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Nevin Manimala Statistics

Performance of a Full-Coverage Cervical Cancer Screening Program Using on an Artificial Intelligence- and Cloud-Based Diagnostic System: Observational Study of an Ultralarge Population

J Med Internet Res. 2024 Nov 20;26:e51477. doi: 10.2196/51477.

ABSTRACT

BACKGROUND: The World Health Organization has set a global strategy to eliminate cervical cancer, emphasizing the need for cervical cancer screening coverage to reach 70%. In response, China has developed an action plan to accelerate the elimination of cervical cancer, with Hubei province implementing China’s first provincial full-coverage screening program using an artificial intelligence (AI) and cloud-based diagnostic system.

OBJECTIVE: This study aimed to evaluate the performance of AI technology in this full-coverage screening program. The evaluation indicators included accessibility, screening efficiency, diagnostic quality, and program cost.

METHODS: Characteristics of 1,704,461 individuals screened from July 2022 to January 2023 were used to analyze accessibility and AI screening efficiency. A random sample of 220 individuals was used for external diagnostic quality control. The costs of different participating screening institutions were assessed.

RESULTS: Cervical cancer screening services were extended to all administrative districts, especially in rural areas. Rural women had the highest participation rate at 67.54% (1,147,839/1,699,591). Approximately 1.7 million individuals were screened, achieving a cumulative coverage of 13.45% in about 6 months. Full-coverage programs could be achieved by AI technology in approximately 1 year, which was 87.5 times more efficient than the manual reading of slides. The sample compliance rate was as high as 99.1%, and compliance rates for positive, negative, and pathology biopsy reviews exceeded 96%. The cost of this program was CN ¥49 (the average exchange rate in 2022 is as follows: US $1=CN ¥6.7261) per person, with the primary screening institution and the third-party testing institute receiving CN ¥19 and ¥27, respectively.

CONCLUSIONS: AI-assisted diagnosis has proven to be accessible, efficient, reliable, and low cost, which could support the implementation of full-coverage screening programs, especially in areas with insufficient health resources. AI technology served as a crucial tool for rapidly and effectively increasing screening coverage, which would accelerate the achievement of the World Health Organization’s goals of eliminating cervical cancer.

PMID:39566061 | DOI:10.2196/51477

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Nevin Manimala Statistics

Rates of Major Depressive Disorder and Bipolar Disorder in Black and White Postpartum Women

J Clin Psychiatry. 2024 Nov 20;85(4):23m15023. doi: 10.4088/JCP.23m15023.

ABSTRACT

Importance: Little is known about differences between Black and White women with respect to the prevalence of postpartum mood disorders or symptom presentations.

Objective: To determine the prevalence and characteristics of postpartum major mood disorders in Black and White women at 4-6 weeks after birth.

Methods: This is a secondary analysis of a large-scale study designed to screen women for postpartum depression with the Edinburgh Postnatal Depression Scale (EPDS) and collect symptom data. Data were collected at an urban maternity hospital in an academic setting in Pittsburgh, Pennsylvania. Of the 2,019 women who screened positive and accepted a psychiatric diagnostic interview, 163 and 85 Black women had major depressive and bipolar disorders, respectively, and 508 and 177 White women had major depressive and bipolar disorders, respectively. Those with an EPDS score greater than or equal to 10 were offered a psychiatric assessment (in-person at home or by telephone) with the Structured Clinical Interview for DSM IV using the Structured Interview Guide for the Hamilton Rating Scale for Depression, Atypical Depression Version symptom inventory, a questionnaire related to childhood and adulthood physical and sexual abuse, and the Short Form Survey 12. Participants who self-identified as Black or White were included in this analysis.

Results: Among screen-positive participants, no significant difference in the rate of major depressive disorder (40% Black and 35% White) was observed. However, bipolar disorder significantly differed between Black (19.2%) and White (11.5%) women. Additionally, symptom profiles differed between Black and White participants with major depressive disorder, and a high rate of traumatic experiences was reported by participants with major depression and bipolar disorder in both racial groups.

Conclusion: An understanding of the different presentations of postpartum mood disorders between Black and White women, as well as trauma-informed care, can optimize postpartum health care through supporting advocacy efforts for resource allocation and health care delivery.

