Incidence and prevalence of Amyotrophic Lateral Sclerosis in three Italian Regions: a study based on health administrative databases.

OBJECTIVES: to estimate Amyotrophic Lateral Sclerosis (ALS) incidence and prevalence in three Italian Regions (Lazio, Tuscany, and Umbria), using health administrative databases. DESIGN: retrospective population-based study. SETTING AND PARTICIPANTS: ALS patients residing in Lazio, Umbria, and Tuscany were identified through an algorithm based on three different administrative databases: hospital discharge records, exemptions from health care co-payment, and emergency departments (study period 2014-2019). Crude, age- and gender-specific prevalence were calculated on 31.12.2019 and incidence rates of ALS were standardised by region, year, and gender between 2014-2019. Using a clinical dataset available in the Lazio Region, the proportion of individuals residing in the region correctly identified as ALS cases by the algorithm were calculated. MAIN OUTCOMES MEASURES: prevalence and incidence rates. RESULTS: a total of 1,031 ALS patients (>=18 years) were identified: 408 cases in Tuscany, 546 in Lazio, and 77 in Umbria. ALS standardised prevalence (per 100,000) was similar among regions: 12.31 in Tuscany, 11.52 in Lazio, and 9.90 in Umbria. The 5-year crude rates were higher in men, and in people aged 65-79 years. Among 310 patients included in the clinical dataset, 263 (84.8%) were correctly identified by the algorithm based on health administrative databases. CONCLUSIONS: ALS prevalence and incidence in three Central Italy Regions are rather similar, but slightly higher than those previously reported. This finding is plausible, given that previous results relate to at least ten years ago and evidenced increasing trends. Overall, the results of this paper encourage the use of administrative data to produce occurrence estimates, useful to both epidemiological surveillance and research and healthcare policies.

Impact of COVID-19 on work loss in the United States- A retrospective database analysis.

OBJECTIVES: This study investigates the utilization of work absence benefits among United States (US) employees diagnosed with COVID-19, examining frequency, duration, cost, and types of work loss benefits used. METHODS: This retrospective analysis of the Workpartners Research Reference Database (RRDb) included employees eligible for short- and long-term disability (STD and LTD employer-sponsored benefits, respectively), and other paid work absence benefits from 2018 to 2022. Workpartners RRDb includes over 3.5 million employees from over 500 self-insured employers across the US. Employees were identified by codes from adjudicated medical and disability claims for COVID-19 (2020-2022) and influenza, as well as prescription claims for COVID-19 treatments. Associated payments were quantified for each absence reason. RESULTS: Approximately 1 million employees were eligible for employer-sponsored paid leave benefits between January 2018 and December 2022. The mean age was 37 years (22% >50 years), and 49.4% were females. COVID-19 was the 2nd most common reason for an STD claim (6.9% of all STD claims) and 13th for an LTD claim (1.7% of all LTD claims) from 2020-2022. The mean duration for COVID-19 STD claims was 24 days (N = 3,731, mean claim=$3,477) versus 10 days for influenza (N = 283, mean claim=$1,721). The mean duration for an LTD claim for COVID-19 was 153 days (N = 11, mean claim=$19,254). Only 21.5% of employees with STD claims in the COVID-19 cohort had prior COVID-19-associated medical or pharmacy claims; over half (range 53%-61%) had documented high risk factors for severe COVID-19. CONCLUSION: COVID-19 and influenza have the potential to cause work loss in otherwise healthy employees. In this analysis, COVID-19 was the second most frequent reason for an STD claim at the start of the pandemic and remained high (ranked 5th) in 2022. These results highlight the impact of COVID-19 on work loss beyond the acute phase. Comprehensively evaluating work loss implications may help employers prioritize strategies, such as vaccinations and timely treatments, to mitigate the impact of COVID-19 on employees and their companies.

