Tag: pubmed

Phys Imaging Radiat Oncol. 2024 Dec 4;32:100684. doi: 10.1016/j.phro.2024.100684. eCollection 2024 Oct.

ABSTRACT

BACKGROUND AND PURPOSE: Segmentation imperfections (noise) in radiotherapy organ-at-risk segmentation naturally arise from specialist experience and image quality. Using clinical contours can result in sub-optimal convolutional neural network (CNN) training and performance, but manual curation is costly. We address the impact of simulated and clinical segmentation noise on CNN parotid gland (PG) segmentation performance and provide proof-of-concept for an easily implemented auto-curation countermeasure.

METHODS AND MATERIALS: The impact of segmentation imperfections was investigated by simulating noise in clean, high-quality segmentations. Curation efficacy was tested by removing lowest-scoring Dice similarity coefficient (DSC) cases early during CNN training, both in simulated (5-fold) and clinical (10-fold) settings, using our full radiotherapy clinical cohort (RTCC; N = 1750 individual PGs). Statistical significance was assessed using Bonferroni-corrected Wilcoxon signed-rank tests. Curation efficacies were evaluated using DSC and mean surface distance (MSD) on in-distribution and out-of-distribution data and visual inspection.

RESULTS: The curation step correctly removed median(range) 98(90-100)% of corrupted segmentations and restored the majority (1.2 %/1.3 %) of DSC lost from training with 30 % corrupted segmentations. This effect was masked when using typical (non-curated) validation data. In RTCC, 20 % curation showed improved model generalizability which significantly improved out-of-distribution DSC and MSD (p < 1.0e-12, p < 1.0e-6). Improved consistency was observed in particularly the medial and anterior lobes.

CONCLUSIONS: Up to 30% case removal, the curation benefit outweighed the training variance lost through curation. Considering the notable ease of implementation, high sensitivity in simulations and performance gains already at lower curation fractions, as a conservative middle ground, we recommend 15% curation of training cases when training CNNs using clinical PG contours.

PMID:39720784 | PMC:PMC11667007 | DOI:10.1016/j.phro.2024.100684

Pharmgenomics Pers Med. 2024 Dec 20;17:551-561. doi: 10.2147/PGPM.S482289. eCollection 2024.

ABSTRACT

PURPOSE: Atorvastatin is commonly used to treat dyslipidemia; however, individual responses vary considerably. This study endeavors to evaluate the relationship between polymorphisms in the coding sequence (CDS) of SLCO1B1 gene and blood lipid levels before and after atorvastatin treatment among the Chinese Han adults with dyslipidemia.

PATIENTS AND METHODS: A total of 165 Chinese Han adults undergoing atorvastatin therapy were enrolled in this study and followed up quarterly. The complete CDS of the SLCO1B1 gene was sequenced to detect polymorphisms. Statistical analysis was utilized to assess the impacts of sex, age, body mass index (BMI), and polymorphisms on blood lipid levels before and after atorvastatin treatment.

RESULTS: Fourteen polymorphisms were identified in the SLCO1B1 CDS. Among them, four polymorphisms had mutant alleles present in over 20 patients. No polymorphism was found to correlate with blood lipid levels before treatment; in contrast, age, sex, and BMI did show correlations (P<0.05). Notably, females had higher baseline blood lipid levels than males, indicating that sex had a more significant impact on baseline levels than age and BMI. The polymorphism rs2306283 was significantly correlated with the efficacy of atorvastatin (P<0.05), whereas age, sex, and BMI were not. Carriers of the rs2306283 AA allele experienced a substantially greater reduction in total cholesterol (TC) and triglyceride (TG) levels after atorvastatin treatment. The other polymorphisms did not demonstrate any significant impact on atorvastatin’s efficacy.

CONCLUSION: This study delved into the intricate genetic structure of polymorphisms in SLCO1B1 CDS and their roles in lipid metabolism and atorvastatin’s efficacy among Chinese Han adults with dyslipidemia. The findings underscore the crucial role of the rs2306283 polymorphism in the response to atorvastatin’s efficacy, highlighting the significance of pharmacogenomics in personalized medicine. It is thus advisable to consider genetic testing for SLCO1B1 variants to optimize atorvastatin therapy.

