Simple Logistic Regression Research Articles

Glycemic Laboratory Values Are Associated With Increased Length of Stay and 90-Day Revision Risk Following Surgical Management of Adult Spinal Deformity

Diabetes mellitus (DM) is a common comorbidity among patients undergoing spinal fusion for adult spinal deformity (ASD) surgery. An elevated Hemoglobin A1c (HbA1c) and elevated postoperative glucose have been shown to increase the risk of complications following spine and other orthopaedic surgeries; however, data is limited for ASD. To investigate glycemic control and ASD surgery to inform surgical decision making, medical optimization, and patient education. Retrospective cohort. Total of 106 adult patients undergoing surgical correction for ASD with an HbA1c drawn within six months preoperatively or two weeks postoperatively and valid plasma glucose levels throughout postoperative hospital stay. Length of stay, 90-day wound complication, 90-day readmission, 90-day revision. All patients undergoing spinal fusion of seven or more levels between 2021 and 2023 at two large academic medical centers were identified using institutional data acquisition software. Medical charts were then manually reviewed to obtain and confirm demographic, laboratory, and surgical characteristics and outcomes. Laboratory characteristics included preoperative HbA1c, mean postoperative glucose (PG), and maximum PG. Surgical characteristics and outcomes included procedure time, estimated blood loss (EBL), length of inpatient stay (LOS), transfusion requirement, 90-day complications, 90-day revision, and 90-day readmission. Bivariate analysis was performed followed by simple and multiple regression analysis. Odds ratios were established relative to the laboratory threshold values informed by receiver operating characteristics. Of 872 original procedures identified, 106 patients (12.2%) were adults with preoperative HbA1c and postoperative plasma glucose measurements who underwent surgery for a diagnosis of ASD. Median patient age was 67 years (IQR 59-72 years), 59 (55.7%) were female, and 96 (90.6%) were of Caucasian race. Median LOS was 7 days (IQR 5-10 years) and median HbA1c was 5.9% (IQR 5.3%-6.5%). Higher preoperative HbA1c was correlated with increased LOS (R=0.22, P=0.023). The odds ratio for patients requiring extended LOS was 2.49 (95% CI 1.06-5.86, P=0.034) for those with HbA1c ≥6.3%. Multiple regression analysis of LOS identified HbA1c [B= 1.51 (95% CI 0.32-2.70), P=0.013] as a positive predictor of LOS and mean PG [B= -0.05 (95% CI -0.10-(-0.01), P=0.019] as a weakly negative predictor of LOS. Upon simple logistic regression, the odds ratio for 90-day revision was 1.81 (95% CI 1.02-3.19, P=0.042) for every unit increase in HbA1c. Patients with mean PG ≥165 mg/dL [OR=5.76 (95% CI 1.28-26.01), P=0.024] were at increased risk for 90-day revision. Glycemic laboratory values do not seem to predict 90-day wound complications or 90-day readmission following surgery for ASD. Elevated preoperative HbA1c is associated with increased LOS and risk for revision within 90 days of ASD surgery. Postoperative hyperglycemia is also associated with increased 90-day revision risk. To our knowledge, this study is the first to evaluate HbA1c and outcomes following ASD surgery. These findings can be leveraged to inform preoperative medical optimization and highlight the importance of glycemic control in ASD patients undergoing corrective surgical intervention.

Alveolar Bone Reconstruction Simultaneous to Implant Removal due to Advanced Peri-Implantitis Defects: A Proof of Concept.

To evaluate the safety and effectiveness of alveolar bone reconstruction simultaneous to implant removal due to peri-implantitis. Partial or fully dentulous patients subjected to implant removal due to advanced peri-implantitis (≥ 50% of bone loss) lesions and seeking to have the failed implant replaced for esthetic or functional reasons were consecutively included. Guided bone regeneration was performed by means of a mixture of xenograft and autogenous bone and a ribose cross-linked barrier membrane. Re-entry for implant placement was performed at 4-month follow-up. Overall, six radiographic variables were assessed before (T0) and after (T1) alveolar bone reconstruction at four levels in ridge width (RW) and height (RH). Peri-implant conditions were evaluated at latest follow-up. Simple and multiple binary logistic regression models were calculated using generalized estimation equations to evaluate the effect of baseline upon reconstructive outcomes. In total, 20 patients (nimplant = 39) met the inclusion criteria. Alveolar RW and RH were augmented from T0 to T1 at all levels. All implants achieved primary stability. Only ~13% were subjected to ancillary bone regeneration simultaneous to implant placement. After a mean follow-up period after loading of ~2.2 years, ~70% implants demonstrated peri-implant health, while mucositis was diagnosed in the remaining implants. The performance of alveolar bone reconstruction in residual partially contained defects simultaneous to implant removal due to peri-implantitis lesions demonstrates being safe and effective for implant site development.

