Medicine and Health Sciences Commons^™

An Evaluation Of Lead Concentration In Commercially Available Tiles, Daidre N. Gamboa

UNLV Theses, Dissertations, Professional Papers, and Capstones

Workers in the manufacturing and construction industries are at risk of lead exposure in projects that involve removal or installation of tiles, and other individuals exposed to lead, including children may also be at risk. The concern with lead in tiles is thought to be related to the glazing process or the country where the tile was produced. Multiple regulations are in place in the U.S. to protect people from lead exposure, including through surface coatings or painted surfaces. But these regulations do not cover glazed tiles. This study examined whether there are differences in lead concentration in (1) tiles …

Development Of A Physics-Informed Neural Network For Prediction Of Blood Flow, Marcello Vittorio Mattei Di Eugenio

Theses and Dissertations

Abstract—Objective: We propose a new neural network architecture that accepts point clouds and outputs 3D velocity profiles for aneurysm geometries. Methods: We generated a synthetic aneurysm 3D flow dataset using CFD and used it to train our model architecture and compare it with other popular architectures like U-net and PointNet. We incorporate tools for improving model performance such as incorporating a distance function, a physics-informed loss to enforce the law of mass conservation, and the Huber loss to learn patterns across heterogeneous velocity components of multiple dimensions. Results: The tools implemented together with our architecture achieved the best performance on …

A Reliable And Secure Mobile Cyber-Physical Digital Microfluidic Biochip For Intelligent Healthcare, Yinan Yao, Decheng Qiu, Huangda Liu, Zhongliao Yang, Ximeng Liu, Yang Yang, Chen Dong

Research Collection School Of Computing and Information Systems

Digital microfluidic, as an emerging and potential technology, diversifies the biochemical applications platform, such as protein dilution sewage detection. At present, a vast majority of universal cyberphysical digital microfluidic biochips (DMFBs) transmit data through wires via personal computers and microcontrollers (like Arduino), consequently, susceptible to various security threats and with the popularity of wireless devices, losing competitiveness gradually. On the premise that security be ensured first and foremost, calls for wireless portable, safe, and economical DMFBs are imperative to expand their application fields, engage more users, and cater to the trend of future wireless communication. To this end, a new …

Examining Covid-19 Vaccine Hesitancy Among The Nevada African American Population Using The Social-Ecological Model, Katelyn Faulk

UNLV Theses, Dissertations, Professional Papers, and Capstones

In Nevada, COVID-19 vaccines have been widely available to the general population since March 2021; however, even with the wide availability of these vaccines only 40% of the African American population in Nevada has been fully vaccinated against COVID-19 as of May 2023. This is problematic as it has been shown that the African American population is disproportionately affected by COVID-19 with higher rates of cases, hospitalizations, and deaths when compared to other races or ethnicities. Through the literature, it has also been well documented that African Americans may experience hesitancy toward these vaccinations for a multitude of reasons including …

The Impact Of The Covid-19 Pandemic Response On Food Safety Violations Observed In Southern Nevada Food Establishments, Samantha Morales

UNLV Theses, Dissertations, Professional Papers, and Capstones

Food poisoning is a common term used to describe what is actually foodborne illness. Despite the fact these illnesses can become deadly, foodborne illnesses are endemic and common in the United States. Nonetheless, they are completely preventable simply by following proper food safety procedures. The Food and Drug Administration identified the most common foodborne pathogens responsible for most foodborne infections, as well as the five risk factor categories to target in order to decrease the risk of cases and outbreaks.

