Tag: nevin manimala

N Z Med J. 2025 Jan 24;138(1608):107-117.

ABSTRACT

BACKGROUND AND AIM: Dysmenorrhea affects the majority of young women worldwide, but geographical and cultural differences can influence the reporting, impact and management of symptoms. Aotearoa New Zealand is a culturally diverse country, with a high proportion of Māori and Pacific peoples. The aim of this scoping review was to assess the current literature on the prevalence, impact and management strategies for dysmenorrhea in Aotearoa New Zealand.

METHOD: The Joanna Briggs Institute (JBI) scoping review methodology was used to systematically map the evidence of prevalence, severity and symptoms, impact and management strategies for dysmenorrhea in Aotearoa New Zealand. Eight electronic databases were searched in August 2024.

RESULTS: Ten studies met the inclusion criteria. Our findings show that the current data for the prevalence, impact and management strategies for dysmenorrhea in Aotearoa New Zealand are both limited and outdated.

CONCLUSION: The results from this scoping review highlight the need for updated data on dysmenorrhea in Aotearoa New Zealand, with particular focus on Māori and Pacific peoples, and geographical diversity.

PMID:39847740

N Z Med J. 2025 Jan 24;138(1608):94-106. doi: 10.26635/6965.6500.

ABSTRACT

BACKGROUND: The prevalence of diabetes has been increasing in Aotearoa New Zealand by approximately 7% per year, and is three times higher among Māori and Pacific peoples than in Europeans. The depth of the diabetes epidemic, and the expansive breadth of services required for its management, elevate the need for high-quality evidence on the projected future burden of this complex disease.

METHODS: In this manuscript we have projected the prevalence of diabetes (type 1 and type 2 combined) out to 2040-2044 using age-period-cohort modelling. National-level data from central government on diabetes prevalence (Virtual Diabetes Register) were used to describe recent diabetes prevalence trends (2006-2019) by age group, calendar period and birth cohort, with these trends used to project diabetes prevalence out from 2020 to 2044.

RESULTS: Aotearoa New Zealand will experience a significant increase in the absolute volume of prevalent diabetes, rising by nearly 90% to more than 500,000 by 2044. The age-standardised prevalence of diabetes will increase from around 3.9% of the population (268,248) to 5.0% overall (502,358). The prevalence and volume of diabetes diagnoses will increase most drastically for Pacific peoples, most notably Pacific females for whom diabetes prevalence is projected to increase to 17% of the population by 2044.

CONCLUSIONS: The increases in the future burden of diabetes mellitus projected here will heighten pressure on health services. Immediate action is required to reduce new cases of diabetes and other obesity-related illnesses. Fiscal policies to prevent these diseases, coupled with population-level interventions to more effectively manage and control diabetes, are effective tools for reducing disease burden.

PMID:39847739 | DOI:10.26635/6965.6500

N Z Med J. 2025 Jan 24;138(1608):84-93. doi: 10.26635/6965.6621.

ABSTRACT

AIM: There are limited data on the prevalence of calcific aortic valve disease (CAVD) in Māori and known inequities in outcomes after aortic valve intervention. Our study aimed to investigate the prevalence of CAVD in Māori.

METHODS: Data from initial clinically indicated echocardiograms performed between 2010 to 2018 in patients aged ≥18 years were linked to nationally collected outcome data. Ethnicity was defined using protocols from the Ministry of Health.

RESULTS: Of the 23,635 patients, 1,312 (5.6%) identified as Māori, and 22,323 (94.4%) as European. Prevalence of aortic stenosis was 5.3% in Māori and 9.9% in Europeans. Age-specific prevalence did not differ between the two groups. Māori with CAVD were more than twice as likely to have advanced cardiac impairment (right ventricular dysfunction) than Europeans (10.1% vs 4.6, p<0.001).

CONCLUSIONS: Age-specific CAVD rates did not differ between Māori and Europeans, though Māori had a higher proportion of advanced cardiac impairment, which is likely unrelated to CAVD. Differences in population structure likely explain the difference in overall prevalence of CAVD. The improving life expectancy in Māori may lead to increasing incidence of CAVD, thus strategies to improve detection and medical management of CAVD should begin as soon as possible.

PMID:39847738 | DOI:10.26635/6965.6621

N Z Med J. 2025 Jan 24;138(1608):24-30. doi: 10.26635/6965.6681.

