Effectiveness of Concurrent Ankle Arthroscopy During Open Reduction and Internal Fixation of Malleolar Fractures in Prevention of Common Short-Term Complications.

Rotational malleolar fractures result in a high prevalence of intra-articular pathologies; therefore, routine arthroscopic assessment may be beneficial in the surgical treatment of ankle fractures. However, the clinical studies regarding the effectiveness of arthroscopy thus far have mixed results. We investigated the efficacy of concurrent arthroscopy during the treatment of malleolar fractures using a large U.S. healthcare data set. Those who had arthroscopy were compared with those who did not, during the surgical treatment of malleolar fractures, while adjusting for covariates of clinical relevance. The analysis showed that concurrent arthroscopy is protective against postoperative repeat surgery (OR = 0.13, 95CI = 0.02-0.41) and wound dehiscence (OR = 0.18, 95CI = 0.03-0.56). The number of added arthroscopy cases needed to avoid one repeat surgery was 74, while that of wound dehiscence was 52. Further studies are needed to determine if routine use of arthroscopy is justifiable in the surgical treatment of malleolar fractures, given the additional costs and time to the healthcare system.

Investigating the uses of machine learning algorithms to inform risk factor analyses: The example of avian infectious bronchitis virus (IBV) in broiler chickens.

Infectious bronchitis virus (IBV) is a contagious coronavirus causing respiratory and urogenital disease in chickens and is responsible for significant economic losses for both the broiler and table egg layer industries. Despite IBV being regularly monitored using standard epidemiologic surveillance practices, knowledge and evidence of risk factors associated with IBV transmission remain limited. The study objective was to compare risk factor modeling outcomes between a traditional stepwise variable selection approach and a machine learning-based random forest Boruta algorithm using routinely collected IBV antibody titer data from broiler flocks. IBV antibody sampling events (n = 1111) from 166 broiler sites between 2016 and 2021 were accessed. Ninety-two geospatial-related and poultry-density variables were obtained using a geographic information system and data sets from publicly available sources. Seventeen and 27 candidate variables were screened to potentially have an association with elevated IBV antibody titers according to the manual selection and machine learning algorithm, respectively. Selected variables from both methods were further investigated by construction of multivariable generalized mixed logistic regression models. Six variables were shortlisted by both screening methods, which included year, distance to urban areas, main roads, landcover, density of layer sites and year, however, final models for both approaches only shared year as an important predictor. Despite limited significance of clinical outcomes, this work showcases the potential of a novel explorative modeling approach in combination with often unutilized resources such as publicly available geospatial data, surveillance health data and machine learning as potential supplementary tools to investigate risk factors related to infectious diseases.

Retrospective Cohort Study on Determinants of Mechanical Ventilation Duration of COVID-19 ICU Patients.

Background In the face of the ongoing global health crisis posed by COVID-19, it becomes imperative to understand the disease's dynamics, particularly in specific regions. This study provides a detailed examination of the factors influencing mechanical ventilation (MV) duration among COVID-19 patients in an intensive care setting, focusing on a diverse patient cohort from the Al Hassa region of Saudi Arabia. The primary aim of this study was to identify key demographic factors, clinical outcomes, and comorbidities that affect the duration of MV among ICU patients with COVID-19. This understanding is crucial for enhancing patient care and informing healthcare strategies in the context of the pandemic. Methods A retrospective cohort study was conducted involving patients diagnosed with COVID-19 and admitted to the ICU in the Al Hassa region. The total number of participants was 1,259. Using a systematic sampling method, these participants were chosen to create a representative sample that reflects the prevailing treatment protocols in ICUs across these hospitals. Data encompassed patient demographics, comorbidities, clinical outcomes, and MV duration. Statistical analyses were employed to explore the associations between these variables. Results Our findings reveal a total of 1,259 participants significant associations between MV duration and various factors, including nationality, legal status, travel history, and comorbidities like heart failure and immunocompromised status. These insights are instrumental in understanding the nuances of COVID-19 management in critical care. Conclusion The study provides valuable insights into the determinants of MV duration in severe COVID-19 cases, emphasizing the need for individualized patient care approaches. It highlights the complexity of managing COVID-19 in ICU settings and underscores the importance of tailored healthcare responses to this global health challenge, particularly in the Al Hassa region.

Incidence and risk factors of stress urinary incontinence after laparoscopic hysterectomy.

