Comparative analysis of hospitalization risk for incident heart failure in non-Hispanic Black versus non-Hispanic White individuals with type 2 diabetes on empagliflozin (Empa-AA): Insights from real-world data.

AIM: There are limited data to evaluate hospitalization for heart failure (hHF) in non-Hispanic Black (hereafter Black) or non-Hispanic White (hereafter White) individuals without previous hHF. Our goal was to evaluate the risk of hHF among Black versus White patients with type 2 diabetes (T2DM) who were initially prescribed empagliflozin using real-world data. METHODS: This multicentre retrospective cohort study included participants aged ≥18 years who had T2DM, were either Black or White, had no previous hHF, and were prescribed empagliflozin between August 2014 and December 2019. Our primary outcome was time to first hHF after the initial prescription of empagliflozin. A propensity-score (PS)-weighted analysis was performed to balance characteristics by race. The inverse probability treatment weighting method based on PS was used to make treatment comparisons. To compare Black with White, a PS-weighted Cox's cause-specific hazards model was used. RESULTS: In total, 8789 participants were eligible for inclusion (Black = 3216 vs. White = 5573). The Black cohort was significantly younger, had a higher proportion of females, and had a higher prevalence of chronic kidney disease, hypertension and diabetic retinopathy, while the White cohort had a higher prevalence of coronary artery disease. After adjustment for confounding factors such as age, gender, coronary artery disease, hypertension and diabetic retinopathy, the hazard ratio for first-time hHF was not significantly different between the two racial groups [hazard ratio (95% confidence interval) = 1.09 (0.84-1.42), p = .52]. CONCLUSION: This study showed no significant difference in incident hHF among Black versus White individuals with T2DM following a prescription for empagliflozin.

Seek and you shall find: Yersinia enterocolitica in Ireland's drinking water.

INTRODUCTION: Three Yersinia species were identified from samples of drinking water from diverse geographic regions of Ireland. Conventional commercial biochemical identification systems classified them as Yersinia enterocolitica. Since this organism is the most common cause of bacterial gastroenteritis in some countries, further investigation was warranted. The aim of the study was to provide a microbial characterisation of three Yersinia species, to determine their pathogenicity, and to review the incidence rate of Yersinia enterocolitica detection in our region. METHODS: Organism identification was performed using conventional commercial diagnostic systems MALDI-TOF, API 20E, API 50CHE, TREK Sensititre GNID and Vitek 2 GN, and whole genome sequencing (WGS) was performed. Historical data for detections was extracted from the lab system for 2008 to 2023. RESULTS: All three isolates gave "good" identifications of Yersinia enterocolitica on conventional systems. Further analysis by WGS matched two of the isolates with recently described Yersinia proxima, and the third was a member of the non-pathogenic Yersinia enterocolitica clade 1Aa. DISCUSSION: Our analysis of these three isolates deemed them to be Yersinia species not known currently to be pathogenic, but determining this necessitated the use of next-generation sequencing and advanced bioinformatics. Our work highlights the importance of having this technology available to public laboratories, either locally or in a national reference laboratory. The introduction of molecular technologies for the detection of Yersinia species may increase the rate of detections. Accurate identification of significant pathogens in environmental, public health and clinical microbiology laboratories is critically important for the protection of society.

Dust storms increase the tolerance of phytoplankton to thermal and pH changes.

