Tag: statistics

Int J Offender Ther Comp Criminol. 2025 Jun 26:306624X251345511. doi: 10.1177/0306624X251345511. Online ahead of print.

ABSTRACT

There has been a considerable amount of research examining the role that poverty might play in the development of crime and with being processed through the criminal justice system. Despite this research, there still remain some important gaps in the knowledge base, including whether poverty differentially moderates the effects of criminal behavior and criminogenic influences on being processed through the criminal justice system. The current study addressed this gap by examining whether poverty in adolescence moderated the influence of antisocial behavior and criminogenic influences on being arrested, convicted, and incarcerated in adulthood. Findings revealed little evidence of poverty as a moderating influence on criminal justice processing. The one exception, however, was that poverty moderated the association between antisocial behavior and incarceration such that antisocial behavior had no association on incarceration for persons living in poverty, but that it had a statistically significant and positive association with incarceration for persons not living in poverty. The results of this study are discussed in relation to the existing literature on the poverty-crime nexus.

PMID:40568765 | DOI:10.1177/0306624X251345511

Front Cell Infect Microbiol. 2025 Jun 11;15:1571291. doi: 10.3389/fcimb.2025.1571291. eCollection 2025.

ABSTRACT

OBJECTIVES: This study aimed to investigate the prevalence of TB/HIV co-infection in pediatric TB patients in southwest China and its associated variables.

METHODS: Pediatric TB patients were recruited from January 2014 to September 2024 in southwest China, based on etiology or clinical confirmation. Hospitalization records were extracted for each patient.

RESULTS: Among 2,607 pediatric TB patients with an average age of 9.58 ± 4.08 years, 39 (1.5%) were HIV-positive. The TB/HIV co-infection group male-to-female ratio was 2:1, higher than the TB-only group 1.19:1. The highest proportion of TB/HIV co-infection was in the 5-9 years age group (43.6%), while the 10-14 years age group accounted for the highest proportion of TB-alone cases (57.5%). In terms of population distribution, the Yi ethnic group had the highest proportion of TB/HIV co-infection cases (43.6%), while the Tibetan group had the highest proportion of TB-alone cases (51.1%). Extrapulmonary TB in the TB/HIV co-infection group primarily involved abdominal and pericardial sites, whereas the TB-alone infection group had more cases of lymphadenitis and pleural TB. The length of hospitalization (>14 days) in the TB/HIV co-infection group (74.4%) was significantly longer than in the TB-alone infection group (51.7%). Over the past 11 years, most pediatric TB/HIV co-infection cases were from the eastern-central and southern-central regions of Sichuan, particularly the southern Liangshan Yi Autonomous Prefecture. The number of children with TB-alone infections increased gradually during this period. No significant difference in the number of pediatric TB/HIV co-infection cases was observed over the 11 years.

CONCLUSION: Pediatric TB/HIV co-infection in southwest China predominantly affects middle-aged and young boys, with a higher co-infection rate than the national average. The central and southern regions of Sichuan have a relatively high proportion of cases. Public health efforts should focus on strengthening awareness, screening, and early diagnosis of TB and HIV in children in high-risk areas to prevent further infections.

PMID:40568707 | PMC:PMC12187718 | DOI:10.3389/fcimb.2025.1571291

medRxiv [Preprint]. 2025 Jan 15:2025.01.14.25320574. doi: 10.1101/2025.01.14.25320574.