GLASGOW-BLATCHFORD AND ROCKALL SCORE UTILITY IN PREDICTING FINDINGS ON VIDEO CAPSULE ENDOSCOPY IN PATIENTS ADMITTED WITH OVERT SMALL BOWEL BLEEDING

Background and Aims Glasgow-Blachford (GBS) and Rockall scores are recognised tools to prioritize patients with upper gastrointestinal bleeding. Its utility in predicting findings on capsule endoscopy (CE) in patients with overt small bowel bleeding (OSBB) remains unclear. The aim was to assess the use of these scores in predicting relevant findings on CE and outcome among patients with suspected OSBB. Methods Retrospective analysis from January 2019 to June 2022. Clinical parameters and scores were collected at presentation and at 24 hours. Univariate analysis used simple logistic regression, chi-squared test or Mann-Whitney as needed. ROC analysis was performed selecting the optimal cut-off point maximized by the Youden index. Results 79 patients were included. 62% had relevant findings. The predictor showing the highest discrimination ability was the Initial GBS (AUC 0.625 95%CI 0.49 – 0.76). The optimal cut-off point was at least 4, with a sensitivity 98%, specificity 30% and accuracy 72%. Multivariable regression analysis showed inpatient status on CE (OR 117.27; CI 11.32 – 4492.93; p=0.001), shorter time to CE (OR 1.02; CI 1.01 – 1.04 p=0.018), higher initial GBS (OR 1.22; CI 1.06 – 1.43 p=0.009) and higher GBS within 24 hours (OR 1.19; CI 1.04 – 1.37 p= 0.013) were predictive factors for relevant findings on CE, with a model AUC 0.802, Sensitivity 91.8% and Specificity 63.3%. Conclusions GBS and Rockall score were useful in predicting relevant findings on CE in this cohort of patients with suspected OSBB. In patients with GBS 5 or higher, an early CE during the same admission, is warranted.

Low psychological resilience and physical fitness predict attrition from US Marine Corps Officer Candidate School training

ABSTRACT The objective is to examine the predictors of attrition in male and female candidates undergoing a 10-week early career military training program. 1006 candidates (79.5% male, 24.7 ± 3.2 years) consented to participating in a larger study examining predictors of injury during US Marine Corps Officer Candidates School (OCS). Participants completed a blood draw, demographic and psychological characteristics questionnaires, and two fitness tests. Participants were then grouped based on successful completion of OCS or not. Associations between potential predictors and attrition were analyzed using simple logistic regression analyses, followed by a backward stepwise elimination method. Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to determine the accuracy of the attrition prediction model. 260 candidates (25.8%) attritted over the 10-week training, with the highest number of discharges during week 5. Musculoskeletal injury (MSKI) was the most common cause of attrition (30%), followed by non-MSKI medical (21.5%), and volitional withdrawals (19.6%). Sex, body mass index (BMI), resilience, initial physical fitness test score, combat fitness test (CFT) score, and prior military service were all significantly associated with attrition from OCS (all p < .05). The final prediction model of attrition included CFT score (p = .027) and resilience (p = .018). Multiple demographic, psychological, and fitness characteristics are associated with attrition from an early career military training course (OCS) and may be utilized as part of early screening procedures to identify and provide guidance for individuals at risk for not completing OCS.

