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Objective: This study aimed to compare cardiac morphological and functional changes in fetuses of patients with diet‐regulated gestational diabetes mellitus (GDM‐A1), insulin‐regulated GDM (GDM‐A2), and a control group. Method: A prospective cohort study included pregnant women aged 18–40 years with singleton pregnancies. Fetal biometric, cardiac morphological, and functional measurements were recorded using Z‐scores at 34–37 weeks of gestation. Results: The study included 87 patients. Both right and left ventricular wall thicknesses were significantly different between the three groups (p < 0.001 and p < 0.001, respectively). Z‐scores of the mitral valve, left and right EDD were significantly lower in GDM‐A1 and GDM‐A2 groups compared to the control group (p < 0.001, p < 0.001, p = 0.002, respectively). Right and left ventricular areas were decreased only in GDM‐A2 group compared to the control group (p = 0.003 and p = 0.001, respectively). MPI and IVRT values were also significantly higher in the same groups (p = 0.016, p < 0.001, respectively). Conclusion: Gestational diabetes increased IVS and ventricular wall thicknesses in both right and left ventricles, irrespective of whether it was controlled by diet or insulin. Cardiac functional changes were observed in the GDM‐A2 group. [ABSTRACT FROM AUTHOR]

Safety accidents in new energy electric vehicles caused by lithium-ion battery failures occur frequently, and the timely and accurate diagnosis of failures in battery packs is crucial. Voltage, as one of the primary characterization parameters of lithium-ion battery malfunctions, is widely utilized in fault diagnosis. This article proposes a lithium-ion battery fault diagnosis method Fault diagnosis method based on the combination of voltage prediction and Z-score. Firstly, the stable trend component is extracted from the battery voltage data using variational mode decomposition, which avoids the influence of noisy signals and random perturbations to the greatest extent. Subsequently, a TCN-BiLSTM-attention model is designed to estimate the average voltage of the battery under normal conditions. Finally, the residuals between the estimated and individual cell voltages are calculated, and the Z-score is utilized to locate and judge whether the battery is caused by the occurrence of a fault. Through verification with real vehicle data and experimental data, the proposed method effectively identifies abnormal battery cells. Compared to the correlation coefficient method, this approach exhibits superior applicability. [ABSTRACT FROM AUTHOR]