Aquatic communities are increasingly subjected to multiple stressors through global change, including warming, pH shifts, and elevated nutrient concentrations. These stressors often surpass species tolerance range, leading to unpredictable consequences for aquatic communities and ecosystem functioning. Phytoplankton, as the foundation of the aquatic food web, play a crucial role in controlling water quality and the transfer of nutrients and energy to higher trophic levels. Despite the significance in understanding the effect of multiple stressors, further research is required to explore the combined impact of multiple stressors on phytoplankton. In this study, we used a combination of crossed experiment and mechanistic model to analyze the ecological and biogeochemical effects of global change on aquatic ecosystems and to forecast phytoplankton dynamics. We examined the effect of dust (0-75 mg L-1 ), temperature (19-27°C), and pH (6.3-7.3) on the growth rate of the algal species Scenedesmus obliquus. Furthermore, we carried out a geospatial analysis to identify regions of the planet where aquatic systems could be most affected by atmospheric dust deposition. Our mechanistic model and our empirical data show that dust exerts a positive effect on phytoplankton growth rate, broadening its thermal and pH tolerance range. Finally, our geospatial analysis identifies several high-risk areas including the highlands of the Tibetan Plateau, western United States, South America, central and southern Africa, central Australia as well as the Mediterranean region where dust-induced changes are expected to have the greatest impacts. Overall, our study shows that increasing dust storms associated with a more arid climate and land degradation can reverse the negative effects of high temperatures and low pH on phytoplankton growth, affecting the biogeochemistry of aquatic ecosystems and their role in the cycles of the elements and tolerance to global change.

Increasing multi-hazard climate risk and financial and health impacts on northern homeowners.

Currently, more than half of the world's human population lives in urban areas, which are increasingly affected by climate hazards. Little is known about how multi-hazard environments affect people, especially those living in urban areas in northern latitudes. This study surveyed homeowners in Anchorage and Fairbanks, USA, Alaska's largest urban centers, to measure individual risk perceptions, mitigation response, and damages related to wildfire, surface ice hazards, and permafrost thaw. Up to one third of residents reported being affected by all three hazards, with surface ice hazards being the most widely distributed, related to an estimated $25 million in annual damages. Behavioral risk response, policy recommendations for rapidly changing urban environments, and the challenges to local governments in mitigation efforts are discussed.

RFS+: A Clinically Adaptable and Computationally Efficient Strategy for Enhanced Brain Tumor Segmentation.

Automated brain tumor segmentation has significant importance, especially for disease diagnosis and treatment planning. The study utilizes a range of MRI modalities, namely T1-weighted (T1), T1-contrast-enhanced (T1ce), T2-weighted (T2), and fluid-attenuated inversion recovery (FLAIR), with each providing unique and vital information for accurate tumor localization. While state-of-the-art models perform well on standardized datasets like the BraTS dataset, their suitability in diverse clinical settings (matrix size, slice thickness, manufacturer-related differences such as repetition time, and echo time) remains a subject of debate. This research aims to address this gap by introducing a novel 'Region-Focused Selection Plus (RFS+)' strategy designed to efficiently improve the generalization and quantification capabilities of deep learning (DL) models for automatic brain tumor segmentation. RFS+ advocates a targeted approach, focusing on one region at a time. It presents a holistic strategy that maximizes the benefits of various segmentation methods by customizing input masks, activation functions, loss functions, and normalization techniques. Upon identifying the top three models for each specific region in the training dataset, RFS+ employs a weighted ensemble learning technique to mitigate the limitations inherent in each segmentation approach. In this study, we explore three distinct approaches, namely, multi-class, multi-label, and binary class for brain tumor segmentation, coupled with various normalization techniques applied to individual sub-regions. The combination of different approaches with diverse normalization techniques is also investigated. A comparative analysis is conducted among three U-net model variants, including the state-of-the-art models that emerged victorious in the BraTS 2020 and 2021 challenges. These models are evaluated using the dice similarity coefficient (DSC) score on the 2021 BraTS validation dataset. The 2D U-net model yielded DSC scores of 77.45%, 82.14%, and 90.82% for enhancing tumor (ET), tumor core (TC), and the whole tumor (WT), respectively. Furthermore, on our local dataset, the 2D U-net model augmented with the RFS+ strategy demonstrates superior performance compared to the state-of-the-art model, achieving the highest DSC score of 79.22% for gross tumor volume (GTV). The model utilizing RFS+ requires 10% less training dataset, 67% less memory and completes training in 92% less time compared to the state-of-the-art model. These results confirm the effectiveness of the RFS+ strategy for enhancing the generalizability of DL models in brain tumor segmentation.

The microbial pathology of maternal perinatal sepsis: A single-institution retrospective five-year review.