PMID:39720770 | PMC:PMC11668066 | DOI:10.2147/PGPM.S482289

Am J Prev Cardiol. 2024 Nov 23;21:100895. doi: 10.1016/j.ajpc.2024.100895. eCollection 2025 Mar.

ABSTRACT

BACKGROUND: Lipoprotein(a) [Lp(a)] is a low-density lipoprotein variant with atherogenic, thrombogenic, and pro-inflammatory properties that may have numerous pathologic effects, including dyslipidemia. Screening for Lp(a) is clinically significant, due to its causal role in atherosclerotic cardiovascular disease (ASCVD). Among clinicians, however, there remains a general lack of both clinical awareness of Lp(a) and adequate tools to track Lp(a) testing in patients.

OBJECTIVE: To study factors affecting Lp(a) screening by: i) determining the effectiveness of messaging providers at a large community health system about Lp(a) screening and measuring the subsequent percentage of Lp(a) tests requested; and ii) by determining the percentage of patients who obtained Lp(a) testing after being advised by the provider.

METHODS: From December 2022 through March 2023, messages detailing the need for Lp(a) screening were sent via the Epic EHR™ to providers of patients meeting criteria for Lp(a) testing in advance of scheduled patient appointments. In this prospective study, providers were randomized into 2 groups: those receiving the pre-appointment message (Group 1) and those not receiving the pre-appointment message (Group 2).

RESULTS: Sending pre-appointment messages correlated with more Lp(a) orders (16.6 % v. 4.7 %, P < 0.001) and consequently with more tests performed (10.2 % v. 3.7 %, p < 0.001). Among provider types, nurse practitioners and physician assistants had the highest number of Lp(a) results per order (Z = 16.40, P < 0.001), achieving 30.8-39.1 % more test results, even if they did not receive the pre-appointment message. Distribution of Lp(a) values in patients was 59.7 % ≤ 29 mg/dL; 9.7 % > 29 and < 50mg/dL; and 30.6 % ≥ 50 mg/dL.

CONCLUSION: Providers who received pre-appointment messages via an EHR were associated with requesting more tests and consequently receiving more Lp(a) results, compared with providers who did not receive messages.

PMID:39720768 | PMC:PMC11666892 | DOI:10.1016/j.ajpc.2024.100895

Am J Prev Cardiol. 2024 Nov 29;21:100899. doi: 10.1016/j.ajpc.2024.100899. eCollection 2025 Mar.

ABSTRACT

AIMS: To investigate the association between body mass index (BMI) at acute myocardial infarction (AMI) and all-cause as well as cause-specific long-term mortality.

METHODS: The analysis was based on 10,651 hospitalized AMI patients (age 25-84 years) recorded by the population-based Myocardial Infarction Registry Augsburg between 2000 and 2017. The median follow-up time was 6.7 years [IQR: 3.5-10.0)]. Cause-specific mortality was obtained by evaluating the death certificates. In multivariable-adjusted COX regression models using cubic splines for the variable BMI, the association between BMI and cause-specific mortality (all-cause, cardiovascular, ischemic heart diseases, cancer) was investigated. Additionally, a subgroup analysis in three age groups was performed for all-cause mortality.

RESULTS: Overall, there was a statistically significant U-shaped association between BMI at AMI and long-term mortality with the lowest hazard ratios (HR) found for BMI values between 25 and 30 kg/m². For cancer mortality, higher BMI values > 30 kg/m² were not associated with higher mortality. In patients aged <60 years, there was a significant association between BMI values >35 kg/m² and increased all-cause mortality; this association was missing in 60 to 84 years old patients. For all groups and for each specific cause of mortality, lower BMI (<25kg/m²) values were significantly associated with higher mortality.

CONCLUSIONS: Overall, a lower BMI – and also a high BMI in patients younger than 60 years – seem to be a risk factors for increased all-cause mortality after AMI. A BMI in a mid-range between 25 and 30 kg/m² is favorable in terms of long-term survival after AMI.