Background: Electrocardiograms (ECGs) in athletes commonly reveal findings related to physiologic adaptations to exercise, that may be difficult to discern from true underlying cardiovascular abnormalities. North American and European societies have published consensus statements for normal, borderline, and abnormal ECG findings for athletes, but these criteria are not based on established correlation with disease states. Additionally, data comparing ECG findings in athletes to non-athlete control subjects are lacking. Our objective was to compare the ECGs of collegiate athletes and non-athlete controls using Z-scores for digital ECG variables to better identify significant differences between the groups and to evaluate the ECG variables in athletes falling outside the normal range. Methods: Values for 102 digital ECG variables on 7206 subjects aged 17–22 years, including 672 athletes, from Hawaii Pacific Health, University of Hawaii, and Rady Children's Hospital San Diego were obtained through retrospective review. Age and sex-specific Z-scores for ECG variables were derived from normal subjects and used to assess the range of values for specific ECG variables in young athletes. Athletes with abnormal ECGs were referred to cardiology consultation and/or echocardiogram. Results: Athletes had slower heart rate, longer PR interval, more rightward QRS axis, longer QRS duration but shorter QTc duration, larger amplitude and area of T waves, prevalent R' waves in V1, and higher values of variables traditionally associated with left ventricular hypertrophy (LVH): amplitudes of S waves (leads V1-V2), Q waves (V6, III) and R waves (II, V5, V6). Z-scores of these ECG variables in 558 (83%) of the athletes fell within − 2.5 and 2.5 range derived from the normal population dataset, and 60 (8.9%) athletes had a Z-score outside the − 3 to 3 range. While 191 (28.4%) athletes met traditional voltage criteria for diagnosis of LVH on ECG, only 53 athletes (7.9%) had Z-scores outside the range of -2.5 to 2.5 for both S amplitude in leads V1-V2 and R amplitude in leads V5-6. Only one athlete was diagnosed with hypertrophic cardiomyopathy with a Z-score of R wave in V6 of 2.34 and T wave in V6 of -5.94. Conclusion: The use of Z-scores derived from a normal population may provide more precise screening to define cardiac abnormalities in young athletes and reduce unnecessary secondary testing, restrictions and concern. Key Points: • Athletes had slower heart rate, longer PR interval, greater QRS axis, longer QRS duration, shorter QTc interval, higher peak amplitude of S waves in leads V1 and V2, Q waves in leads III and V6, R waves in leads II, V5, and V6 compared to control subjects. • However, most of the athletes had ECG variable Z-scores within range of -2.5 and 2.5 (83%) and − 3 and 3 (91.1%), all of which had no identified cardiac pathologies. • ECG assessment in athletes utilizing Z-scores derived from normal subjects may guide clinical decision making regarding secondary screening. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate the value of MGI and multi-parameter in the assessment of different pulmonary circulation blood volumes in congenital heart disease.This study included 350 fetuses categorized into two groups: Normal group consisted of 258 fetuses with no discernible abnormalities through echocardiography as control Group A; Abnormal group with abnormal echocardiogram, including Group B of 71 fetuses with decreased pulmonary blood flow or pulmonary atresia and Group C of 21 fetuses with reduced or detached aortic blood flow.The MGI and Z-scores were measured and compared among these groups. Significant variations were noted in the aortic outflow Z-scores (AO-Zs) (p<0.01), pulmonary artery (PA) (p<0.01), PA Z-scores (PA-Zs) (p<0.01), PA/AO (p<0.01), right PA (p<0.01), and MGI (p<0.01) among the three groups (all p<0.05). Among fetuses with decreased pulmonary blood flow or pulmonary atresia, PA, PA-Zs, and MGI in fetuses with reverse DA flow perfusion were lower than those in the DA forward perfusion group.Fetal echocardiography, incorporating the MGI and multi-parameter, not only allows for the evaluation of pulmonary blood flow and pulmonary vascular development of the fetus but also enables the observation of changes in pulmonary blood flow and MGI development across different gestational weeks. [ABSTRACT FROM AUTHOR]

In statistics, there exists several means such as the arithmetic, geometric, harmonic, or power means. Using axiomatic deduction, they have been unified into the generalized f-mean. Similarly, there are several standard deviations and they have been unified into the generalized f-standard deviation, even though without derivation. However, standard score, as known in its arithmetic and geometric versions, has never been f-generalized. The goal of this article is to expose a full derivation of generalized f-statistics, adopting a parameter estimation point of view. Generalized f-mean and generalized f-variance are derived thanks to a maximum likelihood estimation. The non trivial relation between generalized f-standard deviation and generalized f-variance is also studied. Furthermore, generalized f-standard score is defined and extended to multivariate case. Finally, these generalized f-statistics are applied on simulated data for pre-processing and outlier detection. [ABSTRACT FROM AUTHOR]

Tailings dam deformation is influenced by multiple factors. In response to the limitations of traditional prediction methods due to data complexity and non-linear relationships, which result in inadequate prediction accuracy, a method combnng Mult-Head Atenton mechansm and Bdrectonal Long Short-Term Memory (BLSTM) s proposed for pred ct ng ta l ngs dam d splacement. In the pred ct on process, the or g nal data sfrst processedusng Z-score and SavItzky-Golay fIlterIng techniques to eliminate disturbances caused by outliers and noise. Subsequently, the Grey Relational Analysis method is utilized to determine the factors influencing dam displacement. Finally, the MHA-BiLSTM model is employed to predict the dam displacement. Taking the measured data of a tailings pond in Liaoning Province as an example, he performance of the proposed model is compared with thetradtonal BLSTM model. The results show that this method can predict the dsplacement of dam more accurately. [ABSTRACT FROM AUTHOR]