INTRODUCTION: Greater than half of in-hospital maternal deaths are caused by sepsis, a condition that occurs when infection exceeds local tissue containment and results in organ dysfunction. Determining the source of infection can be challenging. Microbiological cultures of the uterine cavity are often difficult to obtain, so antimicrobial susceptibility results may not be available to guide treatment. The aim of this retrospective study was to assess the potential clinical value of microbiology samples used in the maternal "septic screen" of patients in an Irish maternity hospital. METHODS: A review was completed of all maternal "septic screen" (i.e., high vaginal swabs, placenta swabs, blood cultures, throat swabs and urine samples) microbiology results from July 2016 to December 2021. RESULTS: In the relevant period, 845 patients were subject to a "septic screen", of whom 430 also had a placental swab collected. These 430 patients comprise our study population. 2% of blood cultures yielded potential pathogens, compared with 37%, 33%, 9% and 7% respectively for placental swabs, high vaginal swabs, throat swabs and urine specimens. 95% of blood cultures were sterile, compared with 52%, 0%, 0% and 53% respectively for placental swabs, high vaginal swabs, throat swabs and urine specimens. CONCLUSION: Of the five microbiological specimen types examined, placental swabs yielded the highest number of potential pathogens. Our results suggest that placental swabs are useful specimens for detecting potential pathogens from the uterine cavity, the most common source of perinatal infections.

Effect of Intensive Blood Pressure Control on Kidney Outcomes: Long-Term Electronic Health Record-Based Post-Trial Follow-Up of SPRINT.

BACKGROUND: Intensive BP lowering in the Systolic Blood Pressure Intervention Trial (SPRINT) produced acute decreases in kidney function and higher risk for AKI. We evaluated the effect of intensive BP lowering on long-term changes in kidney function using trial and outpatient electronic health record (EHR) creatinine values. METHODS: SPRINT data were linked with EHR data from 49 (of 102) study sites. The primary outcome was the total slope of decline in eGFR for the intervention phase and the post-trial slope of decline during the observation phase using trial and outpatient EHR values. Secondary outcomes included a ≥30% decline in eGFR to <60 ml/min per 1.73 m 2 and a ≥50% decline in eGFR or kidney failure among participants with baseline eGFR ≥60 and <60 ml/min per 1.73 m 2 , respectively. RESULTS: EHR creatinine values were available for a median of 8.3 years for 3041 participants. The total slope of decline in eGFR during the intervention phase was -0.67 ml/min per 1.73 m 2 per year (95% confidence interval [CI], -0.79 to -0.56) in the standard treatment group and -0.96 ml/min per 1.73 m 2 per year (95% CI, -1.08 to -0.85) in the intensive treatment group ( P < 0.001). The slopes were not significantly different during the observation phase: -1.02 ml/min per 1.73 m 2 per year (95% CI, -1.24 to -0.81) in the standard group and -0.85 ml/min per 1.73 m 2 per year (95% CI, -1.07 to -0.64) in the intensive group. Among participants without CKD at baseline, intensive treatment was associated with higher risk of a ≥30% decline in eGFR during the intervention (hazard ratio, 3.27; 95% CI, 2.43 to 4.40), but not during the postintervention observation phase. In those with CKD at baseline, intensive treatment was associated with a higher hazard of eGFR decline only during the intervention phase (hazard ratio, 1.95; 95% CI, 1.03 to 3.70). CONCLUSIONS: Intensive BP lowering was associated with a steeper total slope of decline in eGFR and higher risk for kidney events during the intervention phase of the trial, but not during the postintervention observation phase.

Annual incidence and assessment of risk factors for early-onset deep surgical site infection following primary total knee arthroplasty in osteoarthritis.