Association between Serum Fatty Acids Profile and MetScore in Women with Severe Obesity

Background: Metabolic syndrome (MetS) is a set of conditions associated with an increased cardiovascular risk. Several serum fatty acids (FAs) seem to play an essential role in the development of cardiometabolic diseases and mortality. Thus, it is imperative to explore the impact of FAs on MetS parameters, using an early MetS screening tool such as MetScore, which is readily available in clinical practice. Aim: The aim of this study was to assess the potential correlation between serum FAs and cardiovascular risk using a MetScore. Methods: This cross-sectional study involved 41 women with severe obesity. The MetScore was calculated, and participants were categorized into high- and low-cardiovascular-risk groups based on the median MetScore value. Gas chromatography was used to quantify serum FAs. Generalized Linear Models were used to compare group means. The association was assessed through simple logistic regression, and an adjusted logistic regression was conducted to validate the association between Metscore and serum FAs. Results: The high-cardiovascular-risk group exhibited elevated values of HOMA-IR, palmitic, oleic, cis-vaccenic, and monounsaturated fatty acids, as well as the SCD-18C, indicating a heightened cardiovascular risk. Conversely, HDL-c, QUICK, gamma-linolenic, and eicosatetraenoic fatty acids showed lower values compared to the low-risk group. Conclusions: Women with severe obesity and high cardiovascular risk have lower values of some omega-3 and omega-6 FAs, considered cardioprotective and anti-inflammatory, and have higher lipogenic activity and FAs, correlated with high cardiovascular risk. These findings emphasize the need to address lipid metabolism in this population as a therapeutic target to reduce cardiovascular risk. Future research should explore clinical interventions that modulate fatty acid metabolism to mitigate cardiometabolic complications.

Prevalence of low back pain and associated factors among medical students in Wachemo University Southern Ethiopia

Low back pain(LBP) is the most common musculoskeletal disorder in adults. According to previous studies medical students were found vulnerable for the development of LBP. We assessed the prevalence of LBP and associated factors among Medical students in Wachemo University, Southern Ethiopia. An institution-based cross-sectional study design and simple random sampling technique was employed to select 370 medical students. A structured pretested interviewer administered questionnaire was used to collect the data. The data were entered into Epi-info version 3.1 and analysed by SPSS version 25. Analytical and descriptive statistics were conducted. Simple and multiple logistic regression analyses were employed to assess factors associated with LBP. Variables at p-value ≤ 0.25 in simple logistic regression analysis were entered into multiple logistic regression. Statistical significance was declared at P-value, < 0.05 in multiple logistic analysis. The prevalence of low back pain among medical students was found to be 40.1%with 95% CI (38.5–41.8). Being male students [AOR (95% CI): 1.83 (1.09–3.08)], design of study sitting chairs without back support [adjusted odds ratio(AOR) (95% C.I): 2.81 (1.74–4.55)], stress during class [AOR (95% C.I): 2.60 (1.56–4.35)], and daily study hours greater than 6 h and above [AOR: 4.33, 95% CI (2.30–8.12)] had a significant association with LBP. The prevalence of LBP in this study is high. Better ergonomic facilities and psychosocial supports to medical students are recommended to reduce the effects of predisposing factors on LBP.

Presence of cholestasis and its impact on survival in SARS-CoV-2 associated acute respiratory distress syndrome.

Data on cholestasis and biliary injury in patients with COVID-19 are scarce. The primary aim of this study was to evaluate the prevalence of cholestasis and factors associated with its development and outcome in critically ill patients with COVID-19 associated acute respiratory distress syndrome (ARDS). In this retrospective exploratory study, COVID-19 patients with ARDS admitted to an intensive care unit (ICU) at the Medical University of Vienna were evaluated for the development of cholestasis defined as an alkaline phosphatase level of 1.67x upper limit of normal for at least three consecutive days. Simple and multiple logistic regression analysis was used to evaluate parameters associated with development of cholestasis and survival. Of 225 included patients 119 (53%) developed cholestasis during ICU stay. Patients with cholestasis had higher peak levels of alkaline phosphatase, gamma-glutamyl transferase, bilirubin and inflammation parameters. Factors independently associated with cholestasis were extracorporeal membrane oxygenation support, ketamine use, high levels of inflammation parameters and disease severity. Presence of cholestasis and peak ALP levels were independently associated with worse ICU and 6-month survival. Development of cholestasis is a common complication in critically ill COVID-19 patients and represents a negative prognostic marker for survival. It is associated with disease severity and specific treatment modalities of intensive care.

