Improvement in the diagnosis and practices of emergency healthcare providers for heat emergencies after HEAT (heat emergency awareness & treatment) an educational intervention: a multicenter quasi-experimental study

Diagnostic Excellence in the Context of Climate Change: A Review

Climate change is leading to a rise in heat-related illnesses, vector-borne diseases, and numerous negative impacts on patients' physical and mental health outcomes. Concurrently, healthcare contributes about 4.6% of global greenhouse gas emissions. Low-value care, such as overtesting and overdiagnosis, contributes to unnecessary emissions. In this review, we describe diagnostic excellence in the context of climate change and focus on two topics. First, climate change is affecting health, leading to the emergence of certain diseases, some of which are new, while others are increasing in prevalence and/or becoming more widespread. These conditions will require timely and accurate diagnosis by clinicians who may not be used to diagnosing them. Second, diagnostic quality issues, such as overtesting and overdiagnosis, contribute to climate change through unnecessary emissions and waste and should be targeted for interventions. We also highlight implications for clinical practice, research, and policy. Our findings call for efforts to engage healthcare professionals and policymakers in understanding the urgent implications for diagnosis in the context of climate change and reducing global greenhouse gas emissions to enhance both patient and planetary outcomes.

Risk, Attributable Fraction and Attributable Number of Cause-Specific Heat-Related Emergency Hospital Admissions in Switzerland

Objectives

We assessed the relationship between heat and emergency hospital admissions (EHAs) in Switzerland using clinically relevant metrics.

Methods

Applying distributed lag non-linear models, we investigated temperature-admission associations between May and September 1998-2019 for various disease groups, by age class and gender. We estimated the relative risk (RR) for moderate (29°C) and extreme (34°C) daily maximum temperatures relative to disease-specific optimum temperature, and calculated attributable fractions (AFs) for hot days and the following week. We also calculated the total number of heat-related EHAs.

Results

We attributed 31,387 (95% confidence interval: 21,567-40,408) EHAs to above-optimal temperatures, 1.1% (0.7%-1.4%) of the total. Extreme temperatures increased the EHA risk for mental, infectious and neurological diseases. We observed particularly high AFs due to extreme heat for dehydration (85.9%, 95% CI: 82.4%-88.8%) and acute kidney injury (AKI, 56.1%, 95% CI: 45.3%-64.7%). While EHA risk generally increased with age, we also found high RRs for infectious diseases in children (0-15 years) and AKI in young adults (15-64 years).

Conclusion

Hot weather increases the EHA risk in Switzerland. Therefore a comprehensive clinical and public health response is needed.

Curcumin nanoparticles in heat stroke management

OBJECTIVE

The exacerbation of extreme high-temperature events due to global climate change poses a significant challenge to public health, particularly impacting the central nervous system through heat stroke. This study aims to develop Poly(amidoamine) (PAMAM) nanoparticles loaded with curcumin (PAMAM@Cur) to enhance its therapeutic efficacy in hypothalamic neural damage in a heat stroke model and explore its potential mechanisms.

METHODS

Curcumin (Cur) was encapsulated into PAMAM nanoparticles through a hydrophobic interaction method, and various techniques were employed to characterize their physicochemical properties. A heat stroke mouse model was established to monitor body temperature and serum biochemical parameters, conduct behavioral assessments, histological examinations, and biochemical analyses. Transcriptomic and proteomic analyses were performed to investigate the therapeutic mechanisms of PAMAM@Cur, validated in an N2a cell model.

RESULTS

PAMAM@Cur demonstrated good stability, photostability, cell compatibility, significant blood-brain barrier (BBB) penetration capability, and effective accumulation in the brain. PAMAM@Cur markedly improved behavioral performance and neural cell structural integrity in heat stroke mice, alleviated inflammatory responses, with superior therapeutic effects compared to Cur or PAMAM alone. Multi-omics analysis revealed that PAMAM@Cur regulated antioxidant defense genes and iron death-related genes, particularly upregulating the PCBP2 protein, stabilizing SLC7A11 and GPX4 mRNA, and reducing iron-dependent cell death.

CONCLUSION

By enhancing the drug delivery properties of Cur and modulating molecular pathways relevant to disease treatment, PAMAM@Cur significantly enhances the therapeutic effects against hypothalamic neural damage induced by heat stroke, showcasing the potential of nanotechnology in improving traditional drug efficacy and providing new strategies for future clinical applications.

SIGNIFICANCE

This study highlights the outlook of nanotechnology in treating neurological disorders caused by heat stroke, offering a novel therapeutic approach with potential clinical applications.

