Ordinal Regression Research Articles

Digital breast tomosynthesis versus X-ray of the breast specimen for intraoperative margin assessment: A randomized trial

BackgroundInvolved resection margins after breast conserving surgery (BCS) often require a re-operation with increased patient anxiety and risk of impaired cosmesis.We investigated the number of re-operations due to involved resection margins after BCS comparing digital breast tomosynthesis(DBT) with X-ray for intraoperative margin evaluation.Furthermore, we assessed the diagnostic accuracy of these methods to predict histopathological margin status. Finally, we evaluated risk factors for re-operation. MethodsIn this randomized, non-blinded study, 250 invasive breast cancer patients were randomized (1:1), whereof 241 were analyzed intraoperatively with either DBT (intervention, n = 119) or X-ray (standard, n = 122). Pearson's chi-squared test, Fisher's exact test, t-test, logistic and ordinal regression analysis was used as appropriate. ResultsNo difference was found in the number of re-operations between the DBT and X-ray group (16.8 % vs 19.7 %, p = 0.57), or in diagnostic accuracy to predict histopathological margin status (77.5 %, CI: 68.6–84.9 %) and (67.3 %, CI: 57.7–75.9 %), respectively. We evaluated 5 potential risk factors for re-operation: Ductal carcinoma in situ (DCIS) outside tumor, OR = 9.4 (CI: 4.3–20.6, p < 0.001); high mammographic breast density, OR = 6.1 (CI: 1.0–38.1, p = 0.047); non-evaluable margins on imaging, OR = 3.8 (CI: 1.3–10.8, p = 0.016); neoadjuvant chemotherapy, OR = 3.0 (CI: 1.0–8.8, p = 0.048); and T2 tumor-size, OR = 2.6 (CI: 1.0–6.4, p = 0.045). ConclusionsNo difference was found in the number of re-operations or in diagnostic accuracy to predict histopathological margin status between DBT and X-ray groups. DCIS outside the tumor showed the highest risk of re-operation. Intraoperative methods with improved visualization of DCIS are needed to obtain tumor free margins in BCS.

Predicting clinical decline over 36 months with a memory‐based digital biomarker

AbstractBackgroundWord‐list recall tests are routinely employed in clinical practice for dementia screening. Process scoring and latent modeling of these tests, where underlying neurocognitive mechanisms are exploited, have shown potential to enhance test accuracy without requiring test redesign. We examined Embic’s digital biomarker M, a measure of recall derived from multinomial processing trees and hierarchical Bayesian computational methods, as a predictor of conversion to mild cognitive impairment (MCI) and Alzheimer’s disease (AD), and of increase in Clinical Dementia Rating (CDR) score.MethodsSecondary data analyses were carried out from ADNI data. M was computed from Rey’s AVLT data, and compared to standard AVLT clinical metrics (total and delayed recall). We conducted logistic regression analyses with diagnosis at 36 months (normal vs. MCI + AD) as outcome; all 169 participants were classified as normal at baseline, and 13 of these progressed to a clinical diagnosis (see Table 1). We controlled for baseline age, gender and years of education; and ran separate analyses with other metrics to avoid multicollinearity. We then repeated the same analytical framework with CDR scores (stable at 0 vs. increased to 0.5 or 1) at 36 months as outcome: stable participants were 141, and 24 increased (see Table 2). Covariates and predictors were the same as in the previous analysis.Results M predicted conversion to MCI or AD after three years (FDR‐corrected p value = 0.048), while neither AVLT total nor delayed recall did. Performance metrics showed that M generated 92% accuracy, or probability of yielding a correct classification, and 100% specificity, or no false positives (Figure 1). Analogously, M, but not standard AVLT metrics, also predicted a CDR increase after three years (FDR‐corrected p value = 0.003), with high accuracy (84%), specificity (96%), and precision (80%), or positive predictive value (Figure 2). Sensitivity analyses with ordinal regression broadly confirmed these findings.ConclusionsThese results indicate Embic’s digital biomarker M outperforms some of AVLT’s traditional metrics in identifying individuals who will progress to MCI and AD after three years, from a healthy baseline.

Brain plasticity and age after restoring elbow flexion with distal nerve transfers in neonatal brachial plexus palsy and nonneonatal traumatic brachial plexus injury using the plasticity grading scale.