Objective: To evaluate non‐invasive prenatal testing (NIPT) and expanded non‐invasive prenatal testing (NIPT‐plus) for detecting aneuploidies at different sequencing depths and assess Z‐score accuracy in predicting trisomies 21, 18, 13, 45X, and 47XXX. Methods: Pregnancies with positive NIPT or NIPT‐plus results detected at the prenatal diagnosis center of Nanfang Hospital were included in this retrospective study, between January 2017 and December 2022. Invasive prenatal diagnostic results were collected. Logistic regression analyses were used to study the relationship between Z‐score and positive predictive value (PPV). Optimal cut‐off values were obtained based on receiver operating characteristic analysis, and PPVs were calculated in different groups. Results: We evaluated 1348 pregnant women with positive results, including 930 reported by NIPT and 418 reported by NIPT‐plus. NIPT reported significantly more rare chromosomal aneuploidies (RCAs), and NIPT‐plus had a significantly higher PPV for trisomy 21 (T21). Logistic regression analyses showed a significant association (P < 0.001) between Z‐score and PPVs for T21 and trisomy 18 (T18). A linear relationship was observed between fetal fraction (FF) and Z‐values in the true positive cases of T21 and T18.The high Z‐score group had significantly higher PPVs than the low Z‐score group for T21, T18, trisomy 13, and 47XXX, but not for 45X. Conclusion: The Z‐score is helpful in assessing NIPT or NIPT‐plus results. Therefore, we suggest including the Z‐score and FF in the results. By combining the Z‐score, FF, and maternal age, clinicians can interpret NIPT results more accurately and improve personal counsel to reduce patients' anxiety. Synopsis: NIPT‐plus showed a significantly higher PPV for T21 than NIPT, and it is suggested that Z‐scores and fetal fraction are added to the result report. [ABSTRACT FROM AUTHOR]

Purpose – This study aims to examine whether there are differences between financial statements prepared in accordance with International Financial Reporting Standards (IFRS) and financial statements prepared in accordance with local accounting standards in terms of its ability to present the financial conditions of companies listed on the Saudi Stock Exchange as one of the emerging markets. Design/methodology/approach – Data on study variables were obtained from the published financial statements of 67 of listed companies in the Saudi Stock Exchange during the period 2014–2019. The study addressed the research hypotheses by using Altman Z-score model. Both the T-test and Wilcoxon rank test were used to investigate the significance of differences between the values of Z-score and the individual variables included in the model in the pre- and post-IFRS mandatory adoption periods. Findings – The results revealed a decrease in the values of Z-score as well as the values of the individual variables included in the model in the period following the adoption of IFRS than it was before the adoption of IFRS, which indicates the ability of IFRS to show the financial conditions of companies more transparently than local accounting standards. However, the results of the T-test and Wilcoxon test showed that these decreases were not statistically significant. Research limitations/implications – This study has some limitations, including the small sample size as a result of the small size of the Saudi Stock Exchange, As well as the reliance of this study only on the Altman model with its five variables in assessing financial conditions without examining the impact of other factors that may affect the financial conditions of companies. Practical implications – Financial conditions of the companies have important implications for multiple parties such as management, government, investors and others as an early warning sign that enables them to take the necessary measures early before the actual bankruptcy occurs and what results in costs. Originality/value – Although assessing financial conditions of the companies is one of the basic uses of accounting information, this topic has not received sufficient attention as a means to test the benefits of adopting IFRS, especially in emerging markets such as Saudi Stock Exchange. This is the first study to examine the impact of adopting IFRS on the transparency of financial reporting in assessing financial conditions in Saudi Arabia.