Aims: This study aims to determine difference in annual rate of early-onset (≤ 90 days) deep surgical site infection (SSI) following primary total knee arthroplasty (TKA) for osteoarthritis, and to identify risk factors that may be associated with infection. Methods: This is a retrospective population-based cohort study using prospectively collected patient-level data between 1 January 2013 and 1 March 2020. The diagnosis of deep SSI was defined as per the Centers for Disease Control/National Healthcare Safety Network criteria. The Mann-Kendall Trend test was used to detect monotonic trends in annual rates of early-onset deep SSI over time. Multiple logistic regression was used to analyze the effect of different patient, surgical, and healthcare setting factors on the risk of developing a deep SSI within 90 days from surgery for patients with complete data. We also report 90-day mortality. Results: A total of 39,038 patients underwent primary TKA for osteoarthritis during the study period. Of these, 275 patients developed a deep SSI within 90 days of surgery, representing a cumulative incidence of 0.7%. The annual infection rate did not significantly decrease over the seven-year study period (p = 0.162). Overall, 13,885 (35.5%) cases were excluded from the risk analysis due to missing data. Risk factors associated with early-onset deep SSI included male sex, American Society of Anesthesiologists grade ≥ 3, blood transfusion, acute length of stay, and surgeon volume < 30 TKAs/year. Early-onset deep SSI was not associated with increased 90-day mortality. Conclusion: This study establishes a reliable baseline infection rate for early-onset deep SSI after TKA for osteoarthritis using robust Infection Prevention and Control surveillance data, and identifies several potentially modifiable risk factors.

Antimicrobial Resistance Is Prevalent in E. coli and Other Enterobacterales Isolated from Public and Private Drinking Water Supplies in the Republic of Ireland.

High levels of bacterial antimicrobial resistance (AMR) have been reported in many environmental studies conducted in Ireland and elsewhere. The inappropriate use of antibiotics in both human and animal healthcare as well as concentrations of residual antibiotics being released into the environment from wastewaters are thought to be contributing factors. Few reports of AMR in drinking water-associated microbes are available for Ireland or internationally. We analysed 201 enterobacterales from group water schemes and public and private water supplies, only the latter having been surveyed in Ireland previously. The organisms were identified using conventional or molecular techniques. Antimicrobial susceptibility testing for a range of antibiotics was performed using the ARIS 2X interpreted in accordance with EUCAST guidelines. A total of 53 Escherichia coli isolates, 37 Serratia species, 32 Enterobacter species and enterobacterales from seven other genera were identified. A total of 55% of isolates were amoxicillin resistant, and 22% were amoxicillin-clavulanic acid resistant. A lower level of resistance (<10%) was observed to aztreonam, chloramphenicol, ciprofloxacin, gentamicin, ceftriaxone and trimethoprim-sulfamethoxazole. No resistance to amikacin, piperacillin/tazobactam, ertapenem or meropenem was detected. The level of AMR detected in this study was low but not insignificant and justifies ongoing surveillance of drinking water as a potential source of antimicrobial resistance.

Concordance between clinical outcomes in the Systolic Blood Pressure Intervention Trial and in the electronic health record.

BACKGROUND: Randomized trials are the gold standard for generating clinical practice evidence, but follow-up and outcome ascertainment are resource-intensive. Electronic health record (EHR) data from routine care can be a cost-effective means of follow-up, but concordance with trial-ascertained outcomes is less well-studied. METHODS: We linked EHR and trial data for participants of the Systolic Blood Pressure Intervention Trial (SPRINT), a randomized trial comparing intensive and standard blood pressure targets. Among participants with available EHR data concurrent to trial-ascertained outcomes, we calculated sensitivity, specificity, positive predictive value, and negative predictive value for EHR-recorded cardiovascular disease (CVD) events, using the gold standard of SPRINT-adjudicated outcomes (myocardial infarction (MI)/acute coronary syndrome (ACS), heart failure, stroke, and composite CVD events). We additionally compared the incidence of non-CVD adverse events (hyponatremia, hypernatremia, hypokalemia, hyperkalemia, bradycardia, and hypotension) in trial versus EHR data. RESULTS: 2468 SPRINT participants were included (mean age 68 (SD 9) years; 26% female). EHR data demonstrated ≥80% sensitivity and specificity, and ≥ 99% negative predictive value for MI/ACS, heart failure, stroke, and composite CVD events. Positive predictive value ranged from 26% (95% CI; 16%, 38%) for heart failure to 52% (95% CI; 37%, 67%) for MI/ACS. EHR data uniformly identified more non-CVD adverse events and higher incidence rates compared with trial ascertainment. CONCLUSIONS: These results support a role for EHR data collection in clinical trials, particularly for capturing laboratory-based adverse events. EHR data may be an efficient source for CVD outcome ascertainment, though there is clear benefit from adjudication to avoid false positives.

Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium.

OBJECTIVE: To report imaging protocol and scheduling variance in routine care of glioblastoma patients in order to demonstrate challenges of integrating deep-learning models in glioblastoma care pathways. Additionally, to understand the most common imaging studies and image contrasts to inform the development of potentially robust deep-learning models. METHODS: MR imaging data were analysed from a random sample of five patients from the prospective cohort across five participating sites of the ZGBM consortium. Reported clinical and treatment data alongside DICOM header information were analysed to understand treatment pathway imaging schedules. RESULTS: All sites perform all structural imaging at every stage in the pathway except for the presurgical study, where in some sites only contrast-enhanced T1-weighted imaging is performed. Diffusion MRI is the most common non-structural imaging type, performed at every site. CONCLUSION: The imaging protocol and scheduling varies across the UK, making it challenging to develop machine-learning models that could perform robustly at other centres. Structural imaging is performed most consistently across all centres. ADVANCES IN KNOWLEDGE: Successful translation of deep-learning models will likely be based on structural post-treatment imaging unless there is significant effort made to standardise non-structural or peri-operative imaging protocols and schedules.

Dermatology mycology diagnostics in Ireland: National deficits identified in 2022 that are relevant internationally.

BACKGROUND: Conventional testing methods for dermatophytes are time-consuming, and resource limitations in our institution have prompted curtailed access to these diagnostics. OBJECTIVES: Evaluation of our hospital's dermatological mycology diagnostic services and similar services nationally. METHODS: This was a retrospective observational study on skin, hair and nail mycology samples in our institution comparing twenty five-year periods (2011-2015 and 2016-2021), including analysis of dermatology clinic data and correspondence related to fungal infection. A survey of national public hospitals' laboratories was conducted to evaluate their mycology testing capabilities. RESULTS: The total 5 year test count prior to curtailment was 4851 specimens comprising 90% (n = 4344) from general practice and 6% (n = 290) from dermatology clinics. For the 5 years post curtailment, 64.5% (582/903) of specimens were from dermatology clinics. Dermatology clinic data demonstrated doubling of attendances (for all conditions) and of correspondence related to fungal infection. During this time also, national dermatological antifungal purchasing increased 11%. Ten of 28 Irish public hospital laboratories reported the provision of in-house dermatological mycology testing, and none had routine availability of susceptibility or molecular testing of dermatophytes. CONCLUSION: This study is the first to report an appraisal of dermatological fungal diagnostic services in Ireland. Insufficient testing capacity implies that patients are either being treated for fungal infection without appropriate diagnostic confirmation, or being left untreated because of the lack of access to diagnostics. The introduction of molecular detection methods and susceptibility systems would enhance testing capabilities and reduce the requirement for the external referral.

Outcomes After Liver Transplantation With Incidental Cholangiocarcinoma.

Cholangiocarcinoma (CCA) is currently a contraindication to liver transplantation (LT) in the United Kingdom (UK). Incidental CCA occurs rarely in some patients undergoing LT. We report on retrospective outcomes of patients with incidental CCA from six UK LT centres. Cases were identified from pathology records. Data regarding tumour characteristics and post-transplant survival were collected. CCA was classified by TNM staging and anatomical location. 95 patients who underwent LT between 1988-2020 were identified. Median follow-up after LT was 2.1 years (14 days-18.6 years). Most patients were male (68.4%), median age at LT was 53 (IQR 46-62), and the majority had underlying PSC (61%). Overall median survival after LT was 4.4 years. Survival differed by tumour site: 1-, 3-, and 5-year estimated survival was 82.1%, 68.7%, and 57.1%, respectively, in intrahepatic CCA (n = 40) and 58.5%, 42.6%, and 30.2% in perihilar CCA (n = 42; p = 0.06). 1-, 3-, and 5-year estimated survival was 95.8%, 86.5%, and 80.6%, respectively, in pT1 tumours (28.2% of cohort), and 65.8%, 44.7%, and 31.1%, respectively, in pT2-4 (p = 0.018). Survival after LT for recipients with incidental CCA is inferior compared to usual outcomes for LT in the United Kingdom. LT for earlier stage CCA has similar survival to LT for hepatocellular cancer, and intrahepatic CCAs have better survival compared to perihilar CCAs. These observations may support LT for CCA in selected cases.