ABSTRACT

Psychiatric disorders display high levels of comorbidity and genetic overlap ^1,2 . Genomic methods have shown that even for schizophrenia and bipolar disorder, two disorders long-thought to be etiologically distinct ³ , the majority of genetic signal is shared ⁴ . Furthermore, recent cross-disorder analyses have uncovered over a hundred pleiotropic loci shared across eight disorders ⁵ . However, the full scope of shared and disorder-specific genetic basis of psychopathology remains largely uncharted. Here, we address this gap by triangulating across a suite of cutting-edge statistical genetic and functional genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders (1,056,201 cases). Our analyses identify and characterize five underlying genomic factors ⁶ that explain the majority of the genetic variance of the individual disorders (∼66% on average) and are associated with 268 pleiotropic loci. We observed particularly high levels of polygenic overlap ⁷ and local genetic correlation ⁸ and very few disorder-specific loci ⁹ for two factors defined by: ( i ) schizophrenia and bipolar disorder (“SB factor”), and by ( ii ) major depression, PTSD, and anxiety (“internalizing factor”). At the functional level, we applied multiple methods ^10-12 which demonstrated that the shared genetic signal across the SB factor was substantially enriched in genes expressed in excitatory neurons, whereas the internalizing factor was associated with oligodendrocyte biology. By comparison, the genetic signal shared across all 14 disorders was enriched for broad biological processes (e.g., transcriptional regulation). These results indicate increasing differentiation of biological function at different levels of shared cross-disorder risk, from quite general vulnerability to more specific pathways associated with subsets of disorders. These observations may inform a more neurobiologically valid psychiatric nosology and implicate novel targets for therapeutic developments designed to treat commonly occurring comorbid presentations.

PMID:40568675 | PMC:PMC12191084 | DOI:10.1101/2025.01.14.25320574

medRxiv [Preprint]. 2025 Jan 20:2025.01.19.25320798. doi: 10.1101/2025.01.19.25320798.

ABSTRACT

Unlike some health conditions that have been extensively delineated throughout the lifespan, many genetic conditions are largely described in pediatric populations, with a focus on early manifestations like congenital anomalies and developmental delay. An apparent gap exists in understanding clinical features and optimal management as patients age. Generative artificial intelligence is transforming biomedical disciplines including through the introduction of large language models (LLMs). Motivated by these advances, we explored how LLMs handle age with respect to 282 genetic conditions selected based on prevalence. We divided these conditions into five categories: Disorders limited to childhood; Disorders limited to adulthood; Disorders with changes in presentation across ages; Disorders with changes in management across ages; Disorders with no changes across ages. We evaluated Llama-2-70b-chat (70b) and GPT-3.5 (GPT) capabilities at generating accurate medical vignettes for these conditions based on Correctness, Completeness, and Conciseness as graded by 3 clinicians. Using accurately generated vignettes as in-context prompts, we further generated and evaluated patient-geneticist dialogues and assessed LLM performance in answering specific questions regarding age-based management plans for a subset of conditions. Results revealed impressive performances of 70b with in-context prompting and GPT in generating vignettes. We overall did not observe age-based biases, though our experiments identified statistically significant differences in some areas related to LLM output. Despite impressive capabilities, LLMs still have limitations in clinical applications.

PMID:40568663 | PMC:PMC12191088 | DOI:10.1101/2025.01.19.25320798

medRxiv [Preprint]. 2025 Jan 15:2025.01.15.25320592. doi: 10.1101/2025.01.15.25320592.

ABSTRACT

PURPOSE: Poor quality prostate MRI images, especially ADC maps, can lead to missed lesions and unnecessary repeat scans. To address this issue, we aimed to develop an automated method to predict ADC map quality from T2 images acquired earlier in the scanning process.

MATERIALS AND METHODS: A paired multi-site image corpus of T2-weighted images and ADC maps was constructed from 486 patients imaged in-house and at 62 external clinics. A senior radiologist assigned 1-3 quality ratings to each image set, later converted to a binary “non-diagnostic” or “diagnostic” scale. A deep learning model and a rectal cross-sectional area measurement approach were developed to predict ADC image quality from T2 images. Model performance was evaluated retrospectively by accuracy, sensitivity, negative and positive predictive value, and AUC.

RESULTS: No single acquisition parameter in the metadata was statistically associated with image quality for either T2 or ADC maps. Quality scores of the same modality showed low correlation across sites (r∼0.2). In the challenging task of predicting ADC quality from prior T2 images, our model achieved performance comparable to current single-site models directly using ADC maps, with 83% sensitivity and 90% negative predictive value. The model showed stronger performance on in-house data (94±2% accuracy) despite being trained exclusively on multicenter external data. Rectal cross-sectional area on T2 images provided an interpretable quality metric (AUC 0.65).

CONCLUSION: The probability of low quality, uninterpretable ADC maps can be inferred early in the imaging process by neural network approach, allowing corrective action to be employed.

PMID:40568662 | PMC:PMC12191087 | DOI:10.1101/2025.01.15.25320592

medRxiv [Preprint]. 2025 May 23:2025.05.22.25328175. doi: 10.1101/2025.05.22.25328175.