COVID-19 results in short- and long-term symptoms that may affect employees' ability to work. Short- and long-term disability (STD and LTD, respectively), other work absences, and medical and pharmacy claims from the Workpartners Research Reference Database were analyzed for US adult (≥18 years) employees. COVID-19 claims were identified using the Center for Disease Control and Prevention recommended International Classification of Diseases codes during the analysis from 2020 to 2022. During 2020 to 2022, COVID-19 ranked as the second most frequent reason for STD claims and 13th most frequent among LTD claims. Influenza ranked 58th overall with no LTD claims (2018­2022). The average COVID-19 STD claim lasted 24 days and cost employers $3,477 per claim, and LTD claims averaged 153 days, costing $19,254. Only 21.5% of employees with STD claims in the COVID-19 cohort had prior COVID-19-associated medical or pharmacy claims, and over half (range 53%­61%) had a documented high-risk factor for severe COVID-19. Our results highlight the ongoing and substantial impact of COVID-19 on work absence benefit utilization beyond the acute phase. This analysis demonstrates the need for employers and researchers to review all available medical, pharmacy, and disability claims to assess the acute and long-term impact of COVID-19 on employees and prioritize mitigation strategies to reduce the burden of the virus to their employees.

Pediatric Complex Chronic Condition System Version 3.

Importance: Since implementation of the International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in the US, thousands of new or related codes have been added to represent clinical conditions. The widely used pediatric complex chronic condition (CCC) system required a major update from version 2 (V2) to version 3 (V3) to capture the range of clinical conditions represented in the ICD-10-CM. Objective: To update the CCC V3 system, creating V3, with new, missing, or retired codes; to reconceptualize the system's use of technology codes; and to compare CCC V3 with V2. Design, Setting, and Participants: This repeated cross-sectional study examined US hospitalization data from the Pediatric Health Information System (PHIS) and the Medicaid Merative MarketScan Research Databases from January 1, 2009, to December 31, 2019, for all patients aged 0 to 18 years. Data were analyzed from March 1, 2023, to April 1, 2024. Exposures: The CCCs were identified in both data sources using the CCC V2 and V3 systems. Main Outcomes and Measures: The (1) percentage of pediatric hospitalizations associated with a CCC, (2) numbers of CCC body-system categories per patient, and (3) explanatory power for hospital length of stay and in-hospital mortality were compared over time for V3 vs V2. Results: Among 7 186 019 hospitalizations within PHIS, 54.3% patients were male, the median age was 4 years (IQR, 1-11 years), and 51.2% were aged 0 to 4 years). The CCC V2 identified 2 878 476 (40.1%) patients as having any CCC compared with 2 753 412 (38.3%) identified by V3. In addition, V2 identified 100 065 (1.4%) patients with transplant status compared with 146 683 (2.0%) by V3, and V2 identified 914 835 (12.7%) as having technology codes compared with 805 585 (11.2%) by V3. The 2 systems were similar in accounting for the number of CCC body-system categories per patient and in explaining variation in hospital length of stay and in-hospital mortality. For both V2 and V3, 10.0% of the variance in hospital length of stay and 12.0% of the variance in in-hospital mortality was explained by the presence of a CCC. Similar patterns were observed when analyzing the 2 999 420 Medicaid Merative MarketScan Research Databases' hospitalizations (52.3% of patients were male, the median age was 1 year [IQR, 0-12 years], and 62.0% were 0 to 4 years old), except that the percentages of identified CCCs were all lower: V2 identified 758 110 hospitalizations (25.3%) with any CCC compared with 718 100 (23.9%) identified by V3. Conclusions and Relevance: These results suggest that, moving forward, V3 should be used to identify CCCs, and ongoing, frequent updates to V3, using a transparent, structured process, will enable V3 to accurately reflect the evolving spectrum of clinical conditions represented in the ICD-10-CM.

Overview of clinical status, treatment, and long-term outcomes of pediatric autosomal-dominant polycystic kidney disease: a nationwide survey in Taiwan.

This retrospective study investigated the incidence, medication use, and outcomes in pediatric autosomal-dominant polycystic kidney disease (ADPKD) using Taiwan's National Health Insurance Research Database (NHIRD). A 1:4 matched control group of individuals included in the NHIRD during the same period was used for comparative analyses. A total of 621 pediatric patients were identified from 2009 to 2019 (mean age, 9.51 ± 6.43 years), and ADPKD incidence ranged from 2.32 to 4.45 per 100,000 individuals (cumulative incidence, 1.26-1.57%). The incidence of newly developed hypertension, anti-hypertensive agent use, nephrolithiasis, and proteinuria were significantly higher in the ADPKD group than the non-ADPKD group (0.7 vs. 0.04, 2.26 vs. 0.30, 0.4 vs. 0.02, and 0.73 vs. 0.05 per 100 person-years, respectively). The adjusted hazard ratios for developing hypertension, proteinuria, nephrolithiasis and anti-hypertensive agent use in cases of newly-diagnosed pediatric ADPKD were 12.36 (95% CI 4.92-31.0), 13.49 (95% CI 5.23-34.79), 13.17 (95% CI 2.48-69.98), and 6.38 (95% CI 4.12-9.89), respectively. The incidence of congenital cardiac defects, hematuria, urinary tract infections, gastrointestinal diverticulosis, dyslipidemia, and hyperuricemia were also higher in the ADPKD group. Our study offers valuable insights into the epidemiology of pediatric ADPKD in Taiwan and could help in formulating guidelines for its appropriate management.