Ulnar and/or median nerve fascicle to musculocutaneous nerve (MCN) transfers are used to restore elbow flexion following severe neonatal and nonneonatal brachial plexus injuries (BPIs). Restoring volitional control requires plastic changes in the brain. To date, whether the potential for plasticity is influenced by a patient's age remains unknown. Patients who had presented with a traumatic upper (C5-6 or C5-7) BPI were divided into two groups: neonatal brachial plexus palsies (NBPPs) and nonneonatal traumatic BPIs (NNBPIs). Both groups underwent ulnar or median nerve transfers to the MCN for elbow flexion restoration between January 2002 and July 2020. Only those who attained a British Medical Research Council strength rating of 4 were reviewed. The primary comparison between the two groups was the plasticity grading scale (PGS) score to determine the level of independence of elbow flexion (target) from forearm motor muscle movement (donors). The authors also assessed patient compliance with rehabilitation using a 4-point Rehabilitation Quality Scale. Bivariable and multivariable analyses were used to identify intergroup differences. In total, 66 patients were analyzed: 22 with NBPP (mean age at surgery 10 months) and 44 with NNBPI (age range at surgery 3-67 years, mean 30.2 years; mean time to surgery 7 months, p < 0.001). All NBPP patients obtained a PGS grade of 4 at the final follow-up versus just 47.7% of NNBPI patients (mean 3.27, p < 0.001). On ordinal regression analysis, after nature of the injury was excluded because of excessive collinearity with age, age was the only significant predictor of plasticity (β = -0.063, p = 0.003). Median rehabilitation compliance scores were not statistically different between the two groups. The extent of plastic changes that occur for patients to regain volitional control over elbow flexion after upper arm distal nerve transfers following BPI is influenced by patient age, with complete plastic rewiring more likely in younger patients and virtually ubiquitous in infants. Older patients should be informed that elbow flexion after an ulnar or median nerve fascicle transfer to the MCN might require simultaneous wrist flexion.

Effects of Bad News on Stock Returns and Analysts’ Recommendations: The Influence of Executive Gender

Although women are more conservative and more ethical than men, the proportion of female executives is still lower than that of men. Both Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs) have strong influences in making corporate financial decisions. However, most of the literature focuses only on CEOs and ignores CFOs. Therefore, when bad news happens, it is possible that a female CEO/CFO can better alleviate the negative impact. We thus employ 4,405 firm-year observations over the period of 1996–2018, of which 680 are unique companies listed on the S&amp;P1500 index, to examine how CEO and CFO gender influences stock returns and analyst recommendations. Our ordinary least squares and logistic regression results show that investors are pessimistic about companies led by female CEOs/CFOs, especially female CEOs. That is, when something bad happens, stock returns and analyst recommendations are worse for firms with female CEOs. Overall, this study is first to use stock returns to observe market reactions to firms with female CEOs/CFOs. In other words, the corporate remains unfriendly toward women, even those who are qualified as CEOs/CFOs

Satisfaction of Patients Family Reviewed from Caring Human Resources in Voluntry Counseling Testing HIV Poly Dr. Soekandar Hospital of Mojosari Kabupaten Mojokerto

Satisfaction of the patient's family is the most important thing so that the Hospital can develop. This can be created if medical personnel are able to provide good service. One of the indicators to support optimal service is managing the appropriate caring human resources. Therefore, the purpose of this study was to determine the effect of patient family satisfaction in the HIV Voluntary Counseling and Testing (VCT) polyclinic in terms of caring for human resources at Dr. Soekandar Mojosari. The research design used cross sectional. The sample of this research is 135 respondents. This study used a random sampling stratification technique with a research instrument using a questionnaire. Data analysis was used to analyze the caring relationship of human resources at Dr. Soekandar Mojosari used ordinal regression analysis techniques.

Perspective of Early Childhood Education Teachers on School Connectivity to Parental Support in the Context of Blended Learning During a Pandemi

Although we are now seeing a point where we can control the pandemic, its impact on education remains a major highlight. Schools around the world have been forced to make deep changes by switching to distance learning and adopting blended learning methods that integrate face-to-face and online learning. This transition not only creates challenges for students, teachers, and parents, and creates new opportunities to improve the way we educate and connect. This research explores the views of Early Childhood Education teachers in Semarang regarding School Connectedness and parent support during the pandemic. With 74 Kindergarten A and Kindergarten B teachers as participants, using the Ex post facto quantitative method in the 2021-2022 school year, this research utilized an online questionnaire via Google Forms. Ordinal regression analysis shows that parental support significantly influences School Connectedness (Wald = 7.318, sig. = 0.007). The novelty of the research lies in its focus on PAUD teachers in Semarang who are facing the challenges of distance learning and blended learning due to the pandemic. The benefits involve a deeper understanding of the crucial role of parental support in strengthening teacher-school-student relationships. The results of the research can be a basis for schools, teachers and parents to develop strategies to improve School Connectedness in the future, especially in an ever-changing learning context. Thus, this research contributes to our understanding of the factors that influence the quality of education in the pandemic era.