Trial Registration: Dataset from study at ClinicalTrials.gov identifier: NCT00282776.

PMID:39566056 | DOI:10.4088/JCP.23m15023

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Nevin Manimala Statistics

Towards a Further Understanding of Meta-Analysis Using Gestational Exposure to Cannabis and Birth Defects as a Case in Point

J Clin Psychiatry. 2024 Nov 20;85(4):24f15673. doi: 10.4088/JCP.24f15673.

ABSTRACT

About 5%-10% of pregnancies in the US are exposed to cannabis with highest use reported during the first trimester. Two recent meta-analyses presented estimates of the risk of birth defects associated with prenatal exposure to cannabis; the larger and more recent meta-analysis pooled data from 18 cohort and 18 case-control studies with a total sample size of >19 million subjects. The meta-analyses found that prenatal exposure to cannabis was associated with a small but statistically significant increased risk of any birth defect (pooled odds ratios [ORs], 1.25-1.33); ORs were also significantly elevated for cardiovascular, gastrointestinal, nervous system, genitourinary, and musculoskeletal but not orofacial birth defects. The ORs were smaller and less likely to be statistically significant in adjusted analyses. These meta-analyses had strengths but also shortcomings. The strengths and shortcomings are explained in detail so that readers obtain a better understanding of how to critically assess findings in meta-analyses. One strength was the presentation of both unadjusted and adjusted pooled estimates; the former allow an understanding of risks in the average real world patient and the latter allow an understanding of the unique contribution of the exposure to the outcomes. Another strength was the presentation of cumulative meta-analyses which demonstrated from which calendar year onwards a finding became consistently statistically significant in the scientific literature. One shortcoming, in analyses of subcategories of birth defects, was the repeated representation of the same sample in the same forest plot; the many reasons why this is problematic are explained. Another shortcoming was the pooling of ORs obtained from cohort studies with those obtained from case control studies; conceptual and numerical reasons why this is problematic are also explained.

PMID:39566055 | DOI:10.4088/JCP.24f15673

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Hyperbaric Oxygen Therapy for Veterans With Combat-Associated Posttraumatic Stress Disorder: A Randomized, Sham-Controlled Clinical Trial

J Clin Psychiatry. 2024 Nov 10;85(4):24m15464. doi: 10.4088/JCP.24m15464.

ABSTRACT

Objective: Cumulative data indicate that new protocols of hyperbaric oxygen therapy (HBOT) may induce neuroplasticity and improve clinical symptoms of patients suffering from posttraumatic stress disorder (PTSD). The aim of the current study was to evaluate the effects of HBOT on veterans with combat-associated PTSD (CA-PTSD) in a randomized, sham-controlled trial.

Methods: Male veterans aged 25-60 years with CA-PTSD, with a Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) score above 20, were included. Exclusion criteria included a history of traumatic brain injury, other psychiatric diseases, or contraindication to HBOT. Participants were randomly assigned to HBOT or sham intervention. Both interventions involved 60 daily sessions, with 90 minutes of either 100% oxygen at 2 atmospheres absolute (ATA) (HBOT) or 21% oxygen at 1.02 ATA (sham) with 5-minute air breaks every 20 minutes. CAPS-5 score, Beck Depression Inventory-II (BDI-II), the Depression, Anxiety and Stress Scale 21 Items (DASS-21), and resting-state functional magnetic resonance imaging (rsfMRI) were assessed at baseline and posttreatment, with the primary end point defined as a 30% reduction in CAPS-5 score from baseline.

Results: The study was conducted between February 2020 and July 2023. Of 63 veterans who underwent randomization, 56 completed the study protocol (28 in each group). The HBOT group showed a significant decrease in mean CAPS-5 total score, from 42.57 ±9.29 at baseline to 25.8±9.5 following HBOT (P< .001) and 25.08± 13.08 at follow-up (P< .001). The sham group demonstrated a significant increase in CAPS-5 total score from baseline to follow-up, from 45.11 ±8.99 to 47.75± 11.27 following HBOT (P= .069) and 49.22± 10.26 at follow-up (P= .011). Significant improvements in the depression domain of the DASS-21 questionnaire and BDI-II were demonstrated (F=4.55, P= .03 and F=4.2, P= .04, respectively). The stress and anxiety domains of DASS-21 did not reach statistically significant levels. Analysis of rsfMRI demonstrated improved connectivity within the 3 main networks (default-mode network, central-executive network, salience network) in HBOT vs sham groups.

