syndrome (CTS) diagnosis. We used bivariate random-effects models to estimate pooled sensitivity and specificity and generate hierarchical summary receiver-operating characteristic curves to assess diagnostic test accuracy. Nine paired accuracy studies were included, representing 1751 hands (743 clinically diagnosed CTS; 1008 without CTS) that underwent NMUS and EDX. Compared to the clinical diagnosis reference standard, the pooled sensitivity was 86.4% for NMUS and 91.6% for EDX. Pooled specificity was 79.3% for NMUS and 81.9% for EDX. The positive likelihood ratios were 4.2 and 5.1 for NMUS and EDX, respectively, and the negative likelihood ratios were 0.17 and 0.10, respectively. The diagnostic odds ratio was 24 for NMUS and 49 for EDX. No statistically significant differences were identified between NMUS and EDX for sensitivity, specificity, or overall diagnostic accuracy. Overall, the diagnostic accuracy of NMUS is similar to that of EDX for CTS diagnosis, with high sensitivity and moderate specificity for each. The choice between these confirmatory diagnostic tests should incorporate shared decision-making between patients and providers that weighs diagnostic accuracy as well as factors such as patient preferences, test availability, cost, and tolerability.

Recurrent Ischemic Stroke and Transient Ischemic Attack: Risk of Single and Multiple Recurrence.

Background/Objectives: Efforts have been made toward primary or secondary stroke or transient ischemic attack (TIA) prevention. However, little attention has been paid to recurrent stroke or TIA. This study investigated risk factors for multiple or single recurrent stroke or TIA. Methods: Data from 3646 patients with ischemic stroke or TIA were obtained from the Korea University Ansan Hospital Stroke Center between March 2014 and December 2021, using the prospective institutional database of the Korea University Stroke Registry. The associations between clinical features and recurrent stroke or TIA were assessed using bivariable and multivariable Cox models. Results: Recurrent stroke or TIA was associated with male sex (adjusted hazard ratio (HR) 1.95, 95% confidence interval (CI) 1.42-2.80), hypertension (HR 1.49, 95% CI 1.00-2.23), diabetes mellitus (HR 1.54, 95% CI 1.13-2.13), an etiologic subtype of transient ischemic attack (HR 1.88, 95% CI 1.09-3.16), white matter changes (HR 1.62, 95% CI 1.05-2.38), and cerebral microbleeds (HR 1.79, 95% CI 1.26-2.59). Multiple recurrent stroke or TIA was associated with male sex (HR 3.86, 95% CI 1.94-11.55), diabetes mellitus (HR 2.40, 95% CI 1.31-4.53), and anemia (HR 4,58, 95% CI 2.31-10.44). Conclusions: Given the risk factor profiles for recurrent stroke or TIA, risks differed among patient subgroups and were based on multiple or single recurrences. It may exert an effect as a prognostic indicator in the high risk of recurrences.

Genetic Parameter Estimates for Growth of Hāpuku (Groper, Polyprion oxygeneios) in Land-Based Aquaculture Using Random Regression Models

Hāpuku (Polyprion oxygeneios) is a promising candidate for aquaculture production in New Zealand. Methods for spawning, juvenile production, and growout to harvest entirely on land, where water quality, pathogens, environmental impacts, and genetic “pollution” can be tightly controlled, have been developed, and genetic improvement to optimise land-based production is the obvious next step. However, estimates of genetic parameters are required to design a rigorous, disciplined, and effective selective breeding program. By using existing data consisting of irregularly spaced repeated measurements of fork length and live body weight collected on wild-collected founders and two generations of captively reared progeny, we evaluated the species’ genetic potential for improvement in growth. We first tested a range of univariate random regression models to identify the best-fitting models for these data. Subsequently, using a bivariate model, we estimated variance components for growth trajectories of fork length and whole body weight. With one to six records available per fish, the best-fitting univariate models included only a fixed effect for contemporary groups and fixed and random genetic third-order Legendre polynomials. More complex models that included full-sib family and/or permanent environmental effects produced unacceptable constrained and/or non-positive-definite solutions. Both traits are moderately heritable at all stages of the growout phase (~0.4–0.5), and the genetic correlation patterns between daily breeding values estimated via the covariance function are different for length and weight. Genetic correlations for length between all pairs of age-specific breeding values are positive and strong (&gt;0.7) and change gradually and smoothly with increasing temporal separation. For weight, these correlations deteriorate more rapidly with increasing time lags between measurements and become negative for some age pairings. We conclude that random regression analyses are a valuable tool for extracting genetic information from irregularly spaced repeated measurements of fish size, speculate that emerging technologies for high-throughput genotyping and phenotyping will add to the value of this approach in the near future, and reason that a breeding strategy that rigorously takes into account the potentially unfavourable genetic correlations between breeding values for weight at some ages will further adapt hāpuku to land-based systems and enhance the profitability commercial-scale production.