PMID:39720766 | PMC:PMC11665372 | DOI:10.1016/j.ajpc.2024.100899

Healthc Technol Lett. 2024 Nov 25;11(6):318-326. doi: 10.1049/htl2.12099. eCollection 2024 Dec.

ABSTRACT

Accurate intra-operative Remaining Surgery Duration (RSD) predictions allow for anaesthetists to more accurately decide when to administer anaesthetic agents and drugs, as well as to notify hospital staff to send in the next patient. Therefore, RSD plays an important role in improved patient care and minimising surgical theatre costs via efficient scheduling. In endoscopic pituitary surgery, it is uniquely challenging due to variable workflow sequences with a selection of optional steps contributing to high variability in surgery duration. This article presents PitRSDNet for predicting RSD during pituitary surgery, a spatio-temporal neural network model that learns from historical data focusing on workflow sequences. PitRSDNet integrates workflow knowledge into RSD prediction in two forms: (1) multi-task learning for concurrently predicting step and RSD; and (2) incorporating prior steps as context in temporal learning and inference. PitRSDNet is trained and evaluated on a new endoscopic pituitary surgery dataset with 88 videos to show competitive performance improvements over previous statistical and machine learning methods. The findings also highlight how PitRSDNet improves RSD precision on outlier cases utilising the knowledge of prior steps.

PMID:39720757 | PMC:PMC11665798 | DOI:10.1049/htl2.12099

J Health Popul Nutr. 2024 Dec 24;43(1):225. doi: 10.1186/s41043-024-00692-3.

ABSTRACT

BACKGROUND: Foodborne illness is a significant public health concern, particularly in developing countries like Bangladesh. Young adults, aged 18-26 (including undergraduates and recent graduates), are especially vulnerable to the onset of unhealthy eating habits and nutritional imbalances as they begin living independently, often away from their families. This research aims to identify the risk factors associated with the knowledge, attitudes, and practices related to safe food handling among residential university students. By understanding these factors, the study seeks to inform strategies to improve food safety behaviors in this at-risk population.

METHODS: A standardized questionnaire was administered through a simple random sampling survey of 250 students at Jahangirnagar University to collect primary data on food safety practices, attitudes, and knowledge. Descriptive statistics and the chi-square test were used to examine associations between the responses and predictor variables. To further assess the statistical significance and strength of these relationships, logistic regression analyses were performed. These methods provided a comprehensive evaluation of the factors influencing safe food handling behaviors among the students.

RESULTS: The survey found that most participants were from rural areas (44.4%) and female students (65.2%). Multicollinearity issues were not detected, and predictor factors explained 53.8% (Nagelkerke R-square: 0.538) of the variation in food poisoning incidents. Overall, 57.6% of students reported being prone to food poisoning. Risk factors for food poisoning included being in the third year of study (OR: 3.493, CI: 0.394-30.972), consuming food during a blackout based on its appearance or scent (OR: 4.824, CI: 0.690-33.715), and believing food should be refrigerated for five to seven days (OR: 2.309, CI: 0.318-16.778). Conversely, students who stored raw meat or fish on the middle shelf (OR: 0.078, CI: 0.012-0.511) and those who thought leftover food should be kept in the fridge for more than seven days (OR: 0.034, CI: 0.002-0.626) were less likely to experience food poisoning. These findings highlight behaviors that influence foodborne illness risk among students.

CONCLUSIONS: This study found that while students in Bangladesh demonstrate a strong understanding of food handling, there has been insufficient focus on food safety education in the country. Based on these findings, the authors recommend enhancing awareness of key food safety risks and integrating this knowledge into both short- and long-term initiatives. To ensure lasting improvements in food safety, sustained and effective interventions are essential. These efforts will accelerate progress toward achieving the sustainable development goals related to public health in Bangladesh.

PMID:39719654 | DOI:10.1186/s41043-024-00692-3

BMC Psychol. 2024 Dec 24;12(1):776. doi: 10.1186/s40359-024-02278-4.