ABSTRACT

The hypothesis that lunar cycles influence human behaviour, particularly incidents recorded by police or coroners, has been a topic of public and media interest around the world for decades. While connections between lunar cycles and numerous cultural practices are well-documented, claims that lunar cycles influence crime or suicide statistics have not been consistently supported. There have been recent media claims that suicide rates in New Zealand follow a lunar cycle, correlating with the Māori Maramataka lunar calendar. Building on prior research, this study scrutinises the postulated association between lunar phases and suicide rates, for general and Māori populations. Utilising 2 decades (2000-2022) of data from the National Coronial Information System (NCIS) and the New Zealand Ministry of Health – Manatū Hauora, the study employs Poisson regression models and cosine curve analyses. Results reveal no significant correlation between lunar phases and suicide rates for the overall population or the Māori sub-group. The absence of a lunar effect persists across univariate and multivariate analyses, incorporating annual, seasonal and day-of-the-week variations. Contrary to claims linking lunar phases to Māori suicide rates, this study provides a robust analysis of comprehensive suicide data. While acknowledging potential limitations, such as the diversity among Maramataka systems and unaccounted external factors, this study emphasises the need for evidence-based practices in mental health interventions. Further research is warranted to explore potential lunar influences on less severe mental health indicators and to substantiate claims supporting traditional Māori Maramataka-based treatments.

PMID:39847735 | DOI:10.26635/6965.6681

N Z Med J. 2025 Jan 24;138(1608):13-23. doi: 10.26635/6965.6653.

ABSTRACT

AIM: Electronic cigarette use (vaping) has increased rapidly among adolescents globally. Most electronic cigarettes (e-cigarettes) contain nicotine, which is addictive and can cause behaviour problems and mood dysregulation. We sought to assess whether an educational intervention increased knowledge about vaping-related health risks and desire to quit among high school students. We assessed whether the effects differed between in-person or online intervention.

METHOD: The analysis included 332 students from four high schools in Ōtautahi Christchurch. Students were randomly assigned to an in-person or online group and completed pre- and post-intervention questionnaires. Risk factors for smoking and vaping were assessed with logistic regression. Schools’ socio-economic status was imputed from their Equity Index rank. Intervention effects were assessed with and without demographic covariates using mixed-effect linear regression.

RESULTS: Students attending schools in lower socio-economic areas and those with Māori ethnicity were at greater risk of smoking and vaping. Risk of smoking increased with year level; however, risk of vaping did not. There was significant improvement in responses to 3 out of 10 knowledge questions, and there was no evidence that post-intervention scores were affected by participant characteristics. The in-person group showed higher percentage improvements than the online group. Expressed desire to quit vaping increased from 61.7% to 68.8%; however, there was significantly greater desire to quit vaping in students from years 9 and 10 than years 11 and 12 (P=0.043).

CONCLUSION: Our educational intervention improved the knowledge of high school students on vaping-related health risks and increased expressed desire to quit vaping.

PMID:39847734 | DOI:10.26635/6965.6653

Invest Radiol. 2025 Jan 24. doi: 10.1097/RLI.0000000000001157. Online ahead of print.

ABSTRACT

OBJECTIVE: Respiratory motion can affect image quality and thus affect the diagnostic accuracy of CT images by masking or mimicking relevant lung pathologies. CT examinations are often performed during deep inspiration and breath-hold to achieve optimal image quality. However, this can be challenging for certain patient groups, such as children, the elderly, or sedated patients. The study aimed to validate a dedicated triggering algorithm for initiating respiratory-triggered high-pitch computed tomography (RT-HPCT) scans in end inspiration and end expiration in complex and irregular respiratory patterns using an anthropomorphic dynamic chest phantom. Additionally, a patient study was conducted to compare the image quality and lung expansion between RT-HPCT and standard HPCT.

MATERIALS AND METHODS: The study utilized an algorithm that processes the patient’s breathing motion in real-time to determine the appropriate time to initiate a scan. This algorithm was tested on a dynamic, tissue-equivalent chest motion phantom to replicate and simulate 3-dimensional target motion using 28 breathing motion patterns taken from patient with irregular breathing. To evaluate the performance on human patients, prospective RT-HPCT was performed in 18 free-breathing patients. As a reference, unenhanced HPCT of the chest was performed in 20 patients without respiratory triggering during free-breathing. The mean CTDI was 1.73 mGy ± 0.1 mGy for HPCT and 1.68 mGy ± 0.1 mGy for RT-HPCT. For phantom tests, the deviation from the target position of the phantom inlay is known. Image quality is approximated by evaluating stationary versus moving acquisitions. For patient scans, respiratory motion artifacts and inspiration depth were analyzed using expert knowledge of lung anatomy and automated lung volume estimation. Statistical analysis was performed to compare image quality and lung volumes between conventional HPCT and RT-HPCT.