Abstract Background Electrocardiograms (ECGs) in athletes commonly reveal findings related to physiologic adaptations to exercise, that may be difficult to discern from true underlying cardiovascular abnormalities. North American and European societies have published consensus statements for normal, borderline, and abnormal ECG findings for athletes, but these criteria are not based on established correlation with disease states. Additionally, data comparing ECG findings in athletes to non-athlete control subjects are lacking. Our objective was to compare the ECGs of collegiate athletes and non-athlete controls using Z-scores for digital ECG variables to better identify significant differences between the groups and to evaluate the ECG variables in athletes falling outside the normal range. Methods Values for 102 digital ECG variables on 7206 subjects aged 17–22 years, including 672 athletes, from Hawaii Pacific Health, University of Hawaii, and Rady Children’s Hospital San Diego were obtained through retrospective review. Age and sex-specific Z-scores for ECG variables were derived from normal subjects and used to assess the range of values for specific ECG variables in young athletes. Athletes with abnormal ECGs were referred to cardiology consultation and/or echocardiogram. Results Athletes had slower heart rate, longer PR interval, more rightward QRS axis, longer QRS duration but shorter QTc duration, larger amplitude and area of T waves, prevalent R’ waves in V1, and higher values of variables traditionally associated with left ventricular hypertrophy (LVH): amplitudes of S waves (leads V1-V2), Q waves (V6, III) and R waves (II, V5, V6). Z-scores of these ECG variables in 558 (83%) of the athletes fell within − 2.5 and 2.5 range derived from the normal population dataset, and 60 (8.9%) athletes had a Z-score outside the − 3 to 3 range. While 191 (28.4%) athletes met traditional voltage criteria for diagnosis of LVH on ECG, only 53 athletes (7.9%) had Z-scores outside the range of -2.5 to 2.5 for both S amplitude in leads V1-V2 and R amplitude in leads V5-6. Only one athlete was diagnosed with hypertrophic cardiomyopathy with a Z-score of R wave in V6 of 2.34 and T wave in V6 of -5.94. Conclusion The use of Z-scores derived from a normal population may provide more precise screening to define cardiac abnormalities in young athletes and reduce unnecessary secondary testing, restrictions and concern.

Abstract Pulsatile hemodynamics have been shown to be independent predictors of cardiovascular events. The aim of the current study was to describe four pulsatile hemodynamic markers in a large, well-established, population-based cohort and to provide reference equations for sex- and age-based standardization of these measurements. 6828 adult participants from the Austrian LEAD (Lung, hEart, sociAl, boDy) cohort study, who were free from overt cardiovascular disease, non-diabetic based on blood test results, and had no history of pharmacological treatment for hypertension, dyslipidemia, and diabetes, comprised the “reference population”. Carotid-femoral pulse wave velocity (cfPWV), augmentation index (AIx), amplitude of forward wave (Pf), and backward wave (Pb) were described in different age categories for both sexes. Sex-specific reference equations for cfPWV, AIx, Pf, and Pb with age as the predictive variable were created using the Lambda-Mu-Sigma (LMS) method. All four parameters increased with age. CfPWV and Pf were higher in males than females, especially in young and middle-age groups (P

The number of interacting devices is increasing every day, and with this constant innovation, serious security challenges arise. The concept of the Internet of Things is being actively applied in both domestic and industrial settings. Researchers are increasingly highlighting the challenges and importance of network security. Data preprocessing plays an important role in security by transforming the input data corresponding to algorithmic criteria and thereby contributing to the prediction accuracy. The data preprocessing process is determined by many factors, including the processing algorithm, the data, and the application. Moreover, in Internet of Things interactions, data normalisation and aggregation can significantly improve security and reduce the amount of data used further decision making. This paper discusses the challenges of data normalisation and aggregation in the IoT to handle large amounts of data generated by multiple connected IoT devices. A secure data normalisation and aggregation method promotes successful minimised data transfer over the network and provides scalability to meet the increasing demands of IoT deployment. The proposed work presents approaches used in data aggregation protocols that address interference, fault tolerance, security and mobility issues. A local aggregation approach using the run-length encoding algorithm is presented. The proposed technique consists of data acquisition, data preprocessing, data normalisation and data aggregation steps. Data normalisation was performed via the Z-score algorithm, and the LEACH algorithm was used for data aggregation. In the experimental study, the percentage of faulty nodes reached 35%. The performance of the proposed solution was 0.82. The results demonstrate a reduction in resource consumption while maintaining the value and integrity of the data.