A protocol for neoWONDER: Neonatal whole population data linkage to improve long-term health and wellbeing of preterm and sick babies.

INTRODUCTION: Early-life medical and surgical interventions in babies born preterm and/or with surgical conditions influence later life health and educational outcomes. Obtaining long-term outcomes post-discharge to evaluate the impact of interventions is complex, expensive, and burdensome to families. Linkage of routinely collected data offers a feasible and cost-effective solution. The NeoWONDER research programme aims to describe the short and long-term health and educational outcomes for babies born preterm and/or with surgical conditions and evaluate the impact of neonatal care and interventions on later health and educational outcomes. METHODS AND ANALYSIS: We will include babies who received care in neonatal units in England and Wales, born between 2007-2020 with a gestational age below 32 weeks (approximately 100,000), and/or born between 2012-2020 (all gestations) with any of six surgical conditions: necrotising enterocolitis, Hirschsprung's disease, gastroschisis, oesophageal atresia, congenital diaphragmatic hernia, and posterior urethral valves (approximately 8,000). A detailed list of surgical condition codes is shown in S3 File. We will obtain long-term health and education outcomes through linkage of the National Neonatal Research Database, which contains routine data for all babies admitted to NHS neonatal units, to other existing health and educational datasets. For England, these are: Hospital Episode Statistics, the Office for National Statistics, Mental Health Services Dataset, Paediatric Intensive Care Audit Network, National Pupil Database; and for Wales, the Secure Anonymised Information Linkage databank. Analysis will be undertaken on de-identified linked datasets. Outcomes of interest for health include mortality, hospital admissions, diagnoses indicative of neurodisability and/or chronic illness, health care utilisation; and for education are attainment (using national curriculum assessments), school absence and special educational needs status.

Estimates of the excess cost burden of Ehlers-Danlos syndromes: a United States MarketScan® claims database analysis.

Introduction: Patients with Ehlers-Danlos syndromes (EDS) and hypermobility spectrum disorders (HSD) have significant health challenges that are well-documented, however their impact in terms of cost is not known. Our research objective was to examine the cost burden of EDS and HSD in the United States. We focused this analysis on those with commercial insurance plans. Methods: We queried the MarketScan® database for year 2021 for claims that contained an ICD-10 diagnosis code for EDS or hypermobility. Excess costs for patients in the EDS and HSD cohorts were determined by matching each patient to one patient in the database that did not have a claim for EDS or HSD and comparing total costs for the calendar year. We determined whether patients had claims for selected comorbid conditions likely to impact costs during the calendar year. Results: Sample sizes were 5,113 for adult (age ≥ 18) patients with EDS, 4,880 for adult patients with HSD, 1,059 for child (age 5-17) patients with EDS, and 2,427 for child patients with HSD. The mean excess costs were $21,100 for adult EDS patients, $11,600 for adult HSD patients, $17,000 for child EDS patients, and $11,000 for child HSD patients. EDS and HSD cohorts, both adults and children, with any of the comorbidities had greater healthcare costs. The largest difference was found in the EDS cohort with gastrointestinal comorbid conditions, with more than double the costs for adults. Discussion: We found that patients in the MarketScan database, adults and children, who had EDS or HSD had substantially higher associated excess healthcare costs than patients without EDS or HSD when considering age, sex, geographic location, and comorbidities. These disproportionate healthcare costs in this population have health policy and economic implications, including the need for rapid diagnosis, access to treatment, and accelerated research to advance treatments.

DarwinGSE: Towards better image retrieval systems for intellectual property datasets.