Conclusions: Dedicated HBOT protocol can improve PTSD symptoms of veterans with CA-PTSD. The clinical improvement was accompanied by enhanced functional connectivity demonstrated by rsMRI.

Trial Registration: ClinicalTrials.gov identifier: NCT04518007.

PMID:39566051 | DOI:10.4088/JCP.24m15464

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COVID-19 knowledge, attitudes, and behaviors of STEM vs. non-STEM college students in Central Appalachia in 2021, a student-led project

J Am Coll Health. 2024 Nov 20:1-5. doi: 10.1080/07448481.2024.2418519. Online ahead of print.

ABSTRACT

Background: The COVID-19 pandemic has provided the general public with an understanding of scientific processes and health systems surrounding vaccination in real-time. This report assesses responses of college students in a regional university to the Centers for Disease Control and Prevention’s (CDC) Knowledge, Attitudes, and Behaviors (KAB) survey in the spring of 2021. Methods: Participants were categorized based on study major: Science, Technology, Engineering and Math (STEM), non-STEM, or health science disciplines. Chi-square tests were used to compare vaccination beliefs between groups. Results: 632 respondents were included in the final analysis. STEM students were the least likely to agree that vaccinated individuals should not need masks (21%) compared to non-STEM (42%) and health science majors (37%). 51%, 45%, and 35% of STEM, non-STEM, and health science students were vaccinated respectively. No statistically significant differences were noted between groups. Conclusions: Vaccine hesitancy was similar in all students. Area of study did not impact vaccine behaviors.

PMID:39566045 | DOI:10.1080/07448481.2024.2418519

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Nevin Manimala Statistics

Evaluation Framework of Large Language Models in Medical Documentation: Development and Usability Study

J Med Internet Res. 2024 Nov 20;26:e58329. doi: 10.2196/58329.

ABSTRACT

BACKGROUND: The advancement of large language models (LLMs) offers significant opportunities for health care, particularly in the generation of medical documentation. However, challenges related to ensuring the accuracy and reliability of LLM outputs, coupled with the absence of established quality standards, have raised concerns about their clinical application.

OBJECTIVE: This study aimed to develop and validate an evaluation framework for assessing the accuracy and clinical applicability of LLM-generated emergency department (ED) records, aiming to enhance artificial intelligence integration in health care documentation.

METHODS: We organized the Healthcare Prompt-a-thon, a competitive event designed to explore the capabilities of LLMs in generating accurate medical records. The event involved 52 participants who generated 33 initial ED records using HyperCLOVA X, a Korean-specialized LLM. We applied a dual evaluation approach. First, clinical evaluation: 4 medical professionals evaluated the records using a 5-point Likert scale across 5 criteria-appropriateness, accuracy, structure/format, conciseness, and clinical validity. Second, quantitative evaluation: We developed a framework to categorize and count errors in the LLM outputs, identifying 7 key error types. Statistical methods, including Pearson correlation and intraclass correlation coefficients (ICC), were used to assess consistency and agreement among evaluators.

RESULTS: The clinical evaluation demonstrated strong interrater reliability, with ICC values ranging from 0.653 to 0.887 (P<.001), and a test-retest reliability Pearson correlation coefficient of 0.776 (P<.001). Quantitative analysis revealed that invalid generation errors were the most common, constituting 35.38% of total errors, while structural malformation errors had the most significant negative impact on the clinical evaluation score (Pearson r=-0.654; P<.001). A strong negative correlation was found between the number of quantitative errors and clinical evaluation scores (Pearson r=-0.633; P<.001), indicating that higher error rates corresponded to lower clinical acceptability.

CONCLUSIONS: Our research provides robust support for the reliability and clinical acceptability of the proposed evaluation framework. It underscores the framework’s potential to mitigate clinical burdens and foster the responsible integration of artificial intelligence technologies in health care, suggesting a promising direction for future research and practical applications in the field.