Pengaruh Gaya Kepemimpinan dan Motivasi Kerja terhadap Kinerja Karyawan di Dinas Kesehatan Bantul

Organizations must pay attention to factors that can increase employee performance, including work motivation and leadership styles that can increase work enthusiasm while creating a professional work attitude. The aim of this research is to determine the influence of leadership style and work motivation on employee performance at the Bantul District Health Service. This research method is a quantitative model, with a cross sectional approach. The sample used was 51 people, selected based on Purposive Sampling. Data were analyzed using multiple linear regression. The results of research using the Kendall Tau test on the leadership style variable on employee performance obtained a sig. (2-tailed) of 0.004 &lt; 0.05. The results of the work motivation test on employee performance obtained a sig. (2-tailed) of 0.000 &lt; 0.05. Based on the results of simultaneous Ordinal Regression Analysis, leadership style and work motivation on employee performance obtained a sig value of 0.000. Conclusion. There is a significant and significant influence of leadership style on employee performance, there is an influence of work motivation on employee performance, simultaneously there is an influence of leadership style and work motivation on employee performance.

Pain in Children and Adolescents with Spinal Muscular Atrophy: A Longitudinal Study from a Patient Registry.

Spinal muscular atrophy (SMA) is a devastating genetic neurodegenerative disease caused by the insufficient production of Survival Motor Neuron (SMN) protein. It presents different phenotypes with frequent contractures and dislocations, scoliosis, and pain. This study aims to report the prevalence and description of pain and how it affects daily life by analyzing a new ad hoc questionnaire. An observational study of patients under 18 years of age with SMA was conducted at two referral centers in Spain. Data were analyzed using a descriptive analysis and a Bayesian ordinal regression model to assess the association with clinical and demographic variables. Fifty-one individuals were included in this study, 27% of whom reported pain with a median duration of 5.2 years and a mean Visual Analogic Scale (VAS) score of 5. Notably, 77% were receiving disease-modifying treatment, with more than 50% receiving analgesic treatment. The Bayesian model showed that functional status, lower limb contractures, and number of visits have a high probability (>90%) of influencing pain. Thus, the prevalence of pain in the SMA population under 18 years is substantial, and its presence could be associated with lower limb contractures, better functional status, and higher RULM (Revised Upper Limb Module) scores.

Clinical Outcome Prediction of Early Brain Injury in Aneurysmal Subarachnoid Hemorrhage: the SHELTER-Score

BackgroundDespite intensive research on preventing and treating vasospasm and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage (aSAH), mortality and morbidity rates remain high. Early brain injury (EBI) has emerged as possibly the major significant factor in aSAH pathophysiology, emphasizing the need to investigate EBI-associated clinical events for improved patient management and decision-making. This study aimed to identify early clinical and radiological events within 72 h after aSAH to develop a conclusive predictive EBI score for clinical practice.MethodsThis retrospective analysis included 561 consecutive patients with aSAH admitted to our neurovascular center between 01/2014 and 09/2022. Fourteen potential predictors occurring within the initial 72 h after hemorrhage were analyzed. The modified Rankin Scale (mRS) score at 6 months, discretized to three levels (0–2, favorable; 3–5, poor; 6, dead), was used as the outcome variable. Univariate ordinal regression ranked predictors by significance, and forward selection with McFadden’s pseudo-R2 determined the optimal set of predictors for multivariate proportional odds logistic regression. Collinear parameters were excluded, and fivefold cross-validation was used to avoid overfitting.ResultsThe analysis resulted in the Subarachnoid Hemorrhage Associated Early Brain Injury Outcome Prediction score (SHELTER-score), comprising seven clinical and radiological events: age (0–4 points), World Federation of Neurosurgical Societies (0–2.5 points), cardiopulmonary resuscitation (CPR) (2 points), mydriasis (1–2 points), midline shift (0.5–1 points), early deterioration (1 point), and early ischemic lesion (2 points). McFadden’s pseudo-R2 = 0.339, area under the curve for death or disability 0.899 and 0.877 for death. A SHELTER-score below 5 indicated a favorable outcome (mRS 0–2), 5–6.5 predicted a poor outcome (mRS 3–5), and ≥ 7 correlated with death (mRS 6) at 6 months.ConclusionsThe novel SHELTER-score, incorporating seven clinical and radiological features of EBI, demonstrated strong predictive performance in determining clinical outcomes. This scoring system serves as a valuable tool for neurointensivists to identify patients with poor outcomes and guide treatment decisions, reflecting the great impact of EBI on the overall outcome of patients with aSAH.