OBJECTIVE: To observe the long-term effects of total hysterectomy on urinary function, evaluate the effects of preoperative nutritional status, urinary occult infection, and surgical factors on the induction of postoperative stress urinary incontinence (SUI), and explore the incidence and risk factors of SUI. STUDY DESIGN: From January 2017 to December 2017, 164 patients with benign non-prolapsing diseases who underwent a laparoscopic total hysterectomy in the First People's Hospital of Taicang were selected as the analysis objects. The International Incontinence Standard Questionnaire for Female Lower Urinary Tract Symptoms (ICIQ-FLUTS) and Pelvic Floor Impact Questionnaire-short version 20 (PFDI-20) were used for telephone follow-up to subjectively assess the urinary function of patients, collect their medical records, and statistically analyze the number of postoperative SUI cases. Logistic multivariate analysis was used to analyze the influencing factors of postoperative female SUI, presented as adjusted odds ratios with 95% confidence intervals. RESULTS: Only 97 out of 164 patients completed the ICIQ-FLUTS and PFDI-20 questionnaires. Among these participants, 28 patients (28.86%) were diagnosed with SUI (study group), while 69 patients (71.13%) were classified as women without SUI (control group). The age, menopause, parity ≥ 2 times, Body mass index (BMI) ≥ 28 kg/m2, neonatal weight ≥ 4000 g, history of chronic cough, preoperative hemoglobin ≤ 100 g/L, preoperative urine bacteria ≥ 100u/L, preoperative uterine volume ≥ 90 cm3, intraoperative blood loss, and operation time of the study group were compared with those of the control group. The differences were statistically significant (P < 0.05). Further Logistic multivariate analysis showed that menopause, preoperative hemoglobin ≤ 100 g/L, preoperative urine bacteria ≥ 100u/L, uterine volume ≥ 90 cm3, history of chronic cough, BMI ≥ 28 kg/m2 were risk factors for postoperative SUI in patients undergoing hysterectomy (P < 0.05). CONCLUSIONS: Hysterectomy for benign non-prolapse diseases has a long-term potential impact on the urinary system of patients, and the risk of postoperative SUI increases. The main risk factors of SUI are parity, menopausal status, obesity, preoperative nutritional status, and occult infection of the urinary system.

Obstructive Sleep Apnea: A Contributing Factor in Gout.

INTRODUCTION: Obstructive sleep apnea (OSA) is a comorbidity, which has shared risk factors with gout as well as causes pathophysiological mechanisms causing hyperuricemia. The relationship remains contentious. METHODS: TrinetX, a global federated research network that provides a dataset of electronic medical records from different healthcare organizations (HCOs). We utilized this network to query patients who had a BMI greater than 30 and then two subgroups were made based on the presence or absence of OSA. Furthermore, propensity score matching (PSM) was carried out to match age, sex, race, chronic kidney disease (CKD), heart failure, and the use of diuretics. Compare outcome analytic function was utilized to map the co-relation with Gout. RESULTS: A total of 3541566 patients who had a BMI >30 were identified, out of which 817638 (23.09%) patients had OSA. 7.19% of patients with OSA had gout while 2.84% without OSA had gout (p<0.0001). The odds of having gout are 2.65 times higher in patients with OSA than patients without OSA (hazard ratio is 2.393, 95% confidence interval (CI) 2.367-2.419, p<0.0001). After PSM, both the groups of obese patients with and without International Classification of Diseases, 10th Revision (ICD-10) diagnosis of OSA included 801526 patients, within which 6.93% of patients with OSA had gout while 4.63% of patients without OSA had gout (p<0.0001). The odds ratio was 1.533 (95% CI 1.512-1.554, p<0.0001) and the hazard ratio was 1.404 (95% CI 1.386-1.423). CONCLUSION: Our study demonstrated that there is a strong correlation between gout and OSA. Chronic hypoxia-induced hyperuricemia is the most widespread explanation. OSA is a treatable condition with timely diagnosis and proper treatment. Prospective cohort studies are required to further test the strength of the relationship between OSA and gout.

Analysis of risk factors for stenosis after laparoscopic pyeloplasty in the treatment of ureteropelvic junction obstruction.