The first assessment of the genetic diversity and structure of the endangered West Indian manatee in Cuba.

The coastal waters of Cuba are home to a small, endangered population of West Indian manatee, which would benefit from a comprehensive characterization of the population's genetic variation. We conducted the first genetic assessment of Cuban manatees to determine the extent of the population's genetic structure and characterize the neutral genetic diversity among regions within the archipelago. We genotyped 49 manatees at 18 microsatellite loci, a subset of 27 samples on 1703 single nucleotide polymorphisms (SNPs), and sequenced 59 manatees at the mitochondrial control region. The Cuba manatee population had low nuclear (microsatellites HE = 0.44, and SNP HE = 0.29) and mitochondrial genetic diversity (h = 0.068 and π = 0.00025), and displayed moderate departures from random mating (microsatellite FIS = 0.12, SNP FIS = 0.10). Our results suggest that the western portion of the archipelago undergoes periodic exchange of alleles based on the evidence of shared ancestry and low but significant differentiation. The southeast Guantanamo Bay region and the western portion of the archipelago were more differentiated than southwest and northwest manatees. The genetic distinctiveness observed in the southeast supports its recognition as a demographically independent unit for natural resource management regardless of whether it is due to historical isolation or isolation by distance. Estimates of the regional effective population sizes, with the microsatellite and SNP datasets, were small (all Ne < 60). Subsequent analyses using additional samples could better examine how the observed structure is masking simple isolation by distance patterns or whether ecological or biogeographic forces shape genetic patterns.

Oviposition Model for a Southern Population of Mountain Pine Beetle.

We develop a predictive oviposition model for a southern population of mountain pine beetle (MPB) using a previously developed rate curve, incorporating variation in both oviposition rate and fecundity. We also introduce a method for determining the time delay before oviposition. The model describes the probability of oviposition for a season of MPB attacks using hourly phloem temperature and adult MPB attack data. We also develop an asymptotic approximation of MPB oviposition that is much less computationally taxing. The detailed oviposition model and its asymptotic approximation are compared with other ovipositional models for MPB; the predictive capacity of each model is evaluated using previously published observations.

Effect of Intensive versus Standard BP Control on AKI and Subsequent Cardiovascular Outcomes and Mortality: Findings from the SPRINT EHR Study.

Background: Adjudication of inpatient AKI in the Systolic Blood Pressure Intervention Trial (SPRINT) was based on billing codes and admission and discharge notes. The purpose of this study was to evaluate the effect of intensive versus standard BP control on creatinine-based inpatient and outpatient AKI, and whether AKI was associated with cardiovascular disease (CVD) and mortality. Methods: We linked electronic health record (EHR) data from 47 clinic sites with trial data to enable creatinine-based adjudication of AKI. Cox regression was used to evaluate the effect of intensive BP control on the incidence of AKI, and the relationship between incident AKI and CVD and all-cause mortality. Results: A total of 3644 participants had linked EHR data. A greater number of inpatient AKI events were identified using EHR data (187 on intensive versus 155 on standard treatment) as compared with serious adverse event (SAE) adjudication in the trial (95 on intensive versus 61 on standard treatment). Intensive treatment increased risk for SPRINT-adjudicated inpatient AKI (HR, 1.51; 95% CI, 1.09 to 2.08) and for creatinine-based outpatient AKI (HR, 1.40; 95% CI, 1.15 to 1.70), but not for creatinine-based inpatient AKI (HR, 1.20; 95% CI, 0.97 to 1.48). Irrespective of the definition (SAE or creatinine based), AKI was associated with increased risk for all-cause mortality, but only creatinine-based inpatient AKI was associated with increased risk for CVD. Conclusions: Creatinine-based ascertainment of AKI, enabled by EHR data, may be more sensitive and less biased than traditional SAE adjudication. Identifying ways to prevent AKI may reduce mortality further in the setting of intensive BP control.