To ensure foodborne outbreaks and cases are prevented, health authorities are tasked with conducting routine inspections on permitted food establishments. …

Development Of A Methodology For The Quantification Of Reaerosolization Of A Biological Contaminate Surrogate Particle From A Military Uniform Fabric, George Cooksey, Jeremy M. Slagley, Casey W. Cooper, Douglas Lewis, Alisha Helm

Faculty Publications

In a mass casualty medical evacuation after a bioaerosol (BA) dispersal event, a decontamination (DC) method is needed that can both decontaminate and prevent biological particle (BP) re-aerosolization (RA) of contaminated clothes. However, neither the efficacy of current DC methods nor the risk of BP RA is greatly explored in the existing literature. The goals of this study were to develop a repeatable method to quantify the RA of a biological contaminant off military uniform fabric swatches and to test the efficacy of one DC protocol (high-volume, low-pressure water) using 1 µm polystyrene latex (PSL) spheres as a surrogate. A …

Responsibility Gaps And Black Box Healthcare Ai: Shared Responsibilization As A Solution, Benjamin H Lang, Sven Nyholm, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

As sophisticated artificial intelligence software becomes more ubiquitously and more intimately integrated within domains of traditionally human endeavor, many are raising questions over how responsibility (be it moral, legal, or causal) can be understood for an AI’s actions or influence on an outcome. So called “responsibility gaps” occur whenever there exists an apparent chasm in the ordinary attribution of moral blame or responsibility when an AI automates physical or cognitive labor otherwise performed by human beings and commits an error. Healthcare administration is an industry ripe for responsibility gaps produced by these kinds of AI. The moral stakes of healthcare …

Targeted Gene Expression Profiling Predicts Meningioma Outcomes And Radiotherapy Responses, William C Chen, Abrar Choudhury, Mark W Youngblood, Mei-Yin C Polley, Calixto-Hope G Lucas, Kanish Mirchia, Sybren L N Maas, Abigail K Suwala, Minhee Won, James C Bayley, Akdes S Harmanci, Arif O Harmanci, Tiemo J Klisch, Minh P Nguyen, Harish N Vasudevan, Kathleen Mccortney, Theresa J Yu, Varun Bhave, Tai-Chung Lam, Jenny Kan-Suen Pu, Lai-Fung Li, Gilberto Ka-Kit Leung, Jason W Chan, Haley K Perlow, Joshua D Palmer, Christine Haberler, Anna S Berghoff, Matthias Preusser, Theodore P Nicolaides, Christian Mawrin, Sameer Agnihotri, Adam Resnick, Brian R Rood, Jessica Chew, Jacob S Young, Lauren Boreta, Steve E Braunstein, Jessica Schulte, Nicholas Butowski, Sandro Santagata, David Spetzler, Nancy Ann Oberheim Bush, Javier E Villanueva-Meyer, James P Chandler, David A Solomon, C Leland Rogers, Stephanie L Pugh, Minesh P Mehta, Penny K Sneed, Mitchel S Berger, Craig M Horbinski, Michael W Mcdermott, Arie Perry, Wenya Linda Bi, Akash J Patel, Felix Sahm, Stephen T Magill, David R Raleigh

Faculty, Staff and Student Publications

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems …

Combat Covid-19 At National Level Using Risk Stratification With Appropriate Intervention, Xuan Jin, Kar Way Tan

Research Collection School Of Computing and Information Systems

In the national battle against COVID-19, harnessing population-level big data is imperative, enabling authorities to devise effective care policies, allocate healthcare resources efficiently, and enact targeted interventions. Singapore adopted the Home Recovery Programme (HRP) in September 2021, diverting low-risk COVID-19 patients to home care to ease hospital burdens amid high vaccination rates and mild symptoms. While a patient's suitability for HRP could be assessed using broad-based criteria, integrating machine learning (ML) model becomes invaluable for identifying high-risk patients prone to severe illness, facilitating early medical assessment. Most prior studies have traditionally depended on clinical and laboratory data, necessitating initial clinic …

The Psychological Science Accelerator's Covid-19 Rapid-Response Dataset, Erin M. Buchanan, Andree Hartanto

Research Collection School of Social Sciences

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with …

Self-Supervised Pseudo Multi-Class Pre-Training For Unsupervised Anomaly Detection And Segmentation In Medical Images, Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro

Research Collection School Of Computing and Information Systems

Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images. UAD is an important medical image analysis (MIA) method to be applied in disease screening problems because the training sets available for those problems usually contain only normal images. However, the exclusive reliance on normal images may result in the learning of ineffective low-dimensional image representations that are not sensitive enough to detect and segment unseen abnormal lesions of varying size, appearance, and shape. Pre-training UAD methods with self-supervised learning, based on computer …

Spatial-Temporal Episodic Memory Modeling For Adls: Encoding, Retrieval, And Prediction, Xinjing Song, Di Wang, Chai Quek, Ah-Hwee Tan, Yanjiang Wang

Research Collection School Of Computing and Information Systems

Activities of daily living (ADLs) relate to people’s daily self-care activities, which reflect their living habits and lifestyle. A prior study presented a neural network model called STADLART for ADL routine learning. In this paper, we propose a cognitive model named Spatial-Temporal Episodic Memory for ADL (STEM-ADL), which extends STADLART to encode event sequences in the form of distributed episodic memory patterns. Specifically, STEM-ADL encodes each ADL and its associated contextual information as an event pattern and encodes all events in a day as an episode pattern. By explicitly encoding the temporal characteristics of events as activity gradient patterns, STEM-ADL …

Access To A Regular Primary Care Physician Among Young People With Early Psychosis In Ontario, Canada, Rebecca Rodrigues, Jennifer N S Reid, Joshua C. Wiener, Suzanne Archie, Richard G Booth, Chiachen Cheng, Arlene G Macdougall, Lena Palaniyappan, Bridget L Ryan, Aristotle Voineskos, Paul Kurdyak, Saadia Hameed Jan, Kelly K. Anderson

Epidemiology and Biostatistics Publications

AIM: Access to a primary care physician in early psychosis facilitates help-seeking and engagement with psychiatric treatment. We examined access to a regular primary care physician in people with early psychosis, compared to the general population, and explored factors associated with access.

METHODS: Using linked health administrative data from Ontario (Canada), we identified people aged 14-35 years with a first diagnosis of nonaffective psychotic disorder (n = 39 449; 2005-2015). We matched cases to four randomly selected general population controls based on age, sex, neighbourhood, and index date (n = 157 796). We used modified Poisson regression to estimate prevalence …

Editorial: The Public Health Scholars As The Health Leaders, Al Asyary, Meita Veruswati, Putri Bungsu Machmud, Indri Hapsari Susilowati

Kesmas

1. Achmadi UF. Kesehatan Masyarakat: Teori dan Aplikasi. Jakarta: Rajawali Pers; 2014.

2. Asyary A. Editorial. Kesmas. 2023; 18 (Special Issue 1): 1-3. DOI: 10.21109/kesmas.v18isp1.7201

3. Badan Kebijakan Pembangunan Kesehatan. Pembangunan Kesehatan di Indonesia melalui Kesinambungan Finansial Jaminan Kesehatan serta Meningkatkan Kualitas Layanan dengan Integrasi Data. Jakarta: Kementerian Kesehatan Republik Indonesia; 2023.

Data Quality Checks: Implementation With Popular Data Collection Crowdsourcing Platforms, James Down, Gregory Balkcom, Kristine Duncan, Ngan (An) Truong, Andrew Lewis

Symposium of Student Scholars

The utilization of online crowdsourcing platforms for data collection has increased over the past two decades in the field of public health due to the ease of use, the cost-saving benefits, the speed of the data collection process, and the accessibility of a potentially true representative population. Although these platforms offer many advantages to researchers, significant drawbacks exist, such as poor data quality, that threaten the reliability and validity of the study. Previous studies have examined data quality concerns, but differences in results arise due to variations in study designs, disciplinary contexts, and the platforms being investigated. Therefore, this study …