ABSTRACT

BACKGROUND: This study examined how university students’ social media use is related to their mental health (subjective well-being [SWB] and loneliness) and perceived physical health. A cognitive bias model and a social network mediation model were used to compare social capital formed via face-to-face and online communication, considering the effects of personality traits (i.e., social skills, generalized trust, and social tolerance).

METHODS: We conducted a self-report survey with 409 university students in Japan from August to September 2022. Four patterns of social media use were analyzed: (1) Twitter only, (2) LINE + Twitter, (3) Instagram + Twitter, and (4) Discord + Twitter. Relationships between the variables were investigated with a structural equation modeling analysis using SmartPLS 4.0.

RESULTS: Overall, regardless of social media use patterns, personality traits had positive direct effects on mental health and also had positive effects on social capital via face-to-face (FTF) communication, which had mediating effects on the improvement of mental health. FTF social capital had a positive relationship with online social capital, which did not have relationships with mental or perceived physical health. Additionally, perceived physical health decreased loneliness but was not associated with SWB. Social media use negatively affected perceived physical health but had no effect on SWB or loneliness. Finally, different relationships between personality traits and social media use, FTF social capital and SWB, social media use and perceived physical health were observed among the four patterns of social media use.

CONCLUSION: This study has implications for improving the health of young adults in the “mobile x social era.” In particular, we provide suggestions to help young adults improve their mental health.

PMID:39719653 | DOI:10.1186/s40359-024-02278-4

J Health Popul Nutr. 2024 Dec 24;43(1):226. doi: 10.1186/s41043-024-00725-x.

ABSTRACT

BACKGROUND: The link between regional body fat distribution and overactive bladder (OAB) in prior epidemiological research has been uncertain. Our objective is to assess the relationship between increased regional body fat and the prevalence of OAB.

METHODS: Within this analysis, 8,084 individuals aged 20 years and older were selected from NHANES surveys conducted from 2011 to 2018. The evaluation of OAB symptoms utilized the overactive bladder symptom score (OABSS). Fat mass (FM) across various regions was quantified employing dual-energy X-ray absorptiometry, which assessed total FM, trunk FM, arm FM, and leg FM. The fat mass index (FMI) was calculated as the ratio of fat mass (kg) to the square of height (meters). Data weighting was performed in accordance with analysis guidelines. A linear logistic regression model was employed to assess the correlation between regional FMI and the occurrence of OAB. Stratified analyses were also conducted.

RESULTS: The study found significant associations between total FMI and limb FMI with OAB. After adjusting for all variables in the analysis, higher total FMI (OR = 1.07, 95% CI = 1.02-1.12) was linked to an increased risk of OAB. Trunk FMI (OR = 1.12, 95% CI = 1.03-1.22), arm FMI (OR = 1.59, 95% CI = 1.20-2.10), and leg FMI (OR = 1.12, 95% CI = 1.01-1.25) demonstrated significant correlations with OAB. The weighted associations between total FMI and limb FMI with OAB incidence showed no significant differences among most subgroups.

CONCLUSIONS: The data indicates a correlation between higher regional FMI and increased OAB risk across different populations.

PMID:39719652 | DOI:10.1186/s41043-024-00725-x

BMC Psychol. 2024 Dec 24;12(1):778. doi: 10.1186/s40359-024-02283-7.

ABSTRACT

BACKGROUND: Traditional cognitive assessments, often reliant on paper-and-pencil tests and professional evaluators, suffer from subjectivity and limited result discrimination. This study introduces the Baguan Online Cognitive Assessment System (BOCAS), a tablet-based system that evaluates both general cognitive ability (GCA) and domain-specific functions across six domains: sensory-motor skills, processing speed, sustained attention, working memory, cognitive flexibility, and spatial ability.

METHODS: BOCAS was validated with 151 healthy Chinese adults aged 18-40. Reliability was assessed through internal consistency and test-retest reliability. Factor analysis and confirmatory factor analysis (CFA) were used to validate the model. The GCA score was correlated with the Raven IQ test and self-reported cognitive flexibility, and its relationship with negative emotions (depression and anxiety) was examined.