Is e-cigarette advertising associated with e-cigarette use among young people? New survey evidence from Poland.

Young people are routinely exposed to e-cigarettes advertising. We examined the impact of e-cigarette advertising on e-cigarette use in a large representative sample of adolescents. Data came from cross-sectional sample of the nationwide study on the health effects of tobacco products called PolNicoYouth, which included adolescents aged 15-18 years (N = 7,498). Data were collected through a detailed questionnaire recommended by international health organizations for monitoring tobacco use by adolescents. Simple and multiple logistic regression analyzes were conducted, adjusting for sex, age, type of school, place of residence, smoking of traditional cigarettes and parental smoking. Frequencies and proportions for descriptive statistics, and adjusted odds ratios with 95% confidence intervals for logistic regression models were reported. Approximately, 56% of interviewees had noticed some form of e-cigarettes advertising. Exposure to e-cigarette advertising was significantly associated with ever use of e-cigarettes (OR = 1.29; 95% CI: 1.09-1.53). Exposure to e-cigarette advertising via club/pub/disco was significantly associated with current e-cigarette use (OR = 1.58; 95% CI: 1.06-2.36). Adolescents who have ever used e-cigarettes were more likely than never users to report exposure to advertisements on club/pub/disco (OR = 1.57; 95% CI: 1.08-2.30) and internet (OR = 1.22; 95% CI: 1.01-1.47). Despite the applicable advertising restrictions, the majority of young people declared contact with e-cigarette advertising, which shows the urgent need for more global action. The internet and advertisements in clubs, pubs and discos seem to be the key places of exposure. These forms of exposure need to be urgently addressed given their clear link to e-cigarette use.

6909 Mortality and Readmission Rates for Inpatients with Diabetic Foot Ulcer in a Tertiary, Urban Medical Center: A Five-Year Retrospective Review

Abstract Disclosure: A. Herrera Chancay: None. R. Lopez Fanas: None. H. Tabassum: None. J. Daily: None. A. Myers: None. Background: Diabetic Foot Ulcer (DFU) is a severe complication of diabetes mellitus and is associated with high rates of morbidity and mortality. The incidence of DFUs and amputation disproportionately impact Black and Hispanic populations. DFU is also associated with a high rate of hospital readmissions and prolonged length of stay (LOS). The goal of this study was to examine 1-year mortality data, LOS and readmission rate. Methods: This study was a retrospective chart review of 1348 patients admitted to three hospitals in our system in the Bronx from 6/1/16 to 5/31/21. Data was extracted from the EPIC® electronic health records, based on the diagnoses ICD 10 codes, E10.621 and E11.622. Inclusion criteria was patients admitted with an active DFU regardless of other admission diagnosis, age 18 years or above. The index admission was defined as the first admission in our medical records within the date range. Patients were excluded if their index admission was not accessible through our EMR. Simple logistic regression and multiple logistic regression were used to analyze the association between variables of interest and mortality at index admission and at 1-year, LOS and re admissions. Results: Of the 650 eligible patients, the mean age was 59 + 13 years, 70% of patients were male, and majority were non-White (88%). Mortality was 1% during the index admission and the risk increased to 6% at 1 year after the index admission. Readmission with an active DFU from the index admission occurred in 15% of patients within 30-days, 32% of patients within 90 days, and 55% of patients within 1 year. The mean length of stay was 9 +7.5 days. Discussion: Our study in an urban region has identified high rates of mortality and costs associated with DFU, which has been reported in many settings. This patient population is high risk for poor outcomes and targeted programs are needed to reduce mortality and provide care to reduce readmissions. Future studies that explore the challenges of DFU health care and that test interventions are needed to improve DFU related health outcomes. Presentation: 6/2/2024

8760 Does an Increased Size of Thyroid Nodules Correlate with a Higher Probability of Intermediate or High-Risk Histopathological Features for Recurrence?