RESULTS: In phantom scans, the average deviation from the desired excursion phase was 1.6 mm ± 4.7 mm or 15% ± 24% of the phantom movement range. In patients, the overall image quality significantly improved with respiratory triggering compared with conventional HPCT (P < 0.001). Quantitative average lung volume was 4.0 L ± 1.1 L in the RT group and 3.6 L ± 1.0 L in the control group.

CONCLUSIONS: This study demonstrated the feasibility of using a patient-adaptive respiratory triggering algorithm for high-pitch lung CT in both phantom and patients. Respiratory-triggered high-pitch CT scanning significantly reduces breathing artifacts compared with conventional nontriggered free-breathing scans.

PMID:39847727 | DOI:10.1097/RLI.0000000000001157

Environ Health Perspect. 2025 Jan;133(1):17007. doi: 10.1289/EHP14285. Epub 2025 Jan 23.

ABSTRACT

BACKGROUND: Millions worldwide are exposed to elevated levels of arsenic that significantly increase their risk of developing atherosclerosis, a pathology primarily driven by immune cells. While the impact of arsenic on immune cell populations in atherosclerotic plaques has been broadly characterized, cellular heterogeneity is a substantial barrier to in-depth examinations of the cellular dynamics for varying immune cell populations.

OBJECTIVES: This study aimed to conduct single-cell multi-omics profiling of atherosclerotic plaques in apolipoprotein E knockout (ApoE^-/-) mice to elucidate transcriptomic and epigenetic changes in immune cells induced by arsenic exposure.

METHODS: The ApoE^-/- mice were fed a high-fat diet and were exposed to either 200 ppb arsenic in drinking water or a tap water control, and single-cell multi-omics profiling was performed on atherosclerotic plaque-resident immune cells. Transcriptomic and epigenetic changes in immune cells were analyzed within the same cell to understand the effects of arsenic exposure.

RESULTS: Our data revealed that the transcriptional profile of macrophages from arsenic-exposed mice were significantly different from that of control mice and that differences were subtype specific and associated with cell-cell interaction and cell fates. Additionally, our data suggest that differences in arsenic-mediated changes in chromosome accessibility in arsenic-exposed mice were statistically more likely to be due to factors other than random variation compared to their effects on the transcriptome, revealing markers of arsenic exposure and potential targets for intervention.

DISCUSSION: These findings in mice provide insights into how arsenic exposure impacts immune cell types in atherosclerosis, highlighting the importance of considering cellular heterogeneity in studying such effects. The identification of subtype-specific differences and potential intervention targets underscores the significance of understanding the molecular mechanisms underlying arsenic-induced atherosclerosis. Further research is warranted to validate these findings and explore therapeutic interventions targeting immune cell dysfunction in arsenic-exposed individuals. https://doi.org/10.1289/EHP14285.

PMID:39847705 | DOI:10.1289/EHP14285

Pain. 2025 Jan 21. doi: 10.1097/j.pain.0000000000003511. Online ahead of print.

ABSTRACT

Rapid declines in opioid analgesics dispensed in American communities since 2011 raise concerns about inadequate access to effective pain management among patients for whom opioid therapies are appropriate, especially for those living in racial/ethnic minority and socioeconomically deprived communities. Using 2011 to 2021 national data from the Automated Reports and Consolidated Ordering System and generalized linear models, this study examined quarterly per capita distribution of oxycodone, hydrocodone, and morphine (in oral morphine milligram equivalents [MMEs]) by communities’ racial/ethnic and socioeconomic profiles. Communities (defined by 3-digit-zip codes areas) were classified as “majority White” (≥50% self-reported non-Hispanic White population) vs “majority non-White.” Community socioeconomic deprivation was measured by quartiles of population-weighted Social Deprivation Index. Overall, majority non-White communities had at least 40% lower mean adjusted per capita distribution than majority White communities across all levels of socioeconomic deprivation. Among the least deprived communities, the adjusted mean per capita distribution was 46.0 (95% confidence interval [CI], 40.0-52.0) for majority non-White vs 82.8 (95% CI, 78.5-87.1) MMEs for majority White communities. Among the most deprived communities, the distribution was 78.0 (95% CI, 70.8-85.1) for majority non-White vs 134.4 (95% CI, 125.4-143.4) MMEs for majority White communities. The lower distribution in majority non-White communities was statistically significant across all socioeconomic deprivation levels and over all study years. Availability of commonly prescribed opioid analgesics was substantially lower in majority non-White communities than in majority White communities across all levels of socioeconomic deprivation. Policies governing opioid analgesic availability warrant careful consideration and potential adjustments.

PMID:39847449 | DOI:10.1097/j.pain.0000000000003511

J Med Internet Res. 2025 Jan 23;27:e66353. doi: 10.2196/66353.