Clarity and adaptability of instructions preventing the spread of the COVID-19 virus and its association with individual and organisational factors regarding the psychosocial work environment: a cross-sectional study

BackgroundIn Sweden, older people in residential care had the highest mortality rates, followed by those who received home care, during the coronavirus disease 2019 (COVID-19) pandemic. Staff working in the care of older people assumed responsibility for preventing the spread of the virus despite lacking the prerequisites and training. This study aimed to investigate the psychosocial work environment during the COVID-19 pandemic among staff in the care of older people and examine the factors associated with staff’s perceptions of the clarity of instructions and the ability to follow them.MethodsA cross-sectional study design was employed using a web survey. The staff’s perceptions of their psychosocial environment were analysed using descriptive statistics. The association between organisational and individual factors, as well as the degree of clarity of the instructions and the staff’s ability to follow them, were assessed using multivariate (ordinal) regression analysis.ResultsThe main findings show that perceptions of the clarity and adaptability of the instructions were primarily correlated with organisational factors, as higher responses (positive) for the subscales focusing on role clarity, support and encouragement in leadership at work were associated with the belief that the instructions were clear. Similarly, those indicating high job demands and high individual learning demands were less likely to report that the instructions were clear. Regarding adaptability, high scores for demands on learning and psychological demands were correlated with lower adaptability, while high scores for role clarity, encouraging leadership and social support, were associated with higher adaptability.ConclusionsHigh job demands and individual learning demands were demonstrated to decrease the staff’s understanding and adoption of instructions. These findings are significant on an organisational level since the work environment must be prepared for potential future pandemics to promote quality improvement and generally increase patient safety and staff health.

Analysis of the high‐pressure steam import behaviour of an integrated ethylene oxide/ethylene glycol petrochemical plant under different production scenarios

AbstractIntegrated ethylene oxide/ethylene glycols (EO/EG) plants are prominent energy consumers in the petrochemical sector, particularly concerning high‐pressure steam (HPS) usage which holds the potential for substantial energy savings. This study focuses on an unexplored territory: Examining the impact of EO catalyst type, selectivity, and glycols production capacity on HPS import in a plant in the Pars Special Economic Energy Zone (PSEEZ). Utilizing Python3 for data preprocessing and ordinary least squares linear regression analysis, we evaluate how varying catalyst loads and production scenarios influence HPS import. Regression models are created, encompassing normal and efficient HPS import scenarios, yielding positive outcomes in terms of correlation, mean error percentage, and R2 analysis. Comparing normal and efficient HPS import models highlights potential savings, uncovering opportunities to conserve between 45 and over 200 tonnes per day of HPS. We also explore the plant's HPS behaviour under 1% selectivity and production capacity reductions. Notably, catalyst activity decline markedly escalates HPS import for hybrid catalysts, while selectivity decline decreases HPS import for high‐activity catalysts. The models demonstrate that HPS import is ~150 tonnes per day more sensitive to a 1% change in selectivity compared to production capacity. Moreover, when comparing high activity and hybrid catalyst scenarios in normal and efficient cases, the most substantial HPS import difference arises under conditions of low selectivity, amounting to nearly 200 tonnes per day. Our methodology applies to other EO/EG plants. It is incorporated into our plant's energy management system, enabling continuous monitoring of steam import behaviour relative to catalyst and plant performance.

1492. Gender-Specific Targets for Primary Prevention in People Living with HIV : Applying Life's Simple 7 to a Gender-Stratified Population of ART-Naive People Living with HIV in Tanzania