Abstract Disclosure: R. Pishdad: None. N. Yousefzadeh: None. E. Gough: None. L. Rooper: None. J.S. Mammen: None. Does an increased size of thyroid nodules correlate with a higher probability of intermediate or high-risk histopathological features for recurrence? Background: The existing practice guidelines recommend total thyroidectomy for solitary nodules exceeding 4 cm regardless of other pre-operative findings. We hypothesize that through comprehensive pre-operative assessments, particularly including a thorough neck ultrasound, even nodules exceeding 4 cm that would otherwise meet ATA criteria for lobectomy (i.e., lacking extrathyroidal extension and suspicious lymphadenopathy) will not exhibit occult high-risk features at a higher rate compared to nodules measuring 1-4 cm. Consequently, these larger nodules would not necessitate a higher rate of completion thyroidectomy. Methods: Solitary thyroid nodules with a largest dimension ≥ 1 cm and operated on at a single institution between 2005 to 2023 were assessed to identify those that would have met ATA criteria for lobectomy. Surgical pathology reports were reviewed to perform risk stratification following ATA guidelines. Preoperative cytopathology, ultrasound characteristics, and patient demographics were considered as covariables. Statistical analyses were performed with R programming language. Simple logistic regression and multivariable logistic regression were performed to analyze the finding of occult intermediate or high-risk features based on size. Results: We identified 461 cases of solitary nodules without extrathyroidal extension or lymph node involvement (406 nodules 1-4 cm; 60 nodules ≥ 4 cm). Patients with larger nodules were more likely to be male than those with smaller nodules (52% versus 26%; P value &amp;lt;0.001). Interestingly, while the majority of smaller nodules meeting criteria for lobectomy were suspicious or malignant by cytopathology (Bethesda 5 and 6), only 20% of larger nodules that met criteria were malignant, with 68% either Bethesda 3 or 4 (p&amp;lt;0.001). There were no statistically significant associations between size or other variables such as age, race, sex, or positive family history and post-operatively assessed high/intermediate risk for recurrence. Conclusion: In this analysis of solitary nodules with larger sizes, the dimension itself did not emerge as a risk factor for occult intermediate or high-risk surgical pathology. Thus, the rates of completion thyroidectomy in appropriately screened patients would be acceptable even in patients with nodules greater than 4 cm. The majority of larger nodules that fulfill preoperative ATA criteria for lobectomy were assessed to be ACUS or a follicular neoplasm on pre-operative fine-needle aspiration. This suggests that the higher risk of more aggressive disease previously reported with larger nodules can be detected during preoperative assessment, emphasizing the essential role of neck US in the comprehensive evaluation of larger nodules. Presentation: 6/2/2024

8305 Assessing The Relationship Between Oral Health And Bone Disease Among Post-menopausal Women

Abstract Disclosure: N. Tahir: None. S. Ahmad: None. K. Batra: None. A. Gupta: None. K.E. Izuora: Research Investigator; Self; Novo Nordisk. Background: Menopause is associated with significant bone loss and worsening oral health, especially periodontal disease (PD). The purpose of this study was to understand the relationship between oral health and bone loss and the factors that influence this relationship. This will help better understand their pathophysiology and provide guidance for more appropriate care. Methods: ​​This cross-sectional study included post-menopausal women undergoing routine bone density evaluation at a diagnostic radiology center. After participants signed informed consent, histories were collected via an investigator-administered questionnaire, the oral cavity was inspected for teeth loss and PD, and a bone density assessment, interpreted by a radiologist, was obtained. The significance level was set at 5% and data were analyzed using chi-square and logistic regression tests. Results: In a sample of 100 eligible participants, the mean age and body mass index (BMI) were 68.17 ± 8.33 years and 29.59 ± 6.13 kg/m2 respectively. Twenty-three participants (23.0%) had T2DM, 29 (29.0%) had &amp;lt; 20 natural teeth and 17 (17.0%) had normal bone mineral density. In an unadjusted simple logistic regression, age, BMI, race/ethnicity, number of natural teeth, history of PD, and history of osteoporotic fracture were associated with bone loss. However, in the binary logistic regression, the only significant predictors of bone loss included age (aOR 1.171, p&amp;lt;0.001), BMI (aOR 0.763, p&amp;lt;0.001), and the history of osteoporotic fractures (aOR 21.273, p=0.021). Conclusion: Clinical variables associated with bone loss in our study included older age, lower BMI, and history of osteoporotic fracture. These are established risk factors for bone loss. Although unadjusted results suggest a relationship between oral health measures and bone loss, these relationships were not present when other factors were included in a multivariate model. These findings suggest PD by itself may not be a risk factor for bone loss but may reflect the similarity in the risk factors for both conditions. Presentation: 6/3/2024