Syphilis among HIV-positive men who have sex with men in Ghana: The 2023 biobehavioral survey.

Apart from HIV acquisition, men who have sex with men are at a higher risk of sexually transmitted infections, especially syphilis. Although the intersection between syphilis and HIV poses a formidable challenge among key populations who are known to be vulnerable to many health threats, there is little known about syphilis infection among MSM living with HIV in Ghana. This study seeks to investigate the burden of syphilis and address the existing knowledge gap by exploring behavioral, healthcare access, and structural factors influencing the syphilis burden within the HIV-positive MSM population. This study was conducted in 2023 as part of the bio-behavioral survey (BBS) among men who have sex with men (MSM) in Ghana. A cross-sectional survey that used a respondent-driven sampling (RDS) approach was conducted in the old ten regions of Ghana. Data was collected on 3,420 participants, however, 857 HIV-positive MSM were included in this study since it focused on syphilis among HIV-positive MSM in Ghana. The study estimated the prevalence of syphilis among MSM living with HIV and provided a 95% confidence interval across different categories of explanatory variables. Bivariate and multivariable logistic regression models were used to identify factors associated with overall syphilis prevalence. All other analyses were weighted due to the complex design of the study. The overall prevalence of syphilis was 23.83% (95% CI: 20.44, 27.58). HIV-positive men who only had sex with men had a 29.77% (95% CI: 23.90, 36.40) prevalence of syphilis compared to a prevalence of 9.50% (95% CI: 2.56, 29.53) recorded by HIV-positive MSM who were attracted to mostly females. Participants who ever had receptive anal sex recorded a higher prevalence 26.79% (95% CI: 22.78, 31.23) than those who never had receptive anal sex 12.86% (95% CI: 8.02, 19.99). The odds of syphilis among HIV-positive MSM who never used condoms with regular sex partners in the last 6 months were 41.08 (aOR: 41.08 at 95% CI 1.24-136.42; p = 0.038). There is a high prevalence of syphilis among HIV-positive men who have sex with men in Ghana, especially among those who engage in unprotected anal sex and have multiple sexual partners. Our findings underscore the dire need for targeted interventions to address the dual brunt of HIV and syphilis among the MSM population in Ghana.

Head-to-Head Comparison of the Diagnostic Performance of FDG PET/CT and FDG PET/MRI in Patients With Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND. The available evidence on the use of FDG PET/MRI performed using an integrated system in patients with cancer has grown substantially. OBJECTIVE. The purpose of this study was to perform a systematic review and meta-analysis comparing the diagnostic performance of FDG PET/CT and FDG PET/MRI in patients with cancer. EVIDENCE ACQUISITION. MEDLINE, Embase, and the Cochrane Database of Systematic Reviews were searched for studies reporting a head-to-head comparison of the diagnostic performance of FDG PET/CT and FDG PET/MRI in patients with cancer from July 1, 2015, to January 25, 2023. The two modalities' diagnostic performance was summarized, stratified by performance end point. For end points with sufficient data, a meta-analysis was performed using bivariate modeling to produce summary estimates of pooled sensitivity and specificity. For the remaining end points, reported performance in individual studies was recorded. EVIDENCE SYNTHESIS. The systematic review included 29 studies with a total of 1656 patients. For patient-level detection of regional nodal metastases (five studies), pooled sensitivity and specificity for PET/MRI were 88% (95% CI, 74-95%) and 92% (95% CI, 71-98%), respectively, and for PET/CT were 86% (95% CI, 70-94%) and 86% (95% CI, 68-95%). For lesion-level detection of recurrence and/or metastases (five studies), pooled sensitivity and specificity for PET/MRI were 94% (95% CI, 78-99%) and 83% (95% CI, 76-88%), respectively, and for PET/CT were 91% (95% CI, 77-96%) and 81% (95% CI, 72-88%). In individual studies not included in the meta-analysis, PET/MRI in comparison with PET/CT showed staging accuracy in breast cancer of 98.0% versus 74.5% and in colorectal cancer of 96.2% versus 69.2%; sensitivity for primary tumor detection in cervical cancer of 93.2% versus 66.2%; and sensitivity, specificity, and accuracy for lesion-level liver metastasis detection of 91.1-98.0% versus 42.3-71.1%, 100.0% versus 83.3-98.6%, and 96.5-98.2% versus 44.7-86.7%, respectively. In three studies, management was more commonly impacted by information from PET/MRI (5.2-11.1%) than PET/CT (0.0-2.6%). CONCLUSION. PET/MRI showed comparable or superior diagnostic performance versus PET/CT across a range of cancers and end points. CLINICAL IMPACT. The findings help to identify clinical settings where PET/MRI may provide clinical benefit for oncologic evaluation. TRIAL REGISTRATION. Prospective Register of Systematic Reviews CRD42023433857.