PMID:39566044 | DOI:10.2196/58329

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Nevin Manimala Statistics

Rank Ordered Design Attributes for Health Care Dashboards Including Artificial Intelligence: Usability Study

Online J Public Health Inform. 2024 Nov 20;16:e58277. doi: 10.2196/58277.

ABSTRACT

BACKGROUND: On average, people in the United States visit a doctor 4 times a year, and many of them have chronic illnesses. Because of the increased use of technology, people frequently rely on the internet to access health information and statistics. People use health care information to make better-educated decisions for themselves and others. Health care dashboards should provide pertinent and easily understood data, such as information on timely cancer screenings, so the public can make better-informed decisions. In order to enhance health outcomes, effective dashboards should provide precise data in an accessible and easily digestible manner.

OBJECTIVE: This study identifies the top 15 attributes of a health care dashboard. The objective of this research is to enhance health care dashboards to benefit the public by making better health care information available for more informed decisions by the public and to improve population-level health care outcomes.

METHODS: The authors conducted a survey of health care dashboards with 218 individuals identifying the best practices to consider when creating a public health care dashboard. The data collection was conducted from June 2023 to August 2023. The analyses performed were descriptive statistics, frequencies, and a comparison to a prior study.

RESULTS: From May 2023 to June 2023, we collected 3259 responses in multiple different states around the United States from 218 people aged 18 years or older. The features ranking in descending order of importance are as follows: (1) easy navigation, (2) historical data, (3) simplicity of design, (4) high usability, (5) use of clear descriptions, (6) consistency of data, (7) use of diverse chart types, (8) compliance with the Americans with Disabilities Act, (9) incorporated user feedback, (10) mobile compatibility, (11) comparison data with other entities, (12) storytelling, (13) predictive analytics with artificial intelligence, (14) adjustable thresholds, and (15) charts with tabulated data.

CONCLUSIONS: Future studies can extend the research to other types of dashboards such as bioinformatics, financial, and managerial dashboards as well as confirm these top 15 best practices for medical dashboards with further evidentiary support. The medical informatics community may benefit from standardization to improve efficiency and effectiveness as dashboards can communicate vital information to patients worldwide on critically prominent issues. Furthermore, health care professionals should use these best practices to help increase population health care outcomes by informing health care consumers to make better decisions with better data.

PMID:39566038 | DOI:10.2196/58277

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Nevin Manimala Statistics

Associations between objectively measured nighttime sleep duration, sleep timing, and sleep quality and body composition in toddlers in the Guelph Family Health Study

Appl Physiol Nutr Metab. 2024 Nov 20. doi: 10.1139/apnm-2024-0244. Online ahead of print.

ABSTRACT

The prevalence of child obesity is a worldwide public health concern. Good sleep hygiene is associated with reduced adiposity in older children and adults. More research is needed in younger children to help mitigate risk of obesity. As well, we aimed to address limitations found in previous studies such as relying on subjective measures, or only including one parameter of sleep,using only one body composition parameter, and/or not adjusting for relevant covariates. This cross-sectional study examined baseline data from 48 toddlers aged 1 to <3 years enrolled in the Guelph Family Health Study. Nighttime sleep duration, sleep timing (time child went to sleep, and awoke), and sleep quality were measured using 24-hour accelerometry for seven consecutive days. Height, body weight, and waist circumference were measured, and BMI z-scores and waist-to-height ratios were calculated. Percent fat mass and fat mass index were calculated using bioelectrical impedance analysis. Linear regression models were used to estimate associations between sleep parameters and body composition outcomes, with adjustments for relevant covariates (age, sex, household income, screen time, energy intake, physical activity, household stress). Nighttime sleep onset time was positively associated with waist-to-height ratio (β^=0.004, p=0.04). Sleep offset time was negatively associated with BMI z-score (β^=-0.48, p=0.02). Total sleep time and wake after sleep onset were not associated with any body composition outcome. Building healthy sleep habits may prevent childhood obesity; longitudinal research in a larger sample is warranted. This study was registered on ClinicalTrials.gov (NCT02939261).

