Leptospirosis is a neglected zoonotic disease that is widespread in tropical and subtropical regions such as Oceania, which includes New Zealand. The incidence rate of leptospirosis in New Zealand remains high in comparison to other high-income countries, with over half of the notified patients hospitalised, and the factors associated with hospitalisation are poorly understood. This study aimed to estimate the risk factors for hospitalisation amongst leptospirosis patients using passive surveillance data: notifications from 1 January 1999 to 31 December 2017 extracted from New Zealand's notifiable disease database. There were 771 hospitalised and 673 non-hospitalised patients. Multivariable logistic regression was used to identify risk factors. The year of notification was significantly and positively associated with hospitalisation, with adjusted (adj.) OR 1.03 (95% CI:1.01-1.05). Occupation was significantly associated with hospitalisation, with the adjusted odds of hospitalisation amongst dairy farmers notified with leptospirosis at adj. OR 1.44 (95% CI: 1.02-2.02) times the adjusted odds of hospitalisation amongst farmers that worked with other livestock. Seropositivity for Copenhageni (adj. OR 5.96, 95% CI: 1.68-21.17) and Pomona (adj. OR 1.14, 95% CI: 0.74-1.74)) was more likely to result in hospitalisation when compared to Ballum (baseline). Seropositivity for Hardjo (adj. OR 0.71, 95% CI: 0.49-1.01) and Tarassovi (adj. OR 0.39, 95% CI: 0.23-0.66) was less likely to result in hospitalisation when compared to Ballum (baseline). All the estimates were additionally adjusted for the effect of sex, age, ethnicity, reported occupational exposure, geographical location, reported season, and deprivation status Although passive surveillance data has limitations we have been able to identify that the New Zealand dairy farming population may benefit from a targeted awareness campaign.
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http://dx.doi.org/10.3390/tropicalmed6040188 | DOI Listing |
Am J Trop Med Hyg
January 2025
Department of Pediatrics, National School of Tropical Medicine, Section of Tropical Medicine, Baylor College of Medicine, Houston, Texas.
The burden of pathogenic enteric protozoa and soil-transmitted helminths among impoverished populations living on the Texas-Mexico border is unclear. We conducted a cross-sectional study on an ongoing longitudinal cohort of 616 adults residing in Starr County, Texas. A total of 359 adults were screened for four protozoa and five soil-transmitted helminths by using real-time polymerase chain reaction.
View Article and Find Full Text PDFJ Occup Environ Hyg
January 2025
Human and Environmental Physiology Research Unit, School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada.
With mines extending deeper and rising surface temperatures, workers are exposed to hotter environments. This study aimed to characterize heat stress and strain in the Canadian mining industry and evaluate the utility of the Heat Strain Score Index (HSSI), combined with additional self-reported adverse health outcomes. An exploratory web-based survey was conducted among workers ( = 119) in the Canadian mining industry.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Background: Despite the increasing popularity of electronic devices, the longitudinal effects of daily prolonged electronic device usage on brain health and the aging process remain unclear.
Objective: The aim of this study was to investigate the impact of the daily use of mobile phones/computers on the brain structure and the risk of neurodegenerative diseases.
Methods: We used data from the UK Biobank, a longitudinal population-based cohort study, to analyze the impact of mobile phone use duration, weekly usage time, and playing computer games on the future brain structure and the future risk of various neurodegenerative diseases, including all-cause dementia (ACD), Alzheimer disease (AD), vascular dementia (VD), all-cause parkinsonism (ACP), and Parkinson disease (PD).
JMIR Res Protoc
January 2025
Department of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, United States.
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View Article and Find Full Text PDFInteract J Med Res
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Medical Directorate, Lausanne University Hospital, Lausanne, Switzerland.
Large language models (LLMs) are artificial intelligence tools that have the prospect of profoundly changing how we practice all aspects of medicine. Considering the incredible potential of LLMs in medicine and the interest of many health care stakeholders for implementation into routine practice, it is therefore essential that clinicians be aware of the basic risks associated with the use of these models. Namely, a significant risk associated with the use of LLMs is their potential to create hallucinations.
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