Genetic Insights into Externalizing and Internalizing Traits through Integration of the Research Domain Criteria and Hierarchical Taxonomy of Psychopathology.

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and potential health impacts, and for informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP). We conducted a multivariate genome-wide association study (GWAS) of EXT and INT psychopathology by applying genomic structural equation modeling to summary statistics from 16 EXT and INT traits in European-ancestry individuals (n = 16,400 to 1,074,629). Downstream analyses explored associations across RDoC units of analysis (i.e., genes, molecules, cells, circuits, physiology, and behaviors). The GWAS identified 409 lead single nucleotide polymorphisms (SNPs) for EXT, 85 for INT, and 256 for EXT+INT (i.e., shared) traits. Bivariate causal mixture models estimated that nearly all EXT and INT causal variants overlapped, despite a genetic correlation of 0.37 (SE = 0.02). Drug repurposing analyses identified potential therapeutic targets, including perturbagens affecting dopamine and serotonin pathways. EXT genes had enriched expression in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT+INT liability was associated with reduced grey matter volumes in the amygdala and subcallosal cortex. These findings reveal both genetic overlap and distinct molecular and neurobiological pathways underlying EXT and INT psychopathology. By integrating genomic insights with the RDoC and HiTOP frameworks, this study advances our understanding of the mechanisms driving these dimensions of psychopathology.

Bridging Prenatal Diagnostics and AI: A Systematic Review and Meta-Analysis of the Efficacy of Advanced Algorithms in Identifying Congenital Fetal Abnormalities

Congenital fetal abnormalities have emerged as a major cause of infant mortality globally. About 3% of pregnancies are reported as fetal structural anomaly through ultrasound, ranging from minor defect to severe organ system anomalies. Our study aimed to evaluate effectiveness of Artificial intelligence (AI) algorithms in prediction of fetal heart and brain abnormalities by using meta-analysis approach. In this study, the “Reporting Items for Systematic Review and Meta-Analysis (PRISMA)" guidelines were applied for screening and selection of research articles. We searched the research articles according to research aims from Google scholar, PubMed, and Ovid MEDLINE. The data search was limited to January 2015 to May 2024. Two researchers independently screened the studies to detect research aim oriented studies. After screening of titles, those researchers assessed all abstract for eligibility. The risk bias of included studies was assessed by two researchers who used Cochrane library tool (version 5.4.0). Using the DerSimonian-Laird technique, a bivariate random effect model that generated SROC plots, we pooled test estimates. This method is particularly helpful in visualizing variability in the sensitivity and specificity across studies, accounting for the heterogeneity. This improves the reliability of the SROC plot, offering a clear summary of diagnostic performance Using the software RevMan 5.4, we carried out every statistical analysis, particularly heterogeneity through the Q test. About 243,456 screened fetus or pregnant women of 11-32 gestational weeks through 10 studies based on AI algorithms (machine learning, deep learning and AI diagnostic tool). The imaging protocols including ultrasound and MRI were used to take visuals of fetal brain and heart abnormalities in all of including studies. DL and ML algorithms provided high-performance diagnostic predictions, mostly include CNN models that assist in providing accurate diagnostic results with high sensitivity and specificity. The AI algorithm model showed a generally good accuracy scores for detection of brain and heart abnormalities and reference machine learning findings, with sensitivity ranging from 82 to 99% and specificity from 78 to 99%. Fig. 5's area under the SROC curve was 0.960. In contrast to the general detection, ML and DL seems to be more sensitive in diagnosing fetal brain and heart abnormalities. Our study provided the scientific evidence that AI models including deep learning and Machine learning are effective in generating highly reliable detection or classification results for diagnosis of fetal brain and heart anomalies. These strategies can help in reducing infant mortalities, improving treatment outcomes, and postpartum outcomes among women.