A trademark's image is usually the first type of indirect contact between a consumer and a product or a service. Companies rely on graphical trademarks as a symbol of quality and instant recognition, seeking to protect them from copyright infringements. A popular defense mechanism is graphical searching, where an image is compared to a large database to find potential conflicts with similar trademarks. Despite not being a new subject, image retrieval state-of-the-art lacks reliable solutions in the Industrial Property (IP) sector, where datasets are practically unrestricted in content, with abstract images for which modeling human perception is a challenging task. Existing Content-based Image Retrieval (CBIR) systems still present several problems, particularly in terms of efficiency and reliability. In this paper, we propose a new CBIR system that overcomes these major limitations. It follows a modular methodology, composed of a set of individual components tasked with the retrieval, maintenance and gradual optimization of trademark image searching, working on large-scale, unlabeled datasets. Its generalization capacity is achieved using multiple feature descriptions, weighted separately, and combined to represent a single similarity score. Images are evaluated for general features, edge maps, and regions of interest, using a method based on Watershedding K-Means segments. We propose an image recovery process that relies on a new similarity measure between all feature descriptions. New trademark images are added every day to ensure up-to-date results. The proposed system showcases a timely retrieval speed, with 95% of searches having a 10 second presentation speed and a mean average precision of 93.7%, supporting its applicability to real-word IP protection scenarios.

Evolutionary Ensemble Learning for EEG-Based Cross-Subject Emotion Recognition.

Electroencephalogram (EEG) has been widely utilized in emotion recognition due to its high temporal resolution and reliability. However, the individual differences and non-stationary characteristics of EEG, along with the complexity and variability of emotions, pose challenges in generalizing emotion recognition models across subjects. In this paper, an end-to-end framework is proposed to improve the performance of cross-subject emotion recognition. A novel evolutionary programming (EP)-based optimization strategy with neural network (NN) as the base classifier termed NN ensemble with EP (EPNNE) is designed for cross-subject emotion recognition. The effectiveness of the proposed method is evaluated on the publicly available DEAP, FACED, SEED, and SEED-IV datasets. Numerical results demonstrate that the proposed method is superior to state-of-the-art cross-subject emotion recognition methods. The proposed end-to-end framework for cross-subject emotion recognition aids biomedical researchers in effectively assessing individual emotional states, thereby enabling efficient treatment and interventions.

Exploring Generalizable Distillation for Efficient Medical Image Segmentation.

Efficient medical image segmentation aims to provide accurate pixel-wise predictions with a lightweight implementation framework. However, existing lightweight networks generally overlook the generalizability of the cross-domain medical segmentation tasks. In this paper, we propose Generalizable Knowledge Distillation (GKD), a novel framework for enhancing the performance of lightweight networks on cross-domain medical segmentation by generalizable knowledge distillation from powerful teacher networks. Considering the domain gaps between different medical datasets, we propose the Model-Specific Alignment Networks (MSAN) to obtain the domain-invariant representations. Meanwhile, a customized Alignment Consistency Training (ACT) strategy is designed to promote the MSAN training. Based on the domain-invariant vectors in MSAN, we propose two generalizable distillation schemes, Dual Contrastive Graph Distillation (DCGD) and Domain-Invariant Cross Distillation (DICD). In DCGD, two implicit contrastive graphs are designed to model the intra-coupling and inter-coupling semantic correlations. Then, in DICD, the domain-invariant semantic vectors are reconstructed from two networks (i.e., teacher and student) with a crossover manner to achieve simultaneous generalization of lightweight networks, hierarchically. Moreover, a metric named Fréchet Semantic Distance (FSD) is tailored to verify the effectiveness of the regularized domain-invariant features. Extensive experiments conducted on the Liver, Retinal Vessel and Colonoscopy segmentation datasets demonstrate the superiority of our method, in terms of performance and generalization ability on lightweight networks.

TB notifications among citizens and non-citizens in Taiwan.