Background and objective: β-Thalassemia is a common inherited disease in this region. A considerable number of transfusion-dependent β-thalassemia (TDT) patients suffer bone problems. The objective of this study was to evaluate bone mineral density in TDT patients using dual-energy X-ray absorptiometry (DEXA) scan. Methods: In this study, 53 TDT patients aged ≥10 years, together with 25 normal healthy individuals were enrolled. Their bone status was assessed using DEXA scan at lumber spine (L1-L4) and femoral neck. The effect of physical, biochemical, and hormonal characteristics on the bone mineral density (BMD) parameters were evaluated. BMD-Z score was used to assess the magnitude of bone disease. Results: The mean age of the patients was 21.3±7.8 years with male to female ratio 1.4:1. The values BMD parameters were significantly lower in the patients compared to the normal group. The mean values of BMD Z-core among the patients at lumber spine and femoral neck were -2.95±1.07 and -1.51±1.02 respectively. Among the patients, osteoporosis was detected in 69.8% and 13.2% in lumber spine and femoral neck respectively. None of the normal individuals had osteoporosis. Patients’ age. body mass index (BMI) and parathyroid hormone level had a significant association with BMD Z-score (P

Abstract Background The application of z-scores in normalizing the cardiac size function and structural dimension will be of immense benefit to the clinician, especially in evaluating children with cardiac anomalies. However, heterogeneity in the obtained z- score results is high, thus a subgroup analysis by region (or continent) to assist healthcare practitioners is necessary. Objectives The review aimed to ascertain the overall mean z-scores for cardiac structures and function. Methods A thorough search of several databases, EMBASE, PubMed/MEDLINE, and Google Scholar was made. Articles published between January 1999 and December 2023 were recruited, of which the last search was done in December 2023. Keywords used in the search were “z-scores”, Children; echocardiography; cardiac structures; cardiac function; and body surface area (BSA)”. We restricted our search to children. Besides, additional relevant articles were manually searched. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) was used to highlight selected studies using a pre-defined search protocol. The I 2 statistics were used to ascertain statistical heterogeneity. Results Two hundred and forty citations were identified in our search strategy, of which a total of 34 studies were identified. Twenty-four were excluded from the thirty-four studies. A total of 11 studies met our inclusion criteria shown in the PRISMA. Apart from different z scores reading obtained from various countries and regions, some authors focused on few cardiac parameters while others were exhaustive. The mean z-scores of the cardiac structures from various countries/regions range as follows; The range of Z scores obtained by different studies and regions above are as follows; MV;-1.62-0.7 AV: -1.8 -0.5 TV: -2.71 -0.7; PV ; -1.52- (-0.99) MPA; -1-81 -0.8 LPA;-1.07-0.4; RPA;-0.92- 0.1 IVSD; -0.1.77–1.89 LVPWD; -0.12-1.5 LVPWS; -0.1-0.15 LVPWS; 0.03–0.18 LVIDD; -1.13- (-0.98) LVIDS; -0.84-10.3 respectively. The mean z-score from the pooled studies showed mitral valve diameter as -0.24 ± 0.9 and pulmonary valve annuls as -1.10 ± 0.3. The left ventricular end diastolic diameter is -0.93 ± 0.3 while the left ventricular end systolic diameter is -0.05 ± 0.5. The total pooled sample size of the eleven included studies was 9074 and the mean at 95% interval was 824.9 ± 537.344. The pooled mean is presented under the model of the Mean raw (MRAW) column. The heterogeneity discovered among the selected studies was statistically significant. Conclusion Due to heterogeneity involved in the reportage of the z-scores of cardiac structures and function, it may be necessary for every region to use their z-scores domiciled in their locale. However, having a pooled mean z-score of cardiac structures and function may be useful in the near future.

This study aimed to establish the nexus between CEO power and bank risk. Previous studies on how CEO power affects risk-taking have produced mixed results. Some studies show that CEO power reduces risk, while others show the reverse. This lack of conclusive findings motivated this study. This study used secondary data from a sample of 14 commercial banks in Uganda covering a period from 2010 to 2020. System GMM was used to establish the relationship between variables, while ARDL was used to infer causality. Findings show that commercial banks with powerful CEOs have lower risk. Such powerful CEOs have prestige power, are internally hired, have ownership, and have served for more than 4 years up to 7 years, and hence possess expert power. We further found a long-run positive relationship between previous bank risk and current bank risk, as well as a causal relationship between CEO power and bank risk. In case there is a need to reduce bank risk in Uganda, making adjustments in CEO power will help. It may also be necessary for persistent adjustment and implementation of decisions and policy actions, if bank risk is to be minimized.

Background: Lifelong management of phenylketonuria (