Identification of novel genomic loci for anxiety symptoms and extensive genetic overlap with psychiatric disorders.

Anxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders. We included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders. Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k-11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MD , BIP , SCZ , ADHD , and ASD . Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci. Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.

Why does perceived parenting in adolescence predict maladaptive personality in adulthood? Evidence for substantial genetic mediation.

Why is parenting in adolescence predictive of maladaptive personality in adulthood? This study sets out to investigate environmental and genetic factors underlying the association between parenting and maladaptive personality longitudinally in a large sample of twins. The present study addressed this question via a longitudinal study focused on two cohorts of twins assessed on aspects of perceived parenting (parent- and adolescent-reported) at age 14 years (n =1,094 pairs). Participants were followed to adulthood, and maladaptive personality traits were self-reported using the Personality Inventory for DSM-5 (PID-5) at age 24 or 34 years. We then modeled these data using a bivariate biometric model, decomposing parenting-maladaptive personality associations into additive genetic, shared environmental, and nonshared environmental factors. Numerous domains of adolescent-reported parenting predicted adult maladaptive personality. Further, we found evidence for substantial additive genetic (r a ranging from 0.22 to 0.55) and (to a lesser extent) nonshared environmental factors (r e ranging from 0.10 to 0.15) that accounted for the association between perceived parenting reported in adolescence and adult personality. Perceived parenting in adolescence and maladaptive personality in adulthood may be related due to some of the same genetic factors contributing to both phenotypes at different developmental periods.

The quality of home-based primary care delivered by nurse practitioners: A national Medicare claims analysis.

As the US population ages, there is an increasing demand for home-based primary care (HBPC) by those with Alzheimer's/dementia, multiple chronic conditions, severe physical limitations, or those facing end-of life. Nurse practitioners (NPs) are increasingly providing HBPC, yet little is known about their quality of care in this unique setting. This observational study uses Medicare claims data from 2018 to assess the quality of care for high-intensity HBPC users (5 or more visits/year) based on provider type (NP-only, physician (MD)-only, or both NP and MDs). We employ 12 quality measures from 3 care domains: access and prevention, acute care utilization, and end-of-life. Analysis includes bivariate comparisons and logistic regression models that adjust for demographic, clinical, and geographic characteristics. Among the 574,567 beneficiaries with 5 or more HBPC visits, 37% saw an NP, 37% saw a MD, and 27% saw both NPs and MDs. In multivariate models, those receiving HBPC from an NP or both NP-MD are significantly more likely to receive a flu shot than the MD-only group, but less likely to access preventive care. NP-only care is associated with more acute care hospitalizations, avoidable ED visits, and fall-related injuries, but significantly fewer avoidable admissions. For end-of-life care, those with NP-only or both NP-MD care are significantly more likely to have an advanced directive, be in hospice in the last 3 days of life, and more likely to die in hospice. The NP group is also more likely to die in the next year. HBPC patients are complex, with both palliative and curative needs. NPs provide almost half of HBPC in the Medicare program, to patients who are possibly sicker than those treated by physicians, with similar quality to MDs.

Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis.

Recent advances in multivariate pattern recognition have fostered the search for reliable neuroimaging-based biomarkers in psychiatric conditions, including schizophrenia. These approaches consider the complex pattern of alterations in brain function and structure, overcoming the limitations of traditional univariate methods. To assess the reliability of neuroimaging-based biomarkers and the contribution of study characteristics in distinguishing individuals with schizophrenia spectrum disorder (SSD) from healthy controls (HCs), we conducted a systematic review of the studies that used multivariate pattern recognition for this objective. We systematically searched PubMed, Scopus, and Web of Science for studies on SSD classification using multivariate pattern analysis on magnetic resonance imaging data. We employed a bivariate random-effects meta-analytic model to explore the classification of sensitivity (SE) and specificity (SP) across studies while also evaluating the moderator effects of clinical and non-clinical variables. A total of 119 studies (with 12,723 patients with SSD and 13,196 HCs) were identified. The meta-analysis estimated a SE of 79.1% (95% confidence interval [CI], 77.1%-81.0%) and a SP of 80.0% (95% CI, 77.8%-82.0%). In particular, the Positive and Negative Syndrome Scale and the Global Assessment of Functioning scores, age, age of onset, duration of untreated psychosis, deep learning, algorithm type, features selection, and validation methods had significant effects on classification performance. Multivariate pattern analysis reliably identifies neuroimaging-based biomarkers of SSD, achieving ∼80% SE and SP. Despite clinical heterogeneity, discernible brain modifications effectively differentiate SSD from HCs. Classification performance depends on patient-related and methodological factors crucial for the development, validation, and application of prospective models in clinical settings.