11.27.2023 Orsp Connect, Liz Williamson

ORED Newsletter

November 27, 2023 edition of the ORSP newsletter

A Systematic Collection Of Medical Image Datasets For Deep Learning, Johann Li, Guangming Zhu, Cong Hua, Mingtao Feng, Basheer Bennamoun, Ping Li, Xiaoyuan Lu, Juan Song, Peiyi Shen, Xu Xu, Lin Mei, Liang Zhang, Syed A. A. Shah, Mohammed Bennamoun

Research outputs 2022 to 2026

The astounding success made by artificial intelligence in healthcare and other fields proves that it can achieve human-like performance. However, success always comes with challenges. Deep learning algorithms are data dependent and require large datasets for training. Many junior researchers face a lack of data for a variety of reasons. Medical image acquisition, annotation, and analysis are costly, and their usage is constrained by ethical restrictions. They also require several other resources, such as professional equipment and expertise. That makes it difficult for novice and non-medical researchers to have access to medical data. Thus, as comprehensively as possible, this article …

Towards A Virtual Reality Visualization Of Hand-Object Interactions To Support Remote Physical Therapy, Trudi Di Qi, Louanne Boyd, Scott Fitzpatrick, Meghna Raswan, Franceli L. Cibrian

Engineering Faculty Articles and Research

Improving object manipulation skills through hand-object interaction exercises is crucial for rehabilitation. Despite limited healthcare resources, physical therapists propose remote exercise routines followed up by remote monitoring. However, remote motor skills assessment remains challenging due to the lack of effective motion visualizations. Therefore, exploring innovative ways of visualization is crucial, and virtual reality (VR) has shown the potential to address this limitation. However, it is unclear how VR visualization can represent understandable hand-object interactions. To address this gap, in this paper, we present VRMoVi, a VR visualization system that incorporates multiple levels of 3D visualization layers to depict movements. In …

Innovation Process And Industrial System Of Us Food And Drug Administration-Approved Software As A Medical Device: Review And Content Analysis, Jiakan Yu, Jiajie Zhang, Shintaro Sengoku

Faculty, Staff and Student Publications

BACKGROUND: There has been a surge in academic and business interest in software as a medical device (SaMD). SaMD enables medical professionals to streamline existing medical practices and make innovative medical processes such as digital therapeutics a reality. Furthermore, SaMD is a billion-dollar market. However, SaMD is not clearly understood as a technological change and emerging industry.

OBJECTIVE: This study aims to review the landscape of SaMD in response to increasing interest in SaMD within health systems and regulation. The objectives of the study are to (1) clarify the innovation process of SaMD, (2) identify the prevailing typology of such …

Evaluating The Efficacy Of Chatgpt In Navigating The Spanish Medical Residency Entrance Examination (Mir): Promising Horizons For Ai In Clinical Medicine., Francisco Guillen-Grima, Sara Guillen-Aguinaga, Laura Guillen-Aguinaga, Rosa Alas-Brun, Luc Onambele, Wilfrido Ortega, Rocio Montejo, Enrique Aguinaga-Ontoso, Paul Barach, Ines Aguinaga-Ontoso

Department of Medicine Faculty Papers

UNLABELLED: The rapid progress in artificial intelligence, machine learning, and natural language processing has led to increasingly sophisticated large language models (LLMs) for use in healthcare. This study assesses the performance of two LLMs, the GPT-3.5 and GPT-4 models, in passing the MIR medical examination for access to medical specialist training in Spain. Our objectives included gauging the model's overall performance, analyzing discrepancies across different medical specialties, discerning between theoretical and practical questions, estimating error proportions, and assessing the hypothetical severity of errors committed by a physician.

MATERIAL AND METHODS: We studied the 2022 Spanish MIR examination results after excluding …

11.20.2023 Orsp Connect, Liz Williamson

ORED Newsletter

ORSP Newsletter for the week of November 20, 2023.