BACKGROUND: Laparoscopic ureteroplasty is an effective method for managing ureteropelvic junction obstruction. Despite its high success rate, there remains a subset of patients who do not experience improvement in the hydrops. METHODS: The study retrospectively analyzed the data of 143 patients with ureteropelvic junction obstruction (UPJO) who underwent laparoscopic pyeloplasty (LP) in our hospital from January 2015 to May 2022. Logistic regression was used to analyze the risk factors of recurrence stenosis after UPJO. RESULTS: Out of these patients, 119 had complete clinical data and follow-up records. Among these patients, restenosis occurred in nine cases after the operation. There was a significant statistical difference in blood loss (P < 0.05). Univariate and multivariate logistic regression analysis revealed that the preoperative separation degree of the renal pelvis, cystatin C, and intraoperative blood loss were potential risk factors for recurrent stenosis after primary LP. When divided by split renal function (SRF), the odds ratio (OR) was 7.850 (P = 0.044), indicating that it was an independent risk factor for postoperative restenosis. Similarly, the OR for stenotic segment length was 0.025 (P = 0.011), also indicating it as an independent risk factor for restenosis. The areas under the receiver operating characteristic curve for stenotic segment length and SRF were 0.9056 and 0.7697, respectively. CONCLUSION: In our study, we identified that preoperative renal pelvis separation, cystatin C, and intraoperative blood loss were potential risk factors for postoperative restenosis. SRF and stenosis segment length were independent risk factors for postoperative restenosis.

Risk factor analysis and risk prediction study of obesity in steelworkers: model development based on an occupational health examination cohort dataset.

BACKGROUND: Obesity is increasingly recognized as a grave public health concern globally. It is associated with prevalent diseases including coronary heart disease, fatty liver, type 2 diabetes, and dyslipidemia. Prior research has identified demographic, socioeconomic, lifestyle, and genetic factors as contributors to obesity. Nevertheless, the influence of occupational risk factors on obesity among workers remains under-explored. Investigating risk factors specific to steelworkers is crucial for early detection, prediction, and effective intervention, thereby safeguarding their health. METHODS: This research utilized a cohort study examining health impacts on workers in an iron and steel company in Hebei Province, China. The study involved 5469 participants. By univariate analysis, multifactor analysis, and review of relevant literature, predictor variables were found. Three predictive models-XG Boost, Support Vector Machine (SVM), and Random Forest (RF)-were employed. RESULTS: Univariate analysis and cox proportional hazard regression modeling identified age, gender, smoking and drinking habits, dietary score, physical activity, shift work, exposure to high temperatures, occupational stress, and carbon monoxide exposure as key factors in the development of obesity in steelworkers. Test results indicated accuracies of 0.819, 0.868, and 0.872 for XG Boost, SVM, and RF respectively. Precision rates were 0.571, 0.696, and 0.765, while recall rates were 0.333, 0.592, and 0.481. The models achieved AUCs of 0.849, 0.908, and 0.912, with Brier scores of 0.128, 0.105, and 0.104, log losses of 0.409, 0.349, and 0.345, and calibration-in-the-large of 0.058, 0.054, and 0.051, respectively. Among these, the Random Forest model demonstrated superior performance. CONCLUSIONS: The research indicates that obesity in steelworkers results from a combination of occupational and lifestyle factors. Of the models tested, the Random Forest model exhibited superior predictive ability, highlighting its significant practical application.

Analysis of factors affecting outcome in acute type A aortic dissection complicated by preoperative cardiopulmonary resuscitation.

OBJECTIVES: Cardiopulmonary resuscitation (CPR) aggravates the pre-existing dismal prognosis of patients suffering from acute type A aortic dissection (ATAAD). We aimed to identify factors affecting survival and outcome in ATAAD patients requiring CPR at presentation at 2 European aortic centres. METHODS: Data on 112 surgical candidates and undergoing preoperative CPR were retrospectively evaluated. Patients were divided into 2 groups according to 30-day mortality. A multivariable model identified predictors for 30-day mortality. RESULTS: Preoperative death occurred in 23 patients (20.5%). In the remaining 89 surgical patients (79.5%) circulatory arrest time (41 ± 20 min in 30-day non-survivors vs 30 ± 13 min in 30-day survivor, P = 0.003) as well as cardiopulmonary bypass time (320 ± 132 min in 30-day non-survivors vs 252 ± 140 min in 30-day survivor, P = 0.020) time was significantly longer in patients with worse outcome. Thirty-day mortality of the total cohort was 61.6% (n = 69) with cardiac failure in 48% and aortic rupture or haemorrhagic shock (28%) as predominant reasons of death. Age [odds ratio (OR) 1.04, 95% confidence interval (CI) 1.01-1.09, P = 0.034], preoperative coronary (OR 3.42, 95% CI 1.34-9.26, p = 0.012) and spinal malperfusion (OR 12.49, 95% CI 1.83-225.02, P = 0.028) emerged as independent predictors for 30-day mortality while CPR due to tamponade was associated with improved early survival (OR 0.29, 95% CI 0.091-0.81, P = 0.023). CONCLUSIONS: Assessment of underlying cause for CPR is mandatory. Pericardial tamponade, rapidly resolved with pericardial drainage, is a predictor for improved survival, while age and presence of coronary and spinal malperfusion are associated with dismal outcome in this high-risk patient group.