Goodness-of-fit testing in bivariate count time series based on a bivariate dispersion index

AbstractA common choice for the marginal distribution of a bivariate count time series is the bivariate Poisson distribution. In practice, however, when the count data exhibit zero inflation, overdispersion or non-stationarity features, such that a marginal bivariate Poisson distribution is not suitable. To test the discrepancy between the actual count data and the bivariate Poisson distribution, we propose a new goodness-of-fit test based on a bivariate dispersion index. The asymptotic distribution of the test statistic under the null hypothesis of a first-order bivariate integer-valued autoregressive model with marginal bivariate Poisson distribution is derived, and the finite-sample performance of the goodness-of-fit test is analyzed by simulations. A real-data example illustrate the application and usefulness of the test in practice.

Level of institutional delivery service utilization and associated factors among women who gave birth in the past 12 months, Ga’an libah district, Marodijeh region, Somaliland: a community-based cross-sectional study

BackgroundInstitutional delivery has been considered one of the important strategies to improve maternal and child health and significantly reduce birth-related complications. However, it is still low in developing countries though there are some improvements. even among the community who has access to the health institutions weather health center and hospital including Somaliland. Hence, the aim of this study was to assess the level of institutional delivery service utilization and associated factors among women who gave birth in the last 12 months in Ga’an libah district, Marodijeh region, Somaliland.MethodsThe community-based cross-sectional study was conducted among women who gave birth in the last 12 months from September to December 2022. A simple random sampling technique was employed to select study participants from a total of sample population. Data was collected using semi-structural administered questionnaire through interviewing women. Data was collected with online mobile data collection (Kobo collect). SPSS version 25.0 was used for data management, entering and analysis. Bivariate and multivariable logistic regression models were fitted to determine the presence of a statistically significant association between independent variables and the outcome variable with p-value < 0.05.ResultLevel of Institutional delivery services utilization in Ga’an libah district was 53.9% [95% Cl 48.2–59.6] gave birth at health institutions. Women who can read and write local were (AOR 2.18, 95% CI 1.08–4.56, p<0.01), Women with their husband can be capable to read and write are [(AOR = 6.95, 95% Cl 2.82–21.58, p<0.002]). Additionally, ability to cost transportation for referral [AOR 5.21, 95% Cl 2.44–11.13, p<0.001]. not good services available [AOR 0.07, 95%Cl 0.01–0.10, p<0.02]. lack of maternal health and child knowledge [AOR 0.034, 95% Cl 0.02–0.57, p<0.01]. were observed associated with level of institutional deliver services utilization.ConclusionThe institutional delivery service utilization was relatively high compared to national demographic health services in the study area. A large proportion of women gave both at home without a skilled attendant. Therefore, this finding has important policy implications since changes in the cost of the health service and perceived quality would mean changes in client satisfaction as well as their choice, as well emphasize to expectant women can receive medical advice and ambulance for referrals.

The Diagnostic Accuracy of Colon Capsule Endoscopy in Inflammatory Bowel Disease-A Systematic Review and Meta-Analysis.