Classifying Student Performance: An In-Depth Analysis Using Machine Learning Algorithms

In recent years, analyzing and predicting student performance has been a significant challenge for educational institutions. Early analysis of student data can reveal their strengths and weaknesses, aiding in the improvement of examination outcomes. Machine learning offers a powerful tool for predicting student performance by utilizing demographic and academic data. We can forecast the results and determine which classification algorithm has the highest accuracy from algorithms such as support vector machines, J48 decision trees, naive bayes, and simple logistic regression. As a result, the accuracy level is addressed in the conclusion of data statistics, featuring classification models. By analyzing the classification algorithms, the logistic regression approach provides a more efficient way for educators to identify patterns and trends in the performance of students. This study enables targeted processes for students who would normally perform poorly on examinations.

Tinnitus prevalence and care experience among population of Almaty city

The prevalence of tinnitus is increasing worldwide along with the aging population. The absence of a gold standard for diagnosis and treatment makes it difficult to assess the health status of a patient with tinnitus.The aim was to determine the prevalence of tinnitus among older adults in Almaty city and to evaluate the healthcare experience among the respondents who received treatment for tinnitus. MethodsA cross-sectional study was conducted among people aged 18 years and above in Almaty city. The data were collected using a questionnaire sent via a Google form and/or as a printed version. Fully completed responses were received from 851 respondents. The questionnaire consists of 31 questions. Simple and multiple logistic regression analyses were performed to identify the risk factors of tinnitus. ResultsThe prevalence of tinnitus in Almaty was 23.3%. The data showed that smoking and sleep regimen were associated with tinnitus. Older respondents indicated more symptoms associated with tinnitus than younger respondents did. Additional consultation was needed as part of the treatment of tinnitus. In addition, 49.4% of the respondents indicated a need of a support group for people with tinnitus. The respondents also indicated that the access to appropriate resources for the treatment of tinnitus was poor. ConclusionSimilar to other studies, this analysis confirmed that tinnitus is prevalent in the adult population of Almaty city. Future activities should include measures for the improvement of public awareness of the risk factors of tinnitus, and multidisciplinary teamwork among healthcare specialists should be improved.

Model-implied simulation-based power estimation for correctly specified and distributionally misspecified models: Applications to nonlinear and linear structural equation models.

Closed-form (asymptotic) analytical power estimation is only available for limited classes of models, requiring correct model specification for most applications. Simulation-based power estimation can be applied in almost all scenarios where data following the model can be estimated. However, a general framework for calculating the required sample sizes for given power rates is still lacking. We propose a new model-implied simulation-based power estimation (MSPE) method for the z-test that makes use of the asymptotic normality property of estimates of a wide class of estimators, the M-estimators, and give theoretical justification for the approach. M-estimators include maximum-likelihood, least squares estimates and limited information estimators, but also estimators used for misspecified models, hence, the new simulation-based power modeling method is widely applicable. The MSPE employs a parametric model to describe the relationship between power and sample size, which can then be used to determine the required sample size for a specified power rate. We highlight its performance in linear and nonlinear structural equation models (SEM) for correctly specified models and models under distributional misspecification. Simulation results suggest that the new power modeling method is unbiased and shows good performance with regard to root mean squared error and type I error rates for the predicted required sample sizes and predicted power rates, outperforming alternative approaches, such as the naïve approach of selecting a discrete selection of sample sizes with linear interpolation of power or simple logistic regression approaches. The MSPE appears to be a valuable tool to estimate power for models without an (asymptotic) analytical power estimation.