Data-Driven Decision Support Tool Co-Development With A Primary Health Care Practice Based Learning Network, Jacqueline K. Kueper, Jennifer Rayner, Sara Bhatti, Kelly Angevaare, Sandra Fitzpatrick, Paulino Lucamba, Eric Sutherland, Daniel J. Lizotte

Epidemiology and Biostatistics Publications

Background: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project.

Methods: We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in …

Pathogenicity In Chickens And Turkeys Of A 2021 United States H5n1 Highly Pathogenic Avian Influenza Clade 2.3.4.4b Wild Bird Virus Compared To Two Previous H5n8 Clade 2.3.4.4 Viruses, Mary J. Pantin-Jackwood, Erica Spackman, Christina Leyson, Sungsu Youk, Scott A. Lee, Linda M. Moon, Mia K. Torchetti, Mary L. Killian, Julianna B. Lenoch, Darrell R. Kapczynski, David E. Swayne, David L. Suarez

United States Department of Agriculture Wildlife Services: Staff Publications

Highly pathogenic avian influenza viruses (HPAIVs) of subtype H5 of the Gs/GD/96 lineage remain a major threat to poultry due to endemicity in wild birds. H5N1 HPAIVs from this lineage were detected in 2021 in the United States (US) and since then have infected many wild and domestic birds. We evaluated the pathobiology of an early US H5N1 HPAIV (clade 2.3.4.4b, 2021) and two H5N8 HPAIVs from previous outbreaks in the US (clade 2.3.4.4c, 2014) and Europe (clade 2.3.4.4b, 2016) in chickens and turkeys. Differences in clinical signs, mean death times (MDTs), and virus transmissibility were found between chickens and …

The Transcription Factor Irf4 Determines The Anti-Tumor Immunity Of Cd8+ T Cells, Hui Yan, Yulin Dai, Xiaolong Zhang, Hedong Zhang, Xiang Xiao, Jinfei Fu, Dawei Zou, Anze Yu, Tao Jiang, Xian C Li, Zhongming Zhao, Wenhao Chen

Faculty, Staff and Student Publications

Understanding the factors that regulate T cell infiltration and functional states in solid tumors is crucial for advancing cancer immunotherapies. Here, we discovered that the expression of interferon regulatory factor 4 (IRF4) was a critical T cell intrinsic requirement for effective anti-tumor immunity. Mice with T-cell-specific ablation of IRF4 showed significantly reduced T cell tumor infiltration and function, resulting in accelerated growth of subcutaneous syngeneic tumors and allowing the growth of allogeneic tumors. Additionally, engineered overexpression of IRF4 in anti-tumor CD8+ T cells that were adoptively transferred significantly promoted their tumor infiltration and transition from a naive/memory-like cell state into …

An Open Natural Language Processing (Nlp) Framework For Ehr-Based Clinical Research: A Case Demonstration Using The National Covid Cohort Collaborative (N3c), Sijia Liu, Andrew Wen, Liwei Wang, Huan He, Sunyang Fu, Robert Miller, Andrew Williams, Daniel Harris, Ramakanth Kavuluru, Mei Liu, Noor Abu-El-Rub, Dalton Schutte, Rui Zhang, Masoud Rouhizadeh, John D Osborne, Yongqun He, Umit Topaloglu, Stephanie S Hong, Joel H Saltz, Thomas Schaffter, Emily Pfaff, Christopher G Chute, Tim Duong, Melissa A Haendel, Rafael Fuentes, Peter Szolovits, Hua Xu, Hongfang Liu

Faculty, Staff and Student Publications

Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both …

Who Sleeps Well In Canada? The Social Determinants Of Sleep Health Among Middle-Aged And Older Adults In The Canadian Longitudinal Study On Aging., Rebecca Rodrigues, Amy Jing, Kelly K. Anderson, Rea Alonzo, Piotr Wilk, Graham J Reid, Jason Gilliland, Guangyong Zou, Kathryn Nicholson, Giuseppe Guaiana, Saverio Stranges

Epidemiology and Biostatistics Publications

OBJECTIVES: Sleep health inequities likely contribute to disparities in health outcomes. Our objective was to identify social determinants of sleep health among middle-aged/older adults in Canada, where prior evidence is limited.