RESULTS: BOCAS showed satisfactory reliability, with internal consistency ranging from 0.712 to 0.846 and test-retest reliability from 0.56 to 0.71. Factor analysis revealed a common factor explaining 40% of the variance, and CFA indicated a good model fit (χ²/df = 1.81; CFI = 0.932). The GCA score strongly correlated with the Raven IQ test (r = 0.58) and was related to self-reported cognitive flexibility and negative emotions.

CONCLUSION: BOCAS offers a digital solution for cognitive assessment, providing automated, remote, and precise evaluations. It demonstrates reliability, validity, and potential for use in clinical and research settings.

PMID:39719650 | DOI:10.1186/s40359-024-02283-7

BMC Psychol. 2024 Dec 24;12(1):780. doi: 10.1186/s40359-024-02300-9.

ABSTRACT

BACKGROUND: Suicide prevention programs delivered in school settings have been shown to reduce suicide attempts and ideation among adolescents. School-based digital interventions targeting at-risk youth are a promising avenue for suicide prevention, and some evidence has shown that blending digital and face-to-face components may improve the effectiveness. However, further evidence is needed, especially in Latin America, where mental health support is limited. We tested the effectiveness of the Reframe-IT+, a blended cognitive behavioral indicated intervention to reduce suicidal ideation, designed to be delivered in school settings. It includes 13 sessions, combining eight internet-based sessions and five face-to-face sessions.

METHODS: We conducted a cluster RCT and delivered the Reframe-IT + among secondary students attending Years 9-11. We recruited 21 schools that were randomized into two groups: (1) Intervention Reframe-IT + Group (IG) (n = 863) and (2) Control Group (CG) (n = 683). All consented students completed online screening self-reported questionnaires at baseline. The primary outcome was suicidal ideation . Additionally, we tested the impact of the intervention on depressive and anxiety symptoms, hopelessness, and emotion regulatory strategies, including social solving-problems skills, behavioral activation, cognitive reappraisal, and emotion suppression. A total of 303 students (IG, n = 164; CG, n = 139) were identified as at risk and eligible for inclusion in the study. From those, 224 students (IG, n = 123; CG, n = 101) and their caregivers were interviewed to confirm inclusion and exclusion criteria. Finally, 48 and 47 students were allocated to control and intervention groups, respectively, and answered the online questionnaires at post-intervention. We performed an intention-to-treat analysis using repetitive measures and multilevel regression analyses.

RESULTS: We found a significant reduction in suicidal ideation (b=-6.7, p = 0.015, Cohen´s d = 0.49), depressive (b=-3.1, p = 0.002, Cohen´s d = 0.81) and anxiety (b=-2.60, p < 0.001, Cohen´s d = 0.72) symptoms, and hopelessness (b=-3.7, p < 0.001, Cohen´s d = 0.70) in the intervention group compared to the control group at post-intervention. We also found improvement in solving-problems skills (b=-1.6, p = 0.002, Cohen´s d = 0.58), behavioral activation (b = 2.8, p = 0.019, Cohen´s d = 0.47), and cognitive reappraisal (b = 2.2, p = 0.029, Cohen´s d = 0.53). In the exploration of the intervention mechanisms concerning suicidal ideation, the total indirect effect of the intervention (b = -5.727923; p = 0.008) was significant, whereas the direct effect (b = – 0.03195473, p = 0.903) was not significant (Suppl 2, Table 1). Problem-solving skill (b=-2.84, p = 0.016) was a significant mediator of intervention effects on suicidal ideation (Path a*b).

CONCLUSIONS: This is the first clustered RCT evaluation of the effectiveness of a blended indicated intervention to prevent suicidality in school settings in Latin America. This is the first step to informing policymakers to scale up an effective intervention for an important public health problem.

TRIAL REGISTRATION: Clinical Trials NCT05229302. Registered on January 27th, 2022.

PMID:39719648 | DOI:10.1186/s40359-024-02300-9