Impact of heart failure and preoperative platelet count on the postoperative short-term outcome in infective endocarditis patients.

BACKGROUND: Heart failure (HF) and platelet count are often considered risk factors for mortality in patients with infective endocarditis (IE); however, their effects on various complications have not been elucidated. HYPOTHESIS: We speculated that HF and platelet count have significant impact on the short-term outcomes of IE. METHODS: This single-center retrospective study analyzed data from 320 IE patients who underwent surgery. A multivariate Cox proportional hazards model was used to identify the risk factors for adverse outcomes. The effect of the platelet count on the prognosis of patients with HF was determined by subgroup analysis and Kaplan-Meier analysis. RESULTS: The study population was divided into the HF group (n = 102) and the non-HF group (n = 218). The median age of the total population was 44.5 years (31-56 years), of which 227 (70.94%) patients were male. The incidence rates of 1-year all-cause mortality, cardiac outcomes, and composite outcomes were respectively almost sixfold, fourfold, and threefold higher in the HF group than in the non-HF group (all p < 0.001). In multivariate Cox regression analysis, HF was an independent risk factor for 1-year all-cause mortality, cardiac outcomes, cerebral outcomes, and composite outcomes. The Kaplan-Meier survival curves revealed that the patients with both HF and thrombocytopenia demonstrated the worst composite outcomes than the patients of the other groups (log-rank p < 0.001). In the HF group, the platelet count was significantly associated with mortality and composite outcomes. CONCLUSIONS: HF and preoperative platelet count are significantly associated with 1-year all-cause mortality and adverse outcomes postoperatively in IE patients. Patients with HF and thrombocytopenia have the worst short-term prognosis.

Development and validation of a postoperative bleeding complications prediction model in infective endocarditis.

OBJECTIVES: Bleeding complications are one of the most serious postoperative complications after cardiac surgery and are associated with high mortality, especially in patients with infective endocarditis (IE). Our objectives were to identify the risk factors and develop a prediction model for postoperative bleeding complications in IE patients. METHODS: The clinical data of IE patients treated from October 2013 to January 2022 were reviewed. Multivariate logistic regression analysis was used to evaluate independent risk factors for postoperative bleeding complications and develop a prediction model accordingly. The prediction model was verified in a temporal validation cohort. The performance of the model was evaluated in terms of its discrimination power, calibration, precision, and clinical utility. RESULTS: A total of 423 consecutive patients with IE who underwent surgery were included in the final analysis, including 315 and 108 patients in the training cohort and validation cohort, respectively. Four variables were selected for developing a prediction model, including platelet counts, systolic blood pressure, heart failure and vegetations on the mitral and aortic valves. In the training cohort, the model exhibited excellent discrimination power (AUC = 0.883), calibration (Hosmer-Lemeshow test, P = 0.803), and precision (Brier score = 0.037). In addition, the model also demonstrated good discrimination power (AUC = 0.805), calibration (Hosmer-Lemeshow test, P = 0.413), and precision (Brier score = 0.067) in the validation cohort. CONCLUSIONS: We developed and validated a promising risk model with good discrimination power, calibration, and precision for predicting postoperative bleeding complications in IE patients.

Evaluation of the First-Dose Anti-VEGF Anatomical Response in Polypoidal Choroidal Vasculopathy Patients: Correlation with the Third-Dose Response and Risk Factor Analysis.