METHODS: We analyzed cross-sectional data from the Canadian Longitudinal Study on Aging, a survey of over 30,000 community-dwelling adults aged 45-85years. Self-reported measures included sleep duration, sleep satisfaction, and sleep efficiency. We explored associations between sleep measures and social determinants of health. We used modified Poisson regression to estimate prevalence ratios for sleep satisfaction and sleep efficiency, and linear regression for sleep duration. Estimates were adjusted for all social, …

Taking Songs To Heart: An Investigation Into Musical Appreciation, Anna Kate Lockhart, Eric A. Febles, Valeria Draine, Kaitlin Pendasulo

Science University Research Symposium (SURS)

Abstract

Music cross-culturally occupies a central part of day-to-day living (Trehub et al., 2015). Research has demonstrated music’s consistent ability to modulate emotional states, through the investigation of properties like tempo and key (Res, 2011; Bella, 2001; Jongwan,, 2018; Schellenberg, 2010). Heartbeat is a steady rhythm that each human alive and well experiences daily, and heart rate, specifically the resting heart rate, has been suggested to set a baseline rhythm that may influence perception of musical valence (Koelsch & Jancke, 2015). The current study aims to investigate this hypothesis by establishing a resting heart rate level and modulating the speed …

Impacts Of Hydrophobic Mismatch On Antimicrobial Peptide Efficacy And Bilayer Permeabilization., Steven Meier, Zachary M Ridgway, Angela L Picciano, Gregory A. Caputo

College of Science & Mathematics Departmental Research

Antimicrobial resistance continues to be a major threat to world health, with the continued emergence of resistant bacterial strains. Antimicrobial peptides have emerged as an attractive option for the development of novel antimicrobial compounds in part due to their ubiquity in nature and the general lack of resistance development to this class of molecules. In this work, we analyzed the antimicrobial peptide C18G and several truncated forms for efficacy and the underlying mechanistic effects of the sequence truncation. The peptides were screened for antimicrobial efficacy against several standard laboratory strains, and further analyzed using fluorescence spectroscopy to evaluate binding to …

Binding Interactions Of Biologically Relevant Molecules Studied Using Surface-Modified And Nanostructured Surfaces, Palak Sondhi

Dissertations

This research focuses on the field of surface nanobioscience, wherein different nanosurfaces that will be used as working electrodes in the electrochemical cell are manufactured and surface modified to understand the critical binding interactions between biologically significant molecules like proteins, carbohydrates, small drug molecules, and glycoproteins. This research is essential if we are to determine whether a synthetic molecule can serve as a therapeutic candidate or diagnose a disease in its early stages. In order to fully understand the binding interactions, the study begins with defining some of the fundamental concepts, principles, and analytical tools for biosensing.

Afterwards, we addressed …

Impact Of Climate Change On Surgery: A Scoping Review To Define Existing Knowledge And Identify Gaps, Tina Bharani, Rebecca Achey, Harris Jamal, Alexis Cherry, Malcolm K. Robinson, Guy J. Maddern, Deirdre K. Tobias, Divyansh Agarwal

Department of Surgery Faculty Papers

With climate change accelerated at a worrisome rate, global warming also will have implications for surgery and surgical practice. The goal of this current study was to systematically survey the literature and better understand how climate change has affected surgical disease burden, surgical care delivery, and surgical outcomes. We performed a comprehensive scoping review, screening 3334 unique citations from three databases – 1766 from Embase, 1329 from Pubmed and 239 from Scopus – to identify studies that had associated climate change with surgery. After systematic searching, quality appraisal, and data extraction, we synthesized findings from qualitative and quantitative studies. Twenty-six …