Substantial under-notification of TB among non-citizens has been noted previously. Foreign workers with TB who were deported previously could stay for anti-TB treatment since 2014. We assessed whether TB notification improved.We used the National Health Insurance (NHI) reimbursement database to identify potential TB cases that required notification. We matched potential TB cases with the national TB registry to determine whether they had been notified. Cases notified within 7 days of the initiation of anti-TB treatment were classified as having timely notification.Of 53,208 potential TB cases identified in 2016-2020, 96.6% had been notified. The notification proportion increased from 95.5% in 2016 to 97.1% in 2020 among citizens and from 89.0% in 2016 to 96.9% in 2020 among non-citizens. Factors significantly associated with non-notification among non-citizens were previously notified TB (aOR 35.5, 95% CI 17.7-70.9), without health insurance (aOR 15.4, 95% CI 9.3-25.2) and having only one visit to health care facilities in 6 months (aOR 2.3, 95% CI 1.4-3.8). The proportion of TB cases notified within 7 days was 87% overall, 86.2% among citizens, and 96.5% among non-citizens.TB notification has improved, especially among non-citizens, following a policy change that allows foreign workers to stay for anti-TB treatment..

Risk of Cardiovascular Events Associated with Chronic Obstructive Pulmonary Disease and/or Metabolic Syndrome: A Large-Scale Nationwide Population-Based Cohort Study.

Purpose: Chronic obstructive pulmonary disease (COPD) and metabolic syndrome (MetS) are among the most prevalent conditions that might predispose individuals to life-threatening events. We aimed to examine their associations with cardiovascular (CV) events and mortality using a large-scale population dataset from the National Health Information Database in Korea. Patients and Methods: This population-based cohort study enrolled adults aged ≥40 years who had undergone more than two health examinations between 2009 and 2011. They were divided into four groups based on the presence of COPD and MetS. Analysis of the outcomes and CV events or deaths was performed from 2014 to 2019. We compared CV event incidence and mortality rates using a multivariate Cox proportional hazards model and Kaplan-Meier curves. Results: Totally, 5,101,810 individuals were included, among whom 3,738,458 (73.3%) had neither COPD nor MetS, 1,193,014 (23.4%) had only MetS, 125,976 (2.5%) had only COPD, and 44,362 (0.9%) had both. The risk of CV events was significantly higher in individuals with both COPD and MetS than in those with either COPD or MetS alone (HRs: 2.4 vs 1.6 and 1.8, respectively; all P <0.001). Similarly, among those with both COPD and MetS, all-cause and CV mortality risks were also elevated (HRs, 2.9 and 3.0, respectively) compared to the risks in those with either COPD (HRs, 2.6 and 2.1, respectively) or MetS (HRs, 1.7 and 2.1, respectively; all P <0.001). Conclusion: The comorbidity of MetS in patients with COPD increases the incidence of CV events and all-cause and cardiovascular mortality rates.

Comparison of Infection Risks Between Various Inhaled and Intranasal Corticosteroids: A Pharmacovigilance Analysis Based on the FAERS Database.

Purpose: This study conducted a pharmacovigilance analysis based on the FDA Adverse Event Reporting System (FAERS) database to compare the infection risk of inhaled or nasal Beclomethasone, Fluticasone, Budesonide, Ciclesonide, Mometasone, and Triamcinolone Acetonide. Methods: We used proportional imbalance analysis to evaluate the correlation between ICS /INCs and infection events. The data was extracted from the FAERS database from April 2015 to September 2023. Further analysis was conducted on the clinical characteristics, site of infection, and pathogenic bacteria of ICS and INCs infection adverse events (AEs). We used bubble charts to display their top 5 infection adverse events. Results: We analyzed 21,837 reports of infection AEs related to ICS and INCs, with an average age of 62.12 years. Among them, 61.14% of infection reports were related to females. One-third of infections reported to occur in the lower respiratory tract with Fluticasone, Budesonide, Ciclesonidec, and Mometasone; over 40% of infections reported by Triamcinolone Acetonide were eye infections; the rate of oral infections caused by Beclomethasone were 7.39%. The reported rates of fungal and viral infections caused by beclomethasone were 21.15% and 19.2%, respectively. The mycobacterial infections caused by Budesonide and Ciclesonidec account for 3.29% and 2.03%, respectively. Bubble plots showed that the ICS group had more fungal infections, oral infections, pneumonia, tracheitis, etc. The INCs group had more eye symptoms, rhinitis, sinusitis, nasopharyngitis, etc. Conclusion: Women who use ICS and INCs are more prone to infection events. Compared to Budesonide, Fluticasone seemed to have a higher risk of pneumonia and oral candidiasis. Mometasone might lead to more upper respiratory tract infections. The risk of oral infection was higher with Beclomethasone. Beclomethasone causes more fungal and viral infections, while Ciclesonide and Budesonide are more susceptible to mycobacterial infections.