ABSTRACT

BACKGROUND: Recent genome-wide association studies (GWAS) for Alzheimer’s Disease and related dementias (ADRD) have increased statistical power via larger analysis datasets from biobanks by 1) including non-age-matched controls and prevalent cases, and/or 2) including individuals who report a family history of ADRD as proxy cases. However, these methods have the potential to increase noise and distort genetic associations which are important for genomic-informed prevention and treatment of ADRD. Here, we sought to understand how the effect sizes of genetic associations in ADRD could be sensitive to these methodological choices, using APOE genotypes as an example.

METHODS: Participants in the All of Us Research Program over the age of 49 at enrollment (n=258,693) were assigned one of four categories: incident ADRD (developed after enrollment in All of Us ), prevalent ADRD (present on enrollment), proxy ADRD (participant noted a family history of ADRD), and control (no history or diagnosis of ADRD). Dementia diagnoses were determined using available Electronic Health Records (EHR) and APOE genotype was determined using whole-genome sequencing. Effect sizes for the associations between APOE risk alleles and ADRD diagnoses were compared using polychotomous logistic regression.

RESULTS: The mean age of the cohort was 67±10 years, and it was 58% female; 63% clustered predominantly with European genetic reference populations. Among the participants, 3,107 (1.2%) had prevalent ADRD, 301 (0.1%) had incident ADRD, and 19,910 (7.7%) reported a family history of ADRD (proxy ADRD). Both prevalent and proxy ADRD had attenuated associations with APOE genotype compared to incident ADRD. The adjusted generalized ratio (95% CI) (AGR) for incident ADRD for APOE ε4 heterozygotes was 2.95 (2.31-3.74) compared to 2.10 (1.96-2.24) and 1.42 (1.32-1.55) for proxy and prevalent ADRD, respectively. For APOE ε4 homozygotes, the effect sizes were even more different. Furthermore, APOE association effect sizes increased when restricting the control (no ADRD) group to older age brackets.

CONCLUSIONS: Our study highlights how genetic associations with ADRD can be sensitive to how cases are defined in biobanks like All of Us , with effect sizes downwardly biased when using prevalent or by-proxy cases compared to incident cases.

PMID:40568661 | PMC:PMC12191090 | DOI:10.1101/2025.05.22.25328175

Rwanda J Med Health Sci. 2023 Nov 30;6(3):389-397. doi: 10.4314/rjmhs.v6i3.12. eCollection 2023 Nov.

ABSTRACT

BACKGROUND: Exposure to polluted air is a significant cause of negative health effects. Air quality is crucial in hospital environments as patients and healthcare workers spend more time in such settings for treatment where they experience prolonged and repetitive exposure; however, comprehensive studies on air quality in hospital environments in Rwanda are scarce.

OBJECTIVE: This study aimed to determine the indoor and outdoor air quality concentration levels in selected hospitals and investigate potential sources of air pollution.

METHODS: This descriptive cross-sectional study was conducted in two public and two private hospitals in Kigali that were randomly selected using a simple random sampling technique. Real-time particulate matter (PM), PM_2.5 and PM₁₀ were measured using calibrated Purple Air PA-II sensors. An observation checklist was used to identify potential sources of air pollution. One way ANOVA and t-tests were performed.

RESULTS: Air quality levels in selected hospitals exceeded acceptable limits. The daily average indoor PM_2.5 concentration ranged from 23.52 µg/m³ to 121.60 µg/m³, and the PM₁₀ levels varied from 25.98 µg/m³ to 131.17 µg/m³. In all hospitals, the difference in average indoor and outdoor PM_2.5 and PM₁₀ concentrations were not statistically significant.

CONCLUSION: All recorded concentrations exceeded the WHO air quality guidelines. The study calls for strategies to improve air quality in hospitals.

PMID:40568653 | PMC:PMC12110502 | DOI:10.4314/rjmhs.v6i3.12

Rwanda J Med Health Sci. 2023 Nov 30;6(3):303-314. doi: 10.4314/rjmhs.v6i3.4. eCollection 2023 Nov.

ABSTRACT

BACKGROUND: Over the past decade, the magnitude and intensity of reported natural and humanmade disasters have been rising globally with substantial mortality and long-term morbidity.