Colon capsule endoscopy (CCE) has regained popularity for lower gastrointestinal investigations since the COVID-19 pandemic. While there have been systematic reviews and meta-analyses on colonic polyp detection using CCE, there is a lack of comprehensive evidence concerning colonic inflammation. Therefore, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of CCE for colonic inflammation, predominantly ulcerative colitis (UC) and Crohn's disease (CD). Methods: We systematically searched electronic databases (EMBASE, MEDLINE, PubMed Central, and Cochrane Library) for studies comparing the diagnostic accuracy between CCE and optical endoscopy as the standard reference. A bivariate random effect model was used for the meta-analysis. Results: From 3797 publications, 23 studies involving 1353 patients were included. Nine studies focused on UC, and ten focused on CD. For UC, CCE showed a pooled sensitivity of 92% (95% CI, 88-95%), a specificity of 71% (95% CI, 35-92%), and an AUC of 0.93 (95% CI, 0.89-0.97). For CD, the pooled sensitivity was 92% (95% CI, 89-95%), and the specificity was 88% (95% CI, 84-92%), with an AUC of 0.87 (95% CI, 0.76-0.98). Overall, for inflammatory bowel disease, the pooled sensitivity, specificity, and AUC were 90% (95% CI, 85-93%), 76% (95% CI, 56-90%), and 0.92 (95% CI, 0.94-0.97), respectively. Conclusions: Despite the challenges around standardised disease scoring and the lack of histological confirmation, CCE performs well in diagnosing inflammatory bowel disease. It demonstrates high sensitivity in both UC and Crohn's terminal ileitis and colitis and high specificity in Crohn's disease. Further studies are needed to evaluate the diagnostic accuracy of other colonic inflammatory conditions.

Prevalence, Predictors, and Treatment Outcomes of Anemia in Vietnamese School-Age Children With Helicobacter pylori Infection.

Background A growing number of studies suggest that anemia caused by Helicobacter pylori (H. pylori) infection is prevalent in developing countries. A combination of H. pylori eradication and iron supplementation may be effective intreating iron deficiency anemia (IDA) caused by H. pylori infection. The aim of this study is to assess the prevalence, risk factors, and treatment outcomes of anemia in Vietnamese school-age children infected with H. pylori Methods A cross-sectional study was conducted from April 2023 to April 2024 involving 112 dyspeptic children from 5 to 16 years old who were admitted to Can Tho Children's Hospital, Vietnam. H. pylori infection was diagnosed with a positive histopathology combined with a rapid urease test. A bivariate and multivariate logistic regression model was used to identify independent variables associated with anemia in H. pylori-infected children. Results The prevalence of anemia and IDA (iron deficiency anemia) amongH . pylori-infected children were 28.6% and 53.1%, respectively. The risk factor for anemia was age group from 11 to 16 years of age (OR: 3.24; CI 95%:1.21- 8.70). Iron supplementation (OR: 0.14; CI 95%:0.03 - 0.66) and periodic deworming (OR: 0.29; CI 95%: 0.10-0.89) were protective factors against anemia. After H. pyroli eradication and iron supplementation, all hematological parameters were increased among 32 anemic patients. Hemoglobin increased from 9.9 ±2.1 to 11.9±2.1 g/dL (p<0.001), mean corpuscular hemoglobin increased from 25.1 ± 4.1 to 28.0 ± 3.3 pg (P=0.003), and ferritin (IQR) increased from 16.7 (9.5-45.2) to 27.0 (15.1-47.0) µg/L (p<0.001). Conclusion Anemia in Vietnamese school-age children infected with H. pylori is prevalent. Taking iron supplements and periodic deworming reduces the risk of anemia. H. pylori eradication therapy plus oral iron supplementation will improve iron status in H. pylori-infected children.

Trivariate Joint Modeling for Family Data with Longitudinal Counts, Recurrent Events and a Terminal Event with Application to Lynch Syndrome.

Trivariate joint modeling for longitudinal count data, recurrent events, and a terminal event for family data has increased interest in medical studies. For example, families with Lynch syndrome (LS) are at high risk of developing colorectal cancer (CRC), where the number of polyps and the frequency of colonoscopy screening visits are highly associated with the risk of CRC among individuals and families. To assess how screening visits influence polyp detection, which in turn influences time to CRC, we propose a clustered trivariate joint model. The proposed model facilitates longitudinal count data that are zero-inflated and over-dispersed and invokes individual-specific and family-specific random effects to account for dependence among individuals and families. We formulate our proposed model as a latent Gaussian model to use the Bayesian estimation approach with the integrated nested Laplace approximation algorithm and evaluate its performance using simulation studies. Our trivariate joint model is applied to a series of 18 families from Newfoundland, with the occurrence of CRC taken as the terminal event, the colonoscopy screening visits as recurrent events, and the number of polyps detected at each visit as zero-inflated count data with overdispersion. We showed that our trivariate model fits better than alternative bivariate models and that the cluster effects should not be ignored when analyzing family data. Finally, the proposed model enables us to quantify heterogeneity across families and individuals in polyp detection and CRC risk, thus helping to identify individuals and families who would benefit from more intensive screening visits.