Oncologists Must Consider Participant Data When Using Large-Scale Cancer Data Sets.

Primer that helps clarify large-scale clinical data sets and participant demographics for oncologists.

Clinical outcomes in people with diabetes-related foot infections: Analysis from a limb preservation service infection database.

BACKGROUND: Diabetes-related foot infections are common and represent a significant clinical challenge. There are scant data about outcomes from large cohorts. The purpose of this study was to report clinical outcomes from a large cohort of people with diabetes-related foot infections. METHODS: A tertiary referral hospital limb preservation service database was established in 2018, and all new episodes of foot infections were captured prospectively using an electronic database (REDCap). People with foot infections between January 2018 and May 2023, for whom complete data were available on infection episodes, were included. Infection outcomes were compared between skin and soft tissue infections (SST-DFI) and osteomyelitis (OM) using chi-square tests. RESULTS: Data extraction identified 647 complete DFI episodes in 397 patients. The data set was divided into two cohorts identifying each infection episode and its severity as either SST-DFI (N = 326, 50%) or OM (N = 321, 50%). Most infection presentations were classified as being moderate (PEDIS 3 = 327, 51%), with 36% mild (PEDIS 2 = 239) and 13% severe (PEDIS 4 = 81). Infection resolution occurred in 69% (n = 449) of episodes with failure in 31% (n = 198). Infection failures were more common with OM than SST-DFI (OM = 140, 71% vs. SST-DFI = 58, 29%, p < 0.00001). In patients with SST-DFI a greater number of infection failures were observed in the presence of peripheral arterial disease (PAD) compared to the patients without PAD (failure occurred in 30% (31/103) of episodes with PAD and 12% (27/223) of episodes without PAD; p < 0.001). In contrast, the number of observed infection failures in OM episodes were similar in patients with and without PAD (failure occurred in 45% (57/128) of episodes with PAD and 55% (83/193) of episodes without PAD; p = 0.78). CONCLUSIONS: This study provides important epidemiological data on the risk of poor outcomes for DFI and factors associated with poor outcomes in an Australian setting. It highlights the association of PAD and treatment failure, reinforcing the need for early intervention to improve PAD in patients with DFI. Future randomised trials should assess the benefits of revascularisation and surgery in people with DFI and particularly those with OM where outcomes are worse.

Compassionate drug uses in Italy. Analysis at single-center level.

AIMS: Using a database from two pharmaceutical companies that managed several compassionate use programs in the last few years in Italy, we have previously analyzed the data by the number of patients and centers in each region and province, showing that the use of compassionate drugs is largely diffused in the country, in a manner directly related to the size of population of each region. In the present study we used the same database to expand the analysis to single-center level, aiming to test the hypothesis whether, despite a good diffusion of compassionate drug uses in each region, the majority of them concentrates within a relatively low number of centers. METHODS: Data from different programs were grouped per center, and the centers were ordered per the number of compassionate uses dispensed, and per region. Two cutoff levels, at 75% and 90%, were drawn to look at the number of centers accounting for such percentages of compassionate uses in each region. RESULTS: Out of 343 centers throughout Italy, 93 and 156 centers (i.e., 27.11% and 45.48% of the total) account for about 75% and 90% of all compassionate drugs dispensed in Italy. In 6 regions out of 20 (Valle d'Aosta, Liguria, Umbria, Lazio, Molise and Campania) the centers accounting for 75% of all compassionate drugs dispensed are located in a single town. Forty and 20 out of the 93 centers dispensing 75% of all compassionate drugs are academic hospitals and research hospitals (Istituti di Ricovero e Cura a Carattere Scientifico, IRCCS), respectively. CONCLUSIONS: In this study we have demonstrated that, in spite of widespread diffusion of compassionate drug uses in all Italian regions, their management is restricted to a relatively low number of dispensing centers in each region.

Pattern of heterogeneity in normal brain ageing: screening for mild cognitive impairment and its risk of progression with a radiomics model.