Abstract Background Cardiovascular disease (CVD) represents a major cause of premature mortality in people living with HIV (PLWH). However, morbidity is not equal between males and females. There is a need to better understand how gender influences cardiovascular health (CVH) in PLWH in order to identify targets for intervention. Therefore, we applied the Life's Simple Seven (LS7) scale to a gender-stratified cohort of ART-Naive PLWH and HIV-uninfected controls in adults. Methods A cross-sectional analysis was conducted on a cohort of ART-naive PLWH and HIV-uninfected adults recruited from HIV clinics between June 2016 and August 2019 in Mwanza, Tanzania (HIV&amp;HTN cohort). We applied modified Life's Simple Seven (LS7) definitions (Table 1) and compared the distribution of Ideal LS7 metrics between males and females of both study groups. Each LS7 metric was categorized as ideal (2 points), intermediate (1 point) and poor (0 point) and ordinal regressions were employed to investigate associations between gender and each individual LS7 metric. Regressions were adjusted for HIV status, age, income, education level. Results Our study included 997 participants, with 493 PLWH (68.7% female) and 504 HIV-uninfected (66.4% female). As displayed in Figure 1, the distribution of Ideal LS7 metrics differed between the males and females in both study groups. Males had a higher prevalence of ideal physical activity (aOR=4.12 [95%CI=3.11 to 5.44], p&amp;lt; 0.001) and ideal BMI (aOR=5.10 [3.47 to 7.49], p&amp;lt; 0.001) but lower prevalence of ideal smoking (aOR=0.037 [0.021 to 0.065], p&amp;lt; 0.001) and ideal blood pressure (aOR= 0.65 [0.50 to 0.85], p=0.002). The magnitude of these differences also varied by HIV status such that they were larger in PLWH than HIV-uninfected group for smoking (41.3% vs 26.4%), physical activity (41.6% vs 24.8%) and blood pressure (12.7% vs 9.2%) metrics. By contrast, these differences were less pronounced in PLWH vs HIV-uninfected group for the BMI metric (23.1% vs 29.7%). Figure 1: Distribution of Ideal Life's Simple 7 metrics, stratified by gender for both PLWH and HIV-uninfected controls Conclusion Cardiovascular health profiles vary by gender and HIV status, with stark differences between male and female PLWH for most metrics. Gender-specific interventions targeting smoking cessation, blood pressure control in male PLWH and physical activity, weight loss in female PLWH are warranted to mitigate CVD risk. Disclosures All Authors: No reported disclosures

2951. Nursing home clinician characteristics associated with simulated urinary tract infection treatment decision-making

Abstract Background Antibiotic overuse and misuse are common in nursing homes (NHs). Urinary tract infection (UTI) is the most common indication for antibiotics in NHs. We conducted a clinical vignette experiment to identify clinician-level characteristics associated with suboptimal UTI treatment decision-making among a sample of NH clinicians. Methods Six clinical vignettes, two designed to assess clinicians’ treatment threshold and four designed to assess antibiotic choice decision-making, were created through an iterative process. NH clinicians were recruited nationally via professional organizations from December 2021 to April 2022. Clinical vignettes were shared using a web-based survey tool (Qualtrics) during which participants were asked if they would initiate antibiotics and which one. Participants provided demographic information, including degree, specialty training and NH experience. A multivariable logistic regression model with the decision to initiate antibiotic therapy (Yes/No) as the dependent variable and a multivariable ordinal regression model with number of vignettes for which a fluoroquinolone (FQ) was empirically chosen as the dependent variable were constructed in R. Results A total of 298 NH clinicians, whose characteristics are detailed in Table 1, responded to the survey. Despite national guidelines not recommending treatment for asymptomatic bacteriuiria (ASB), 10.4% of participants chose to initiate antibiotics when presented with the ASB vignette. Physicians (vs. APPs) and clinicians with ≥ 10 years NH experience were less likely to initiate antibiotics for ASB (Table 2). Empiric treatment was withheld for simple cystitis by 38.9% of clinicians, with APPs more likely to withhold antibiotics than physicians (Table 2). Across the four cases assessing empiric antibiotic choice, 38.3% of clinicians chose a FQ in at least one clinical case (Table 1). Clinicians with more years of NH-practice experience were more likely to prescribe a FQ (aOR 2.41, 95% CI 1.47-3.95, p&amp;lt; 0.01, Table 2). Respondent Characteristics Abbreviations: Advanced Practice Provider (APP); Asymptomatic bacteriuria (ASB); Fluoroquinolone (FQ), Nursing Home (NH). Effect of clinician credentials, training, and experience on antibiotic prescribing for urinary tract infection Abbreviations: * reference; Adjusted odds ratio (aOR); Confidence interval (CI); Asymptomatic bacteriuria (ASB); Advanced practitioner (APP) Conclusion Our results indicate that specific clinician characteristics are associated with suboptimal antibiotic prescribing. This suggests that tailoring stewardship interventions to clinician-specific factors may augment ongoing efforts to improve antibiotic use in NHs. Disclosures Lindsay Taylor, MD, MS, Merck: Grant/Research Support Robin Jump, MD, PhD, Merck: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support

Modeling and Prediction of Thermal Deformation Errors in Fiber Optic Gyroscopes Based on the TD-Model