Lifestyle aspects are associated with common mental disorders in women over 40 years older in a population-based study

Background & AimsCommon mental disorders (CMD) are more prevalent in women, as well as noncommunicable diseases. Diet and physical activity are lifestyle modifiable factors that might help on managing these conditions. MethodsThis study aimed to investigate the association between lifestyle aspects (diet and physical activity) and common mental disorders in women aged 40+ years. Methods: This is a cross-sectional, population-based study (2015 ISA-Nutrition) with a representative sample of São Paulo-SP-Brazil urban residents. The present study was conducted with data from 467 women aged 40+ years old. Common Mental Disorders (dependent variable) were investigated by the Self-Reporting Questionnaire-20 (SRQ-20); the independent variables of interest were: the inflammatory potential of the diet was evaluated by dietary inflammatory index (DII), and physical activity level (evaluated by IPAQ) adopting the leisure dimension of physical activity. We considered as adjusting variables the presence of self-reported Noncommunicable Diseases (NCD), the age intervals (defined as 40-45, 46-50, 51-55, 56-60, 61+ years old), schooling, (according to years of formal education), Body Mass Index (BMI); and ethnicity (self-declared skin color). Simple and multi-adjusted logistic regression models were performed to investigate the associations. ConclusionsThe main findings indicate that the prevalence of CMD was 32.2%, and the frequency of having one or more NCD was 67.2%. In the final regression model, CMD was associated with the highest tertile of the DII (OR=2.215; p=0.003) and having three, and four or more NCD (OR= 6. 735; p<0.001, and OR= 3.874; p=0.033, respectively). Altogether, our results indicate that dietary inflammatory characteristics, and physical activity, along with NCD, are associated with CMD, in women aged 40+ years old, in different dimensions.

Impacts of clinical psychiatric posting experience on specialization intention and associated factors among Nursing Science students

BackgroundGlobally, there is increasingly high prevalence of mental disorders across all age groups and social classes with more being projected by 2030, but without commensurate resources for mental health care delivery especially in developing countries.PurposeThis study examined the impacts of clinical psychiatric posting on career choice in psychiatry among nursing students in Ebonyi state, Nigeria.MethodsA prospective cohort research design was used and data were collected using attitude towards psychiatry (ATP), mental illness clinician attitude scale (MICA-4) and researcher developed questionnaires on career choice in pre and post clinical posting approach. This study was conducted between November, 2023 to May 2024. A sample size of 400 students (with data collected before posting and after posting) were involved in the study. Data were coded, cleaned and analyzed using SPSS version 26. McNemar Test was used to determine effects of clinical posting on career choices in psychiatry. Simple and multiple logistic regressions were used to analyze data on determinants of career choices in psychiatry. The hypotheses (Null and alternative hypotheses) were tested at p-value < 0.05.ResultsPsychiatric and mental health nursing was one of the least preferred specialty, 21(6%) respondents showed interest before clinical posting and 25(7.1%) after the posting. Commonly preferred specialty was pediatric nursing (20.5%), community health nursing (17.1%) and midwifery (17.7%). McNemer test showed no statistically significant differences in choice of psychiatry before and after clinical posting. Key determinants of career choices were interest in psychiatry (AOR = 16.06(95% CI = 1.10, 14.96) P = 0.009), interest in community services (AOR = 4.01(95% CI = 1.32, 12.20)P = 0.014), family influence(AOR = 13.76(95% CI = 1.74, 108.57)p = 0.013) and job satisfaction(AOR = 0.10(95% CI = 0.03, 0.26)P < 0.001).ConclusionThe researcher therefore concluded that clinical psychiatric posting has no significant impacts on career choices in psychiatry among nursing students in Nigeria. Interest of the students, family influence and job satisfaction were significantly associated with career choices among the respondents.

Biological and ecological determinants of Hand Foot and Mouth Disease (HFMD) in Coastal District of Northeastern Peninsular Malaysia: A 5-Year retrospective study