PURPOSE: This study aimed to develop a normal brain ageing model based on magnetic resonance imaging and radiomics, therefore identifying radscore, an imaging indicator representing white matter heterogeneity and exploring the significance of radscore in detecting people's cognitive changes. METHODS: Three hundred sixty cognitively normal (CN) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 105 CN subjects from the Parkinson's Progression Markers Initiative database were used to develop the model. In ADNI, 230 mild cognitive impairment (MCI) subjects were matched with 230 CN old-aged subjects to evaluate their heterogeneity difference. One hundred four MCI subjects with 48 months of follow-up were divided into low and high heterogeneity groups. Kaplan-Meier survival curve analysis was used to observe the importance of heterogeneity results for predicting MCI progression. RESULTS: The area under the receiver operating characteristic curve of the model in the training, internal test and external test sets was 0.7503, 0.7512 and 0.7514, respectively. There was a significantly positive correlation between age and radscore of CN subjects (r = 0.501; P < .001). The radscore of MCI subjects was significantly higher than that of matched CN subjects (P < .001). The median radscore ratios of MCI to CN from four age groups (66-70y, 71-75y, 76-80y and 81-85y) were 1.611, 1.760, 1.340 and 1.266, respectively. The probability to progression of low and high heterogeneity groups had a significant difference (P = .002). CONCLUSION: When radscore is significantly higher than that of normal ageing, it is necessary to alert the possibility of cognitive impairment and deterioration.

Comparison of embolic risk in left ventricular thrombus between nonischemic and ischemic cardiomyopathy: A nationwide database analysis.

BACKGROUND: Left ventricular (LV) thrombus is not common but poses significant risks of embolic stroke or systemic embolism. However, the distinction in embolic risk between nonischemic cardiomyopathy (NICM) and ischemic cardiomyopathy (ICM) remains unclear. METHODS AND RESULTS: In total, 2738 LV thrombus patients from the JROAD-DPC (Japanese Registry of All Cardiac and Vascular Diseases Diagnosis Procedure Combination) database were included. Among these patients, 1037 patients were analyzed, with 826 (79.7%) having ICM and 211 with NICM (20.3%). Within the NICM group, the distribution was as follows: dilated cardiomyopathy (DCM; 41.2%), takotsubo cardiomyopathy (27.0%), hypertrophic cardiomyopathy (18.0%), and other causes (13.8%). The primary outcome was a composite of embolic stroke or systemic embolism (SSE) during hospitalization. The ICM and NICM groups showed no significant difference in the primary outcome (5.8% vs. 7.6%, p = 0.34). Among NICM, SSE occurred in 12.6% of patients with DCM, 7.0% with takotsubo cardiomyopathy, and 2.6% with hypertrophic cardiomyopathy. Multivariate logistic regression analysis for SSE revealed an odds ratio of 1.4 (95% confidence interval [CI], 0.7-2.7, p = 0.37) for NICM compared to ICM. However, DCM exhibited a higher adjusted odds ratio for SSE compared to ICM (2.6, 95% CI 1.2-6.0, p = 0.022). CONCLUSIONS: This nationwide shows comparable rates of embolic events between ICM and NICM in LV thrombus patients, with DCM posing a greater risk of SSE than ICM. The findings emphasize the importance of assessing the specific cause of heart disease in NICM, within LV thrombus management strategies.

Recent Trends in Concomitant Distal Clavicle Excision During Rotator Cuff Repair.

The purpose of this study is to evaluate trends in distal clavicle excision (DCE) in association with arthroscopic rotator cuff repair (RCR) from 2010 to 2019. The National Surgical Quality Improvement Program database was queried to identify all patients who underwent arthroscopic RCR from January 1, 2010 to December 31, 2019, and was further subdivided into procedure type: (1) isolated RCR; and (2) RCR with arthroscopic or open DCE. The proportion of each surgery type, by year and within groups, was calculated. The Cochran-Armitage test for trend was used to analyze yearly proportions of RCR with concomitant DCE. In a sample size of 19,163 patients, the proportion of RCR with DCE decreased from 51.2% to 40.8% (r = -0.830; p = 0.003). Although the results of this study suggest that surgeons are performing fewer DCEs in the setting of RCR, many DCEs are still being done. (Journal of Surgical Orthopaedic Advances 33(2):077-079, 2024).

Understanding Local Alcohol Control in Wisconsin: Building a Database of Local Municipal Alcohol Policies.

In Wisconsin, many alcohol policies are regulated at the local level. To examine the relationship between local policies, alcohol use and health outcomes, our team developed a database to collect local alcohol policies. Initial results highlight differences in how policies are defined, enforced, and made available to the public.