ABSTRACT

BACKGROUND: Patient portals, or secure websites linked to electronic medical records, have emerged as tools to provide patients with timely access to their health information. To support the potential benefits of patient portals such as improved engagement in health care, it is essential to understand how patients and caregivers experience these portals.

OBJECTIVE: This study aimed to explore patient and caregiver experiences, facilitators, and barriers to accessing and using a patient portal called MyChart during the initial stages of its implementation.

METHODS: We applied explanatory sequential mixed methods to conduct a web-based questionnaire and semistructured interviews with MyChart users and nonusers at a large community hospital in Ontario, Canada. Among users, we explored user satisfaction with MyChart, its impact on care, and areas for improvement. For nonusers, we explored barriers to MyChart access and willingness to use it in the future. Descriptive statistics and thematic analysis were used for data analysis.

RESULTS: A total of 5651 patients and caregivers completed the web-based questionnaire and 18 (12 users and 6 nonusers) participated in interviews. MyChart users primarily learned about the portal through email (n=1288, 39%), after-visit summaries (n=953, 29%), and hospital staff (n=408, 12%). Nonusers cited lack of awareness (n=1291, 59%) and registration difficulties (n=707, 32%) as some barriers to activation and adoption, but the majority would consider activating and using MyChart if they could learn more about it (n=1126, 54%). Users valued MyChart for preparing for health care encounters but expressed dissatisfaction with limited features and access to medical history and test results, whereas nonusers tended to be unsure about the benefits of using MyChart, especially if they were infrequent health care users.

CONCLUSIONS: Patient portals offer benefits, but barriers to access and limited functionality can hinder widespread use. To enhance the adoption and potential benefits of patient portals, targeted outreach and comprehensive access to health information are essential to promote positive and seamlessly integrated health care experiences.

PMID:39847431 | DOI:10.2196/66353

J Med Internet Res. 2025 Jan 23;27:e58177. doi: 10.2196/58177.

ABSTRACT

BACKGROUND: Efficient emergency patient transport systems, which are crucial for delivering timely medical care to individuals in critical situations, face certain challenges. To address this, CONNECT-AI (CONnected Network for EMS Comprehensive Technical-Support using Artificial Intelligence), a novel digital platform, was introduced. This artificial intelligence (AI)-based network provides comprehensive technical support for the real-time sharing of medical information at the prehospital stage.

OBJECTIVE: This study aimed to evaluate the effectiveness of this system in reducing patient transport delays.

METHODS: The CONNECT-AI system provided 3 key AI services to prehospital care providers by collecting real-time patient data from the scene and hospital resource information, such as bed occupancy and the availability of emergency surgeries or procedures, using 5G communication technology and internet of things devices. These services included guidance on first aid, prediction of critically ill patients, and recommendation of the optimal transfer hospital. In addition, the platform offered emergency department medical staff real-time clinical information, including live video of patients during transport to the hospital. This community-based, nonrandomized controlled intervention study was designed to evaluate the effectiveness of the CONNECT-AI system in 2 regions of South Korea, each of which operated an intervention and a control period, each lasting 16 weeks. The impact of the system was assessed based on the proportion of patients experiencing transfer delays.

RESULTS: A total of 14,853 patients transported by public ambulance were finally selected for analysis. Overall, the median transport time was 10 (IQR 7-14) minutes in the intervention group and 9 (IQR 6-13) minutes in the control group. When comparing the incidence of transport time outliers (>75%), which was the primary outcome of this study, the rate was higher in the intervention group in region 1, but significantly reduced in region 2, with the overall outlier rate being higher in the intervention group (27.5%-29.7%, P=.04). However, for patients with fever or respiratory symptoms, the group using the system showed a statistically significant reduction in outlier cases (36.5%-30.1%, P=.01). For patients who received real-time acceptance signals from the hospital, the reduction in the percentage of 75% outliers was statistically significant compared with those without the system (27.5%-19.6%, P=.02). As a result of emergency department treatment, 1.5% of patients in the control group and 1.1% in the intervention group died (P=.14). In the system-guided optimal hospital transfer group, the mortality rate was significantly lower than in the control group (1.54%-0.64%, P=.01).

CONCLUSIONS: The present digital emergency medical system platform offers a novel approach to enhancing emergency patient transport by leveraging AI, real-time information sharing, and decision support. While the system demonstrated improvements for certain patient groups facing transfer challenges, further research and modifications are necessary to fully realize its benefits in diverse health care contexts.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04829279; https://clinicaltrials.gov/study/NCT04829279.

PMID:39847421 | DOI:10.2196/58177