INTRODUCTION: The aims of the study were to investigate whether first-dose efficacy can predict third-dose anatomical response and analyze the risk factors for first-dose response of polypoidal choroidal vasculopathy (PCV) patients. METHODS: We retrospectively reviewed patients' medical records from 27 centers of China PCV Research Alliance. PCV patients treated with intravitreal injections of conbercept (IVC) based on the 3+ pro re nata regimen (three initial monthly injections, followed by injections as needed) with complete 3-month injection data were included. Response correlations, risk factor associations, changes in central macular thickness (CMT) or best-corrected visual acuity (BCVA), and number of injections in the first year of follow-up were evaluated separately in the pachy-PCV and non-pachy-PCV phenotypes. RESULTS: Overall, 165 eligible patients were included. There was a significant correlation between first-dose and third-dose anatomical response in pachy-PCV or non-pachy-PCV patients (rs = 0.611, p < 0.001; rs = 0.638, p < 0.001). Multivariate analysis revealed associations of good first-dose anatomical response in pachy-PCV patients with baseline CMT with a predicted area under the curve (AUC) of 0.847, while a good response in non-pachy-PCV patients was associated with baseline BCVA, baseline CMT, pigment epithelial detachment (PED) height, higher proportion of intraretinal fluid, and lower PED minimum diameter with a predicted AUC of 0.940. CMT in the good first-dose response group was significantly decreased from baseline at all first-year follow-up visits in both groups (p < 0.001), and mean BCVA was improved in the good versus poor first-dose anatomical response group (5.4 vs. 1.6 ETDRS letters in pachy-PCV, 10.6 vs. 7.4 letters in non-pachy-PCV) after the third injection. No significant difference was observed in the number of injections in the first year of follow-up between different response groups. CONCLUSION: In PCV patients receiving IVC, the first- and third-dose responses are significantly correlated, and different factors influence the first-dose response in different subtypes of PCV.

Home reading environment, sociometric and demographic factors associated with dyslexia in primary school students in China: A case-control study.

Background: Developmental dyslexia (DD) has been generally recognized as a multifactorial psychological disorder in recent decades. However, studies on reading and learning environment, social and demographic factors affecting Chinese developmental dyslexia (DD) are still scarce in China. This study aims to explore multidimensional home influencing factors associated with DD before and after birth. Methods: A total of 60 dyslexic and 252 normal elementary school students graded 2-5 were recruited in Shantou, China. The Least Absolute Shrinkage and Selection Operator (LASSO) regression model was used for the social and demographic variables screening. Odds ratios (ORs) with 95 % confidence intervals (CIs) for associations between DD and related factors were estimated by multivariate logistic regression models. Results: Through LASSO regression, we ultimately identified 13 key variables, including maternal education level and family monthly income, among others. The logistic regression analyses showed that the risk of DD was higher in children with lower maternal education levels. Divergent parenting styles may be a risk factor for developing DD as opposed to consistent parenting styles (OR = 4.93, 95%CI: 1.11-21.91). Children whose mothers suffered from malnutrition during pregnancy were more likely to develop DD (OR = 10.31, 95%CI: 1.84-37.86), as well as exposure to second-hand smoking at home every day (OR = 5.33, 95%CI: 1.52-18.66). Interestingly, children's active reading (OR = 0.26, 95%CI: 0.08-0.84; OR = 0.17, 95%CI: 0.04-0.76 for "sometimes" and "often" compared to none, respectively), children having extracurricular reading fairy tale books (OR = 0.37, 95%CI: 0.15-0.90), and children having extracurricular reading composition books (OR = 0.25, 95%CI: 0.09-0.69) were significant protective factors for DD. Conclusions: Home reading environment, several educational, sociometric and demographic factors may influence the development of dyslexia. We should pay attention to these factors on the development of dyslexia, so as to provide the well social and familial environment to ensure the healthy development of children.

On-farm epidemiology, virulence profiling, and molecular characterization of methicillin-resistant Staphylococcus aureus at goat farms.

Antimicrobial resistance (AMR) becomes a challenging issue that limits the therapeutic options for both veterinary and public health professionals. The current study aimed to investigate the on-farm epidemiology, antibiotics resisting profiling, virulence analysis, and molecular detection of methicillin-resistant Staphylococcus aureus (MRSA) at the caprine-human interface. A total of 768 goat milk samples and 94 skin swabs from farm personnel were collected from 30 goat flocks and processed for isolation of S. aureus. The study isolates were confirmed as MRSA based on the oxacillin and cefoxitin disc diffusion test and the presence of mecA gene. MRSA isolates of goats and human origin were characterized and further evaluated for the presence of virulence genes responsible for intramammary infections and public health hazards. The results revealed 26.82 % and 27.79 % goat milk samples and human samples positive for S. aureus, respectively. A higher MRSA prevalence of 35.92 % and 10.71 % was found in goat and human isolates respectively. The phylogenetic analysis revealed a lesser extent of homology in mecA gene of S. aureus isolates at the caprine-human interface. Moreover, this study revealed strong evolutionary connection between the study isolates and MRSA isolates of Pakistani cattle and buffalo while the in-silico protein analysis showed that all sequences have the same protein motifs resembling penicillin binding protein 2a. The risk factors analysis revealed that teat length, drainage system, hygienic measures during milking, use of teat dip, teat injury, and veterinary services were significantly associated with subclinical mastitis in goats. A total of 43.24 % of local MRSA isolates showed multi-drug resistance (MDR). The isolates showed higher resistance to oxytetracycline followed by gentamicin and vancomycin while moxifloxacin, and linezolid were among the susceptible antibiotics. Local MRSA isolates carried virulence markers (nuc and coag genes) and biofilm-associated icaA (43.24 %) and icaD (29.73 %) genes which are responsible for the intramammary infection. The local isolates also carried the virulence genes of public health concern including the enterotoxin C (sec) gene (24.3 %), enterotoxins B (seb) gene (5.41 %), and enterotoxin D (sed) gene (2.7 %). Enterotoxins A (sea) and E (see) genes were not detected in any isolate. The study concluded that MRSA is an emerging and prevailing pathogen in dairy goats with a high potential to transmit to associated human beings. The presence of a variety of virulence factors as well as the associated antibiotic resistance makes MRSA a potential threat at animal-human interface and thus demands further research.