OBJECTIVES: To assess the health care providers’ knowledge, attitude and practices towards disaster and emergency preparedness at Ligula Regional Referral Hospital in Mtwara, Tanzania.

METHODS: A descriptive and analytical cross-sectional study was conducted among 94 health care providers; and a stratified sampling technique was employed to recruit the participants. Bivariate and multivariable regression analyses were performed using IBM SPSS Statistics for Windows version 25.0 (IBM Corp, Armonk, NY, USA) to determine the association between independent and dependent variables. A P < 0.05 was considered statistically significant.

RESULTS: More than half 50 (53.2%) and more than three-quarters 75 (79.8%) of the participants had adequate knowledge and positive attitude towards disaster and emergency preparedness respectively. Younger participants aged 20-29 years had 5.252 (95% CI 1.313-21.016) times higher odds of having adequate knowledge of disaster and emergency preparedness than the older groups.

CONCLUSIONS: More disaster and emergency preparedness training programs and clinical simulations are needed to enhance the competencies of health care providers in handling disastrous events efficiently.

PMID:40568652 | PMC:PMC12110494 | DOI:10.4314/rjmhs.v6i3.4

Rwanda J Med Health Sci. 2023 Nov 30;6(3):346-354. doi: 10.4314/rjmhs.v6i3.8. eCollection 2023 Nov.

ABSTRACT

BACKGROUND: Ultrasound imaging has been shown to improve maternal health outcomes through timely diagnosis of pregnancy problems. Despite ultrasound being vital for women’s management in pregnancy, studies have reported low awareness among African women.

OBJECTIVE: To evaluate the knowledge and expectations of pregnant women in Harare about prenatal ultrasound.

METHODS: A cross-sectional survey of 385 pregnant women was done at the ultrasound department of a private maternity hospital in Harare, Zimbabwe. Statistical Package for Social Sciences (SPSS) 27.0 and Windows Excel were used to analyse the data.

RESULTS: The majority of women (85.4%) concurred that ultrasound scans are important during pregnancy, but most (79.3%) were not aware that congenital abnormalities can be detected through ultrasound. Despite low overall knowledge of congenital abnormalities, 80.2% of women were familiar with Down’s syndrome, and this knowledge tended to increase with higher education levels, although not statistically significant (linear-by-linear association = 0.057). The primary expectation of ultrasound scans among pregnant women was to confirm the expected delivery date, and gender determination, with the least expectation being a diagnosis of congenital abnormalities.

CONCLUSION: Knowledge levels were lower in our setting relative to other similar studies, and hence this underscores the need for further public education.

PMID:40568646 | PMC:PMC12110497 | DOI:10.4314/rjmhs.v6i3.8

Rwanda J Med Health Sci. 2023 Nov 30;6(3):290-302. doi: 10.4314/rjmhs.v6i3.3. eCollection 2023 Nov.

ABSTRACT

BACKGROUND: Poorly controlled postoperative pain remains a significant challenge. Music is a safe, inexpensive, non-invasive intervention that can be used in managing pain in surgical patients.

OBJECTIVES: To evaluate effectiveness of music intervention as an adjuvant therapy in attenuating postoperative pain among patients with tibia/fibula fractures.

METHODOLOGY: A cross-sectional pre-test, post-test intervention study design was utilized to conduct a study involving 20 tibia-fibula patients, divided equally into intervention and control groups. Self-selected music was administered for 20 minutes to the intervention group once on day-3 after surgery. Data was collected using a demographic questionnaire and Visual Analogue Scale (VAS). Data was analyzed using SPSS software version 29.0. Descriptive statistics analyzed continuous and categorical data. T-test compared means of physiologic parameters and pain levels in pre-and post-intervention. ANCOVA established the relationship between music and post-intervention pain levels.

FINDINGS: Use of music alongside conventional therapy significantly reduced pain in the intervention group than in the control group (P = 0.014). Music had no statistically significant impact on the physiological parameters.

CONCLUSION: Music therapy is effective as an adjuvant therapy for pain management and can therefore reduce the use of analgesics among surgical patients.

PMID:40568645 | PMC:PMC12110506 | DOI:10.4314/rjmhs.v6i3.3