PSLBI-26 Purebred-crossbred genetic parameters for sow pelvic organ prolapse

Abstract The incidence rate of sow pelvic organ prolapses (vaginal, uterine, or rectal) has increased in recent years. Using a relatively large dataset, this study aimed to estimate the genetic parameters for sow pelvic organ prolapse in purebred and crossbred sow herds. Data were collected from 2018 to 2023 in 32 purebred and 8 crossbred farms, including records from 75,162 purebred sows of a single maternal line and 18,988 two-way crossbred commercial sows. Pelvic organ prolapse was categorized as either normal or prolapsed at the individual sow level, with average incidence rates of 1.81% and 3.93% for purebred and crossbred, respectively. Prolapses in purebred and crossbred were considered two different traits in the model. The bivariate model included fixed effects of parity group and region, and random effects of contemporary group, additive genetic and residual. The contemporary group was defined as the farm, mating year, and month at the first parity. Genetic parameters were estimated using BLUPF90+ with the AIREML option. Heritability estimates were 0.09 for purebreds and 0.11 for crossbreds, with a genetic correlation of 0.83. Results suggested that selection strategies aimed at reducing prolapse incidence in purebred herds will also benefit crossbred sow herds. Due to the low heritability, reducing the incidence of prolapse will have to rely on genetic improvement and enhanced animal management strategies.

118 DHGLMF90: A software tool using double hierarchical generalized linear models for estimating the genetic heterogeneity of residual variance

Abstract In animal breeding, there is a growing interest in selecting animals that exhibit uniform responses to environmental conditions, aiming for product consistency as a desirable breeding objective. This could be achieved by modeling heteroskedastic residuals when estimating breeding values through a hierarchical single-trait model that includes a mean and dispersion part. The latter could be influenced by genetic and non-genetic features. Bayesian methods can estimate heteroskedastic residuals using the Metropolis-Hastings algorithm, which is a slow and inefficient approach. Double hierarchical generalized linear models (DHGLM) provide a faster alternative to Bayesian methods. This study aimed to develop software named DHGLMF90 to implement DHGLM using a highly efficient algorithm to accurately estimate heterogeneous residual variances and breeding values, particularly suited for handling large datasets. We improved the reweighted least squares algorithm (IRWLS) to enhance convergence properties compared with prior implementations. IRWLS iteratively computes variance components and leverages them for a bivariate model, covering both the mean and dispersion part of the original model. In DHGLMF90, variance component estimation is performed using REML through BLUPF90+. The software was tested using both simulated and real datasets, the latter from previous studies. Additionally, the simulations were replicated to ensure a comprehensive evaluation of the DHGLMF90 performance. Results indicated that, in most cases, there were no significant differences in estimation compared with results obtained from previous studies. DHGLMF90 converged in order of magnitude faster than Bayesian methods. Future developments will include analyzing datasets with genomic information and multiple-trait models.

Vitamin C and suicidal ideation: A cross-sectional and Mendelian randomization study

BackgroundStudies have shown that a history of suicide attempts is associated with low levels of antioxidant vitamins. However, the specific relationship between vitamin C and suicidal ideation remains poorly understood. The purpose of this study is to investigate the effect of vitamin C on the development of suicidal ideation and to explore further the causal relationship using Mendelian randomization (MR). MethodsUsing the 2005–2018 National Health and Nutrition Examination Survey (NHANES) dataset, a comprehensive, cross-sectional, stratified survey of 28,623 participants aged 20 years and older was conducted. Suicidal ideation was assessed using item 9 of the Patient Health Questionnaire-9 (PHQ-9) item. The relationship between vitamin C and suicidal ideation was revealed by weighted multiple linear regression, smooth curve fitting, hierarchical analysis, and interaction test. To determine causality, MR was performed on vitamin C and suicidal ideation. ResultsIn cross-sectional studies, all models showed a negative association between vitamin C and suicidal ideation, with a 37 % reduction in the risk of suicidal ideation for each unit increase in vitamin C in the highest quartile in the fully adjusted model. The results of the subgroup analysis showed that the association between vitamin C and suicidal ideation was stable across gender, age, education, smoking status, and marital status. In the MR study, our bivariate model showed no significant causal relationship between vitamin C and the development of suicidal ideation. ConclusionsDietary vitamin C intake was negatively associated with the development of suicidal ideation. However, genetic evidence does not support causation of these associations.