Strategic Enhancement of Healthcare Services During the Hajj Season in Makkah: A Comprehensive Geographic Information System (GIS) Analysis

Annually, over two million international pilgrims embark on the Hajj pilgrimage to Makkah, presenting a significant challenge for healthcare services. This study analyzes the spatial distribution of healthcare facilities in the Al Mashaer area using Geographic Information System (GIS) technology to enhance healthcare during this religious gathering. It evaluates the accessibility and efficacy of healthcare facilities, including primary care centers, clinics, and hospitals, each addressing distinct medical needs to ensure a holistic approach for pilgrims. The study maps the distribution, service radius, and services offered by each facility, along with an analysis of travel distances and times, to evaluate the viability of healthcare services. Identifying coverage gaps and accessibility issues is critical for making strategic recommendations to enhance resource allocation and distribution. The research addresses challenges such as data precision, population density, infrastructural constraints, and resource limitations. The study offers recommendations to optimize resource distribution, improve transportation strategies, expand healthcare capacity, and enhance cultural competency, resulting in improved healthcare accessibility, reduced congestion, quicker medical responses, and a safer pilgrimage experience, promoting a world-class pilgrimage management system.

Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models

This study aims to propose a novel approach for enhancing clinical prediction models by combining structured and unstructured data with multimodal data fusion. We presented a comprehensive framework that integrated multimodal data sources, including textual clinical notes, structured electronic health records (EHRs), and relevant clinical data from National Electronic Injury Surveillance System (NEISS) datasets. We proposed a novel hybrid fusion method, which incorporated state-of-the-art pre-trained language model, to integrate unstructured clinical text with structured EHR data and other multimodal sources, thereby capturing a more comprehensive representation of patient information. The experimental results demonstrated that the hybrid fusion approach significantly improved the performance of clinical prediction models compared to traditional fusion frameworks and unimodal models that rely solely on structured data or text information alone. The proposed hybrid fusion system with RoBERTa language encoder achieved the best prediction of the Top 1 injury with an accuracy of 75.00% and Top 3 injuries with an accuracy of 93.54%. Our study highlights the potential of integrating natural language processing (NLP) techniques with multimodal data fusion for enhancing clinical prediction models' performances. By leveraging the rich information present in clinical text and combining it with structured EHR data, the proposed approach can improve the accuracy and robustness of predictive models. The approach has the potential to advance clinical decision support systems, enable personalized medicine, and facilitate evidence-based health care practices. Future research can further explore the application of this hybrid fusion approach in real-world clinical settings and investigate its impact on improving patient outcomes.

An assessment of public experiences and expectations with physicians: a cross sectional study from Karachi, Pakistan

BACKGROUND

Although physicians are highly regarded members of society, patients are not always satisfied with their care, suggesting a mismatch between the public's expectations and reality. Thus, the aim of this study was to determine the public's expectations regarding roles and responsibilities of a physician, to assess patient experiences, and to evaluate factors associated with the two outcomes.

METHODS

A cross-sectional study was conducted via face-to-face structured interviews from July 14th to August 2nd, 2023, in Karachi, Pakistan. The study sample comprised 424 consenting adults enrolled by visiting public spaces (malls, parks, hospitals, and residential areas). A modified version of 'Exceptionally Good Doctor Likert scale', and 'Patient Picker-15' (PPE-15) questionnaires was used. The Likert and PPE-15 sections were scored through pre-decided criteria for expectations and experience, respectively, and categorized using a median cut-off into high and low expectations and negative and positive experiences, respectively for simple and multivariable logistic regression.

RESULTS

A median score of 30.5/ 34 (IQR = 3.3) was found for expectations and 4/ 14 (IQR = 4) for experiences. Significant factors associated with expectations were older age groups (OR = 4.54 [1.18-17.50]) and higher monthly household incomes (0.40 [0.20-0.79]), while the odds of negative experiences were lower after visits to emergency departments (0.38 [0.18-0.84]) and private health care centers (0.31 [0.13-0.70]).

CONCLUSION

These results suggest that the public has high expectations from physicians, however their experiences are not always positive. Initiatives to develop a patient-centric ethos are needed for which we outline recommendations to both the public and physicians, respectively.

Factors causing emergency medical care overload during heatwaves: A Delphi study

Heatwaves pose an important risk for population health and are associated with an increased demand for emergency care. To find factors causing such overload, an online Delphi study included 15 experts in emergency medicine, disaster medicine, or public health. One open-ended question was delivered in the first round. After content analysis, the obtained statements were sent to the experts in two rounds to be rated on a 7-point linear scale. Consensus was defined as a standard deviation ≤ 1.0. Thirty-one statements were obtained after content analysis. The experts agreed on 18 statements, mostly focusing on the input section of patient processing and identifying stakeholders, the population, and primary care as targets of potential interventions. Additional dedicated resources and bed capacity were deemed important as per throughput and output sections, respectively. These findings could be used in the future to implement and test solutions to increase emergency healthcare resilience during heatwaves and reduce disaster risk due to climatic change.