For a fiber optic gyroscope, thermal deformation of the fiber coil can introduce additional thermal-induced phase errors, commonly referred to as thermal errors. Implementing effective thermal error compensation techniques is crucial to addressing this issue. These techniques operate based on the real-time sensing of thermal errors and subsequent correction within the output signal. Given the challenge of directly isolating thermal errors from the gyroscope’s output signal, predicting thermal errors based on temperature becomes necessary. To establish a mathematical model correlating the temperature and thermal errors, this study measured synchronized data of phase errors and angular velocity for the fiber coil under various temperature conditions, aiming to model it using data-driven methods. However, due to the difficulty of conducting tests and the limited number of data samples, direct engagement in data-driven modeling poses a risk of severe overfitting. To overcome this challenge, we propose a modeling algorithm that effectively integrates theoretical models with data, referred to as the TD-model in this paper. Initially, a theoretical analysis of the phase errors caused by thermal deformation of the fiber coil is performed. Subsequently, critical parameters, such as the thermal expansion coefficient, are determined, leading to the establishment of a theoretical model. Finally, the theoretical analysis model is incorporated as a regularization term and combined with the test data to jointly participate in the regression of model coefficients. Through experimental comparative analysis, it is shown that, relative to ordinary regression models, the TD-model effectively mitigates overfitting caused by the limited number of samples, resulting in a substantial 58% improvement in predictive accuracy.

Factors of Cloud Computing and Digitization of SMEs in Peru using PLS-SEM Structural Analysis

The objective of this research is to determine the main factors of cloud computing that explain the variability of the digitalization of SMEs in Peru. The type of research is basic, with a quantitative approach, at the explanatory level, with a non-experimental design, and a sample of 211 SMEs in Peru. The research concludes that there is a significant influence of cloud computing and certain factors in the digitalization of SMEs in Peru. An exploratory factor analysis (EFA) was carried out, obtaining values above 0.90 for the Kaiser-Meyer-Olkin tests, as well as the Barlett's sphericity test p=0.000 and the analysis of variance explained by 66.26% for cloud computing and 68.28% for the digitalization of SMEs, determining that the interrelation of the items is satisfactory. Confirmatory factor analysis (CFA) was applied, obtaining values for CFI=0.901, and TLI=0.890, being close to 1, thus determining that the models are appropriate and give validity to the construct. Additionally, construct validity is performed by PLS-SEM analysis of the model. The research determines that there is a moderate to strong correlation of part of the factors of cloud computing in the digitalization of SMEs, through Spearman's correlation coefficient obtaining values higher than 0.685, as well as through the ordinal regression that through the Pseudo R-squared in the Nagelkerke indicator obtained 80% and in the model adjustment obtaining Sig = 0.00. These results were contrasted with the bootstrapping method through the PLS-SEM analysis obtained for the T-statistic values greater than 2, as well as for the P-values lower than 0.05, these results determine that there is a causal relationship between the factors of cloud computing and digitalization of SMEs.

Association of diabetes and glycemic control with left atrial function: The Atherosclerosis Risk in Communities (ARIC) study

Background and aimsAlthough glycemic status is associated with impaired cardiac structure and function, less is known on left atrial (LA) function across the glycemic spectrum. We evaluated the association of diabetes and glycemic control with LA function in a community-based cohort of older adults. Methods and resultsThis cross-sectional analysis included 5075 participants from the Atherosclerosis Risk in Communities Study (mean age 75.5 years, 58 % women, and 20 % Black adults) with echocardiographic strain data for LA reservoir, conduit, and contractile function. Multivariable linear regression was used to assess associations of diabetes status and glycemic control with LA function. In participants without diabetes, we used ordinal linear regression to evaluate associations of fasting glucose and HbA1c with LA function. Compared to individuals with a normal fasting glucose, prevalent diabetes was associated with 0.68 % lower LA conduit function (95 % confidence interval (CI): 1.11 to −0.25) and prediabetes a 0.47 % reduction (95 % CI: 0.85 to −0.09) in fully adjusted analyses. Persons with diabetes and high HbA1c (HgbA1c ≥ 7 % vs <7 %) had 1.05 % lower LA conduit function (95 % CI: 1.63, −0.48). Among individuals without diagnosed diabetes, higher fasting glucose, but not HbA1c, was significantly associated with worse LA conduit function. No significant associations were observed for LA reservoir and contractile function. ConclusionsA history of diabetes, prediabetes, and higher fasting glucose levels in persons without diabetes were associated with worse LA conduit function. Corroborative research is needed in prospective cohorts as well as studies that explore underlying mechanisms.