PMID:39566036 | DOI:10.1139/apnm-2024-0244

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Nevin Manimala Statistics

Differing conceptual maps of skills for implementing evidence-based interventions held by community-based organization practitioners and academics: A multidimensional scaling comparison

Transl Behav Med. 2024 Nov 20:ibae051. doi: 10.1093/tbm/ibae051. Online ahead of print.

ABSTRACT

Community-based organizations (CBOs) are critical for delivering evidence-based interventions (EBIs) to address cancer inequities. However, a lack of consensus on the core skills needed for this work often hinders capacity-building strategies to support EBI implementation. The disconnect is partly due to differing views of EBIs and related skills held by those typically receiving versus developing capacity-building interventions (here, practitioners and academics, respectively). Our team of implementation scientists and practice-based advisors used group concept mapping to engage 34 CBO practitioners and 30 academics with experience addressing cervical cancer inequities implementing EBIs. We created group-specific maps of skills using multidimensional scaling and hierarchical cluster analysis, then compared them using Procrustes comparison permutations. The 98 skills were sorted into six clusters by CBO practitioners and five by academics. The groups generated maps with statistically comparable underlying structures but also statistically significant divergence. Some skill clusters had high concordance across the two maps, e.g. “managing funding and external resources.” Other skill clusters, e.g. “adapting EBIs” from the CBO practitioner map and “selecting and adapting EBIs” from the academic map, did not overlap as much. Across groups, key clusters of skills included connecting with community members, understanding the selected EBI and community context, adapting EBIs, building diverse and equitable partnerships, using data and evaluation, and managing funding and external resources. There is a significant opportunity to combine CBO practitioners’ systems/community frames with the EBI-focused frame of academics to promote EBI utilization and address cancer and other health inequities.

PMID:39566021 | DOI:10.1093/tbm/ibae051

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Analysis of Concordance Between Next-Generation Sequencing Assessment of Microsatellite Instability and Immunohistochemistry-Mismatch Repair From Solid Tumors

JCO Precis Oncol. 2024 Oct;8:e2300648. doi: 10.1200/PO.23.00648. Epub 2024 Nov 20.

ABSTRACT

PURPOSE: The new CAP guideline published in August 2022 recommends using immunohistochemistry (IHC) to test for mismatch repair defects in gastroesophageal (GE), small bowel (SB), or endometrial carcinoma (EC) cancers over next-generation sequencing assessment of microsatellite instability (NGS-MSI) for immune checkpoint inhibitor (ICI) therapy eligibility and states there is a preference to use IHC over NGS-MSI in colorectal carcinoma (CRC).

METHODS: We assessed the concordance of NGS-MSI and IHC-MMR from a very large cohort across the spectrum of solid tumors.

RESULTS: Of the over 190,000 samples with both NGS-MSI and IHC-MMR about 1,160 were initially flagged as discordant. Of those samples initially flagged as discordant, 50.9% remained discordant after being reviewed by an additional pathologist. This resulted in a final discordance rate of 0.31% (590/191,767). Among CRC, GE, SB and EC, 55.4% of mismatch repair proficient/MSI high (MMRp/MSI-H) tumors had at least one somatic pathogenic mutation in an MMR gene or POLE. Mismatch repair deficient/microsatellite stable (MMRd/MSS) tumors had a significantly lower rate of high tumor mutational burden than MMRp/MSI-H tumors. Across all solid tumors, MMRd/MSI-H tumors had significantly longer overall survival (OS; hazard ratio [HR], 1.47, P < .001) and post-ICI survival (HR, 1.82, P < .001) as compared with MMRp/MSS tumors. The OS for the MMRd/MSS group was slightly worse compared to the MMRp/MSI-H tumors, but this difference was not statistically significant (HR, 0.73, P = .058), with a similar pattern when looking at post-ICI survival (HR, 0.43, P = .155).

CONCLUSION: This study demonstrates that NGS-MSI is noninferior to IHC-MMR and can identify MSI-H tumors that IHC-MMR is unable to detect and conversely IHC-MMR can identify MMRd tumors that NGS-MSI misses.

PMID:39565978 | DOI:10.1200/PO.23.00648