Hand, foot, and mouth disease (HFMD) is a common viral communicable disease in Malaysia, characterized by its self-limiting nature, yet it leads to numerous outbreaks and fatalities, particularly among young children. The current study aimed to determine the prevalence, geographic distribution, temporal patterns, and associated factors of HFMD cases within the Bachok District of Kelantan, spanning the years 2018 to 2022. A retrospective cohort study analysed extract data on independent factors and notification status from the Communicable Disease Control Information System (CDCIS). Simple and multiple logistic regression analyses were employed on a cohort of 1351 HFMD’s notifications. The retrospective analysis reveals a predominant HFMD’s notification were males (56.7%). Outpatient care was common (98.4%), with primary health care being the main choice. Logistic regression indicates higher odds for HFMD in those attending primary health care or private practitioners, daycare attendees, during the Southwest Monsoon season, and before the Movement Control Order (MCO) implementation, emphasizing key risk factors for HFMD. This study’s integrative approach recognizes that health and disease are often influenced by a combination of factors spanning the ecological, biological, and clinical domains. Thus, emphasizing the need for a comprehensive understanding when formulating public health strategies particularly in primary healthcare settings and daycare facilities during the Southwest Monsoon season.

Parathyroid gland identification and angiography classification using simple machine learning methods.

Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualized parathyroid gland near-infrared indocyanine green angiographic fluorescence signals. Near-infrared indocyanine green-parathyroid gland angiography video recordings (Fluobeam® LX, Fluoptics, Grenoble-part of Getinge-Göteborg) from patients undergoing endocrine cervical surgery in a high-volume unit were used for model development. Computation (MATLAB, Mathworks, Ireland) included segmentation-identification of the parathyroid gland (by autofluorescence), image stabilization (by linear translation) and adjusted time-fluorescence intensity profile generation. Relative upslope and maximum intensity ratios then trained a simple logistic regression model based on expert interpretation and outcome (including hypoparathyroidism), with subsequent unseen testing for validation. The model was trained on 37 patient videos (45 glands, 29 judged well perfused by parathyroid gland angiography experts), achieving feature data separation with 100% accuracy, and tested on 22 unseen videos (27 glands, 15 judged well perfused), including four in real time. Segmentation-guided parathyroid gland detection correctly identified all parathyroid glands during unseen testing along with three additional non-parathyroid gland regions (90% positive predictive value). Subsequent time-fluorescence intensity profile extraction with vitality prediction was shown feasible in all cases within 5 min, with a 96.3% model accuracy (sensitivity and specificity were 93.3 and 100% respectively) when compared with expert judgement. Automatic parathyroid gland perfusion quantification using simple machine learning computational methods discriminates parathyroid gland perfusion in concordance with expert surgeon interpretation, providing a means for near-infrared indocyanine green-parathyroid gland signal evaluation.

Predicting patent lawsuits with machine learning

We use machine learning methods to predict which patents end up in court using the population of US patents granted between 2002 and 2005. We show that patent characteristics have significant predictive power, particularly value indicators and patent-owner characteristics. Furthermore, we analyze the predictive performance concerning the number of observations used to train the model, which patent characteristics to use, and which predictive model to choose. We find that extending the set of patent characteristics has the biggest positive impact on predictive performance. The model choice matters as well. More sophisticated machine learning methods provide additional value relative to a simple logistic regression. This result highlights the existence of non-linearities among and interactions across the predictors. Our results provide practical advice to anyone building patent litigation models, e.g., for litigation insurance or patent management more generally.

Impact of usage of electronic devices on sleep quality among healthcare professions students in Ajman, UAE

Due to the advancement in technology, people are using various electronic devices. People using electronics and the internet at inappropriate times may have a harder time falling asleep and have less sleep duration, and the sharp rise in electronic device use has numerous adverse effects. This study aimed to assess the impact of the usage of electronic devices on sleep and also to determine the factors influencing sleep among healthcare professions students. A cross-sectional study was conducted using a self-administered questionnaire. The association was assessed using the Chi-square test and simple binary logistic regression to identify the factors. Of the total 446, 36.4% reported not having problems during the past month in getting to sleep within 30 minutes. Internet use at school during a typical weekday, 22.2% use 2-4 hours a day; outside of school during a typical weekday, 24.7% use &amp;gt;6 hours. 34.3% use the internet &amp;gt;6 hours outside of school on weekends. The crude OR observed was 4.1, 3.7, 3.6 and 3.9 for 1-2, 2-4, 4-6, &amp;gt;6 hours respectively which is statistically significant. Factors that showed statistical significance for sleep duration were nationality and internet use outside the school during a typical weekend day. For how long it takes to fall asleep, the age group was the factor that showed statistical significance.