Fundament for a methodological standard to process hip accelerometer data to a measure of physical activity intensity in middle-aged individuals.

There is a lack of a methodological standard to process accelerometer data to measures of physical activity, which impairs data quality and comparability. This study investigated the effect of different combinations of settings of multiple processing components, on the measure of physical activity and the association with measures of cardiometabolic health in an unselected population of middle-aged individuals. Free-living hip accelerometer data, aerobic fitness, body mass index, HDL:total cholesterol ratio, blood glucose, and systolic blood pressure were achieved from 4391 participants 50-64 years old included in The Swedish CArdioPulmonary bioImage Study (SCAPIS) baseline measurement (cross-sectional). Lab data were also included for calibration of accelerometers to provide comparable measure of physical activity intensity and time spent in different intensity categories, as well as to enhance understanding. The accelerometer data processing components were hardware recalibration, frequency filtering, number of accelerometer axes, epoch length, wear time criterium, time composition (min/24 h vs. % of wear time). Partial least regression and ordinary least regression were used for the association analyses. The setting of frequency filter had the strongest effect on the physical activity intensity measure and time distribution in different intensity categories followed by epoch length and number of accelerometer axes. Wear time criterium and recalibration of accelerometer data were less important. The setting of frequency filter and epoch length also showed consistent important effect on the associations with the different measures of cardiometabolic health, while the effect of recalibration, number of accelerometer axes, wear time criterium and expression of time composition was less consistent and less important. There was a large range in explained variance of the measures of cardiometabolic health depending on the combination of processing settings, for example, 12.1%-20.8% for aerobic fitness and 5.8%-14.0% for body mass index. There was a large variation in the physical activity intensity measure and the association with different measures of cardiometabolic health depending on the combination of settings of accelerometer data processing components. The results provide a fundament for a standard to process hip accelerometer data to assess the physical activity in middle-aged populations.

EGS P16 Laparoscopic cholecystectomy for acute cholecystitis versus diagnostic laparoscopy for suspected appendicitis: comparative time of admission to theatre and impact on reaching national guidance

Abstract Background Early laparoscopic cholecystectomy for acute cholecystitis reduces intra-operative complications. National AUGIS guidelines therefore propose laparoscopic cholecystectomy should be performed within 72 hours of diagnosis. Locally, laparoscopic cholecystectomies for acute cholecystitis are preferentially performed within Emergency General Surgery (EGS) theatres whilst diagnostic laparoscopies for suspected appendicitis within CEPOD. Access to EGS is anecdotally challenging when compared with CEPOD. Patients with acute cholecystitis may subsequently experience longer times from admission to theatre. This project aimed to compare patient timelines from admission/booking to theatre and evaluate the impact on reaching national AUGIS guidance, intra-operative findings and intra-operative drain insertions. Methods Retrospective analysis of patient records at a single tertiary centre was performed. All patients that underwent a laparoscopic cholecystectomy for imaging-confirmed acute cholecystitis (n=66) alongside patients who underwent diagnostic laparoscopy +/- appendicectomy for suspected acute appendicitis (February-June 2022) (n = 62) were included. Time from admission/booking to theatre was determined and independent t-tests performed for statistical comparison. Associations between prolonged waiting times (&amp;gt;72 hours) and severity of intra-operative findings (Parkland scores) (ordinal regression analysis) / intra-operative drain insertion (Chi squared analysis) were analysed. Results Patients undergoing laparoscopic cholecystectomies waited significantly longer from both admission to theatre and booking to theatre compared to patients undergoing diagnostic laparoscopy for suspected appendicitis (71.4 hours vs. 33.33 hours, mean difference 38.07 hours, p=&amp;lt;0.001; 26.93 hours vs. 15.57 hours, mean difference 11.36 hours, p=0.002;). 63.6% of laparoscopic cholecystectomies were performed within 72 hours of admission. Waiting over 72 hours for laparoscopic cholecystectomy was not associated with increased severity of intra-operative findings (higher Parkland scores) (estimate 0.40, p=0.519) or drain insertion (Chi-squared 0.886a, p=0.347). Mean age 57.2 years (range 19-93) and 36.3 (range 8-86) for cholecystectomy versus diagnostic laparoscopy, respectively. Conclusions Patients awaiting laparoscopic cholecystectomy experience significantly longer waiting times from admission and booking to theatre when compared to those awaiting diagnostic laparoscopy for suspected appendicitis. Local concordance with national AUGIS guidance is variable and a proportion of patients with acute cholecystitis wait beyond 72 hours for laparoscopic cholecystectomy. Waiting &amp;gt;72 hours within this tertiary centre is not, however, reflected by intra-operative findings or intra-operative drain insertion. Completion of laparoscopic cholecystectomies within CEPOD should be considered for cases of acute cholecystitis to minimise wait times.