Equine tapeworm (Anoplocephala spp.) infection: evaluation of saliva- and serum-based antibody detection methods and risk factor analysis in Slovak horse populations.

A lack of accurate information on the prevalence and distribution of Anoplocephala spp. infections on horse farms has led to insufficient attention to tapeworm control and increasing horse anoplocephaloses in Europe. Our study aimed to examine the occurrence of Anoplocephala spp. infection using coprological, serum- and saliva-based antibody detection methods and to analyze the risk factors associated with tapeworm infection in domestic horses in Slovakia. Fecal, serum, and saliva samples were collected from 427 horses from 31 farms in Slovakia. Additionally, a questionnaire study was conducted to collect information on tapeworm distribution on horse farms and analyze risk factors associated with infection. Fecal samples were examined by the mini-FLOTAC and the double centrifugation/combined sedimentation-flotation techniques. Serum and saliva samples were analyzed by ELISA to determine antibody levels against Anoplocephala spp. The effects of variables associated with an individual horse were tested for the positive result of the saliva ELISA test on Anoplocephala spp. Cestode eggs were detected in 1.99% of fecal samples (farm prevalence 12.90%), with no differences between the two coprological methods. Serum-based tapeworm ELISA results revealed that 39.39% of horses tested positive (farm prevalence 83.87%); while saliva-based tapeworm ELISA results revealed 56.95% positive horses (farm prevalence 96.77%). Binary logistic regression analysis revealed four meaningful predictors that significantly impacted the likelihood of detecting tapeworm infection in horses: horse age, pasture size, anthelmintic treatment scheme, and access to pasture. The influences of other variables associated with an individual horse were not significantly associated with detecting tapeworm infection.

Associations of cow and farm characteristics with cow-level lameness using data from an extensive cross-sectional study across 3 structurally different dairy regions in Germany.

The aim of the present study was to evaluate the associations between milk recording data, body condition score (BCS), housing factors, management factors, and lameness in freestall-housed dairy cows in 3 structurally different regions in Germany. These regions substantially vary regarding herd size, breeds, access to pasture, farm management (family run or company owned), and percentage of organic farms. The data used was collected in a large cross-sectional study from 2016 to 2019. A total of 58,144 cows from 651 farms in 3 regions of Germany (North, East, and South) was scored for locomotion and body condition. Additionally, data on milk yield, milk composition, breed, age, as well as information on housing and management were retrieved. One mixed-logistic regression model was fitted per region to evaluate the association of the data with the target variable "lame" and to allow for a comprehensive reflection across different kinds of farming types. In all regions, undercondition (BCS lower than recommended for the lactation stage; North: odds ratio [OR] 2.15, CI 1.96-2.34; East: OR 2.66, CI 2.45-2.88; South: OR 2.45, CI 2.01-2.98) and mid-lactation stage (102-204 d in milk; North: OR 1.15, CI 1.05-1.27; East: OR 1.24, CI 1.17-1.32; South: OR 1.38, CI 1.18-1.62) were associated with higher odds for lameness, whereas overcondition (BCS higher than recommended for the lactation stage; North: OR 0.51, CI 0.44-0.60; East: OR 0.51, CI 0.48-0.54; South: OR 0.65, CI 0.54-0.77) and parity of 1 or 2 was associated with lower odds (parity 1 = North: OR 0.32, CI 0.29-0.35; East: OR 0.19, CI 0.18-0.20; South: OR 0.28, CI 0.24-0.33; parity 2 = North: OR 0.51, CI 0.47-0.46; East: OR 0.41, CI 0.39-0.44; South: OR 0.49, CI 0.42-0.57), irrespective of the regional production characteristics. Low energy-corrected milk yield was associated with higher odds for lameness in South and North (North: OR 1.16, CI 1.05-1.27; South: OR 1.43, CI 1.22-1.69). Further factors such as pasture access for cows (North: OR 0.64, CI 0.50-0.82; and South: OR 0.65, CI 0.47-0.88), milk protein content (high milk protein content = North: OR 1.34, CI 1.18-1.52; East: OR 1.17, CI 1.08-1.28; low milk protein content = North: OR 0.79, CI 0.71-0.88; East: OR 0.84, CI 0.79-0.90), and breed (lower odds for "other" [other breeds than German Simmental and German Holstein] in East [OR 0.47, CI 0.42-0.53] and lower odds both for German Holstein and "other" in South [German Holstein: OR 0.62, CI 0.43-0.90; other: OR 0.46, CI 0.34 - 0.62]) were associated with lameness in 2 regions, respectively. The risk of ketosis (higher odds in North: OR 1.11, CI 1.01-1.22) and somatic cell count (higher odds in East: increased (>39.9 cells × 1,000/mL): OR 1.10; CI 1.03-1.17; high (>198.5 cells × 1,000/mL): OR 1.08; CI 1.01-1.06) altered the odds for lameness in 1 region, respectively. Cows from organic farms had lower odds for lameness in all 3 regions (North: OR 0.18, CI 0.11-0.32; East: OR 0.39, CI 0.28-0.56; South: OR 0.45, CI 0.29-0.68). As the dairy production systems differed substantially between the different regions, the results of this study can be viewed as representative for a wide variety of loose-housed dairy systems in Europe and North America. The consistent association between low BCS and lameness in all regions aligns with the previous literature. Our study also suggests that risk factors for lameness can differ between geographically regions, potentially due to differences in which dairy production system is predominantly used and that region-specific characteristics should be taken into account in comparable future projects.

Lessons learned through the 20-year development of a national fatal drowning database in Australia.

BACKGROUND: Co-ordinated, evidence-based policy and programmatic efforts are needed to respond to complex drowning prevention problems. Comprehensive, current, and robust data are vital for agenda setting, burden and risk factor identification, intervention design and evaluation, as well as setting policy. We aim to record methods used in, and identify impacts of, the development of a national fatal drowning database (NFDD) in Australia, including lessons learned across research, policy, and practice. METHODS: We employ a case study method using process mapping and document review to explore the evolution, drivers and impacts of the NFDD. We analyse methodological approaches including those relating to data definitions, drowning case collection, and management, as well as tracking the various outputs of the NFDD. We describe a development timeline that presents impact of drowning prevention policy, and research agendas on database development, and research investments more specifically. RESULTS: Our study identified that the collected variables grew 20-fold from 2002 to 2022, reaching 259 variables, and 5,692 unique cases of fatal drowning. The NFDD employs data triangulation methodology, combining keyword and targeted searches of coronial files, media report monitoring, and organisational data provision. Database development is influenced by the Australia Water Safety Strategy, policymaker and practitioner-initiated research agendas, and identification of knowledge gaps. We identified numerous outputs spanning publications, media, intervention development, and legislative submissions. CONCLUSION: A comprehensive and robust NFDD informed by policymaker and practitioner input can enhance surveillance, policy, and intervention development for drowning prevention. Employing mixed data collection and validation methods can supplement weaknesses in official data sources. There is a need for the NFDD to continue to evolve in its application while maintaining rigorous case identification and data quality assurance processes. Despite significant investment, the outputs and influence on drowning prevention practice in Australia has been extremely valuable and contributed to sizeable reductions in Australia's fatal drowning rate.

XGBoost-based machine learning test improves the accuracy of hemorrhage prediction among geriatric patients with long-term administration of rivaroxaban.

BACKGROUND: Hemorrhage is a potential and serious adverse drug reaction, especially for geriatric patients with long-term administration of rivaroxaban. It is essential to establish an effective model for predicting bleeding events, which could improve the safety of rivaroxaban use in clinical practice. METHODS: The hemorrhage information of 798 geriatric patients (over the age of 70 years) who needed long-term administration of rivaroxaban for anticoagulation therapy was constantly tracked and recorded through a well-established clinical follow-up system. Relying on the 27 collected clinical indicators of these patients, conventional logistic regression analysis, random forest and XGBoost-based machine learning approaches were applied to analyze the hemorrhagic risk factors and establish the corresponding prediction models. Furthermore, the performance of the models was tested and compared by the area under curve (AUC) of the receiver operating characteristic (ROC) curve. RESULTS: A total of 112 patients (14.0%) had bleeding adverse events after treatment with rivaroxaban for more than 3 months. Among them, 96 patients had gastrointestinal and intracranial hemorrhage during treatment, which accounted for 83.18% of the total hemorrhagic events. The logistic regression, random forest and XGBoost models were established with AUCs of 0.679, 0.672 and 0.776, respectively. The XGBoost model showed the best predictive performance in terms of discrimination, accuracy and calibration among all the models. CONCLUSION: An XGBoost-based model with good discrimination and accuracy was built to predict the hemorrhage risk of rivaroxaban, which will facilitate individualized treatment for geriatric patients.

Molecular evidence of ß-lactam resistant Staphylococcus aureus in equids with respiratory tract infections: Frequency and resistance modulation strategy.

The emergence of antimicrobial-resistant strains in Staphylococcus aureus (ß-lactam and methicillin-resistant) is an overwhelming issue worldwide. Using the purposive sampling technique, 217 equids samples were collected from district Layyah which were subjected to culturing followed by genotypic identification of mecA and blaZ genes by PCR. This study revealed that by phenotypic methods, a prevalence of 44.24%, 56.25%, and 47.92% was found for S. aureus, MRSA, and ß-lactam resistant S. aureus in equids. While genotypically, MRSA was found in 29.63% and ß-lactam resistant S. aureus in 28.26% of equids. In-vitro antibiotic susceptibility testing against S. aureus isolates harboring both mecA and blaZ genes showed a high resistance against Gentamicin (75%), followed by Amoxicillin (66.67%) and Trimethoprim+sulfamethoxazole (58.34%). In an attempt to re-sensitize the resistant bacteria to antibiotics, a combination of antibiotics and non-steroidal anti-inflammatory drugs (NSAIDs) was used which revealed synergistic effect of Gentamicin and Trimethoprim+sulfamethoxazole with Phenylbutazone; and Amoxicillin with Flunixin meglumine. Analysis of risk factors revealed significant association with the S. aureus-associated respiratory infection in equids. Phylogenetic analysis of mecA and blaZ genes showed a high resemblance of study isolate's sequences with each other and variable resemblance with already reported isolates obtained from different samples of neighboring countries. This study reports the first molecular characterization and phylogenetic analysis of ß-lactam and methicillin resistant S. aureus in equids in Pakistan. Moreover, this study will help in the resistance modulation of resistant antibiotics (Gentamicin, Amoxicillin, Trimethoprim+sulfamethoxazole) and provide a good insight into planning an effective therapeutic regime.

Evidence and Molecular Characterization of Multidrug Resistant Staphylococcus aureus Isolated From Equines in Pakistan.

The purpose of the current study was to investigate the nasal colonization and drug resistance profile of Staphylococcus aureus, methicillin-resistant S. aureus (MRSA), and vancomycin-resistant S. aureus (VRSA) in donkeys (n =63), mules (n = 42), and horses (n = 98). MRSA and VRSA were confirmed based on phenotypic and molecular methods, followed by phylogenetic analysis. Furthermore, the association of various animal and management-based risk factors with S. aureus colonization was also evaluated. The presence of nuc gene on polymerase chain reaction showed an overall prevalence of 42.86% of S. aureus in equines. Based on Kirby-Bauer disc diffusion test, 26.44% of isolates showed resistance to vancomycin. Further, mecA and vanB genes were targeted which showed an overall 14.94% and 13.79% prevalence of methicillin and vancomycin-resistant isolates, respectively. The phylogenetic analysis revealed a significant variation of the study isolates with each other and with already reported sequences of mecA and vanB genes. Risk factor analysis revealed that raising purpose (P = .011), work intensity (P < .001), stocking density (P = .006), presence of other livestock animals in surroundings (P = .043), and common drinking water source (P = .023) as significant. Antimicrobial susceptibility testing of MRSA and VRSA isolates showed high resistance to various commonly used antibiotics. Furthermore, all the tested isolates showing resistance to three or more than three antibiotics were considered multiple drug-resistant. The current study manifests the molecular evidence of MRSA and VRSA isolated from equines in Pakistan which will help to address the emerging issue of multidrug resistance in S. aureus in equines and emphasizes the need for possible measures to tackle this issue.

Computational network analysis of host genetic risk variants of severe COVID-19.

BACKGROUND: Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks. RESULTS: We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein-protein interaction networks. We identified 24 protein-protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction. CONCLUSIONS: This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.