Diabetes-Related Microvascular Complications - A Practical Approach.

Diabetes-related microvascular complications include diabetic neuropathy (eg, diabetic symmetric polyneuropathy (DSPN), cardiac autonomic neuropathy, gastroparesis, enteropathy, erectile dysfunction, female sexual dysfunction, and hypoglycemia unawareness), diabetic kidney disease (DKD), and diabetes-related eye disease (eg, diabetic retinopathy (DR) and cataract). Both diabetes duration and degree of glycemic control strongly correlate with the development of microvascular complications. The development of diabetes-related microvascular complications interferes with the patient's quality of life and poses higher health system costs. This article will discuss a practical approach to effectively minimize/delay and manage the most common diabetes-related microvascular (DSPN, DKD, and DR).

Epidemiology of dermatomycoses and onychomycoses in Ireland (2001-2020): A single-institution review.

BACKGROUND: Fungal skin infections are recognised as one of the most common health disorders globally, and dermatophyte infections of the skin, hair and nails are the most common fungal infections. Dermatophytes can be classified as anthropophilic, zoophilic or geophilic species based on their primary habitat association, and this classification makes epidemiological analysis useful for the prevention and control of these infections. The Irish contribution to the epidemiology of these infections has been scant, with just two papers (both reporting paediatric tinea capitis only) published in the last 20 years, and none in the last seven. OBJECTIVES: To perform a comprehensive retrospective epidemiological analysis of all dermatological mycology tests performed in University Hospital Limerick over a 20-year period. METHODS: All mycology laboratory test results were extracted from the Laboratory Information Management System (LIMS, iLab, DXC Technologies) from 2001 to 2020 inclusive for analysis. Specimen types were categorised according to the site of sampling. The data were analysed using Microsoft Excel. RESULTS: About 12,951 specimens of skin, hair and nails were studied. Median patient age was 42 years (IQR 26-57) with a slight female preponderance (57.2%). Two thirds of samples (67%, n = 8633) were nail, 32% were skin scrapings (n = 4118) and 200 hair samples (1.5%) were received. Zoophilic dermatophytes were more commonly present in females (38% F, 23% M, proportion of dermatophytes) and in those under 10 years of age or from 45 to 70 years (36% and 34% zoophiles, respectively, proportion of dermatophytes), although anthropophiles predominated every age and gender category. Anthropophiles had their highest prevalence in the 10-20 years age category (80% anthropophiles, proportion of dermatophytes), and yeast infections were more prevalent in older patients (29% of >60 year olds vs. 17% of <60 year olds, proportion of all fungal positives). Trichophyton rubrum was the most prevalent pathogen detected, accounting for 53% of all dermatophytes detected, 61% of those detected from nail samples and 34% from skin and hair samples. Trichophyton tonsurans was the most prevalent dermatophyte in tinea capitis, accounting for 37% of dermatophytes detected. Both of these organisms are anthropophilic, and this group showed consistently increased prevalence in proportion to all fungal isolates. The proportion of this dermatophyte class (anthropophiles) increased among both nail samples and skin/hair samples during the study period, from 55% of samples in the first 5 years of the study (2001-2005) to 88% (proportion of dermatophytes) in the final 5 years. Conversely, yeast detection decreased. CONCLUSIONS: This study provides a detailed overview of the epidemiology of the fungal cultures of skin, nail and hair samples in the Mid-West of Ireland over a 20-year period. Monitoring this changing landscape is important in identifying likely sources of infections, to identifying potential outbreaks, and may help guide empiric treatment. To the best of our knowledge, this study provides the first detailed analysis from Ireland of fungal detections from skin, hair and nail samples, and is the first epidemiological fungal report of any kind in over 7 years.