Net Zero Energy cost Building system design based on Artificial Intelligence

This paper presents a solution to the energy planning problem in buildings by implementing the net Zero Energy cost Building (nZEcB), a new concept that refers to buildings with zero or almost zero annual energy costs, using Artificial Intelligence (AI) techniques such as bidirectional long short-term memory, ordinary least squares linear regression, K-means, Pearson’s correlation, decision tree, and binary gravitational search algorithm. AI techniques are used to design the optimal structure of a distributed generation system. The system includes wind and photovoltaic renewable energy sources, a battery bank, and an automated capacitor bank for power factor compensation. A case study was conducted in a real public building with an annual consumption of 1.748 GWh, which resulted in the specification of a distributed generation system with a generation of 2.805 GWh per year. This system meets approximately 160.5% of the building’s electrical demand and 99.999% of annual energy costs, i.e., attending the nZEcB concept. The excess production of approximately 60% of the energy is necessary because the exported energy (feed-in tariff) has a lower value than that imported from the network, having to deduct costs with demand, in addition to having to compensate for losses in the battery banks. The project has a payback period of 6.79 years. This novel study demonstrates the feasibility and effectiveness of using AI techniques to achieve nZEcBs more efficiently, economically and sustainably.

Development and validation of a fully automated 2-dimensional imaging system generating body condition scores for dairy cows using machine learning

Monitoring body condition score (BCS) is a useful management tool to estimate the energy reserves of an individual cow or a group of cows. The aim of this study was to develop and evaluate the performance of a fully automated 2-dimensional imaging system using a machine learning algorithm to generate real-time BCS for dairy cows. Two separate datasets were used for training and testing. The training dataset included 34,150 manual BCS (MAN_BCS) assigned by 5 experienced veterinarians during 35 visits at 7 dairy farms. Ordinal regression methods and deep learning architecture were used when developing the algorithm. Subsequently, the testing dataset was used to evaluate the developed BCS prediction algorithm on 4 of the participating farms. An experienced human assessor (HA1) visited these farms and performed 8 whole-milking-herd BCS sessions. Each farm was visited twice, allowing for 30 d (±2 d) to pass between visits. The MAN_BCS assigned by HA1 were considered the ground truth data. At the end of the validation study, MAN_BCS were merged with the stored automated BCS (AI_BCS), resulting in a testing dataset of 9,657 single BCS. A total of 3,817 cows in the testing dataset were scored twice 30 d (±2 d) apart, and the change in their BCS (ΔBCS) was calculated. A subset of cows at one farm were scored twice on consecutive days to evaluate the within-observer agreement of both the human assessor and the system. The manual BCS of 2 more assessors (HA2 and HA3) were used to assess the interobserver agreement between humans. Finally, we also collected ultrasound measurements of backfat thickness (BFT) from 111 randomly selected cows with available MAN_BCS and AI_BCS. Using the testing dataset, intra- and interobserver agreement for single BCS and ΔBCS were estimated by calculating the simple percentage agreement (PA) at 3 error levels and the weighted kappa (κw) for the exact agreement. A Bland-Altman plot was constructed to visualize the systematic and proportional bias. The association between MAN_BCS and AI_BCS and the BFT was assessed with Passing-Bablok regressions. The system had an almost perfect repeatability with a κw of 0.99. The agreement between MAN_BCS and AI_BCS was substantial, with an overall κw of 0.69. The overall PA at the exact, ± 0.25-unit, and ± 0.50-unit BCS error range between MAN_BCS and AI_BCS was 44.4%, 84.6%, and 94.8%, respectively, and greater than the PA obtained between HA1 and HA3. The Bland-Altman plot revealed a minimal systematic bias of -0.09 with a proportional bias at the extreme scores. Furthermore, despite the low κw of 0.20, the overall PA at the exact and ± 0.25-unit of BCS error range between MAN_BCS and AI_BCS regarding the ΔBCS was 45.7 and 88.2%, respectively. A strong linear relationship was observed between BFT and AI_BCS (ρ = 0.75), although weaker than that between BFT and MAN_BCS (ρ = 0.91). The system was able to predict single BCS and ΔBCS with satisfactory accuracy, comparable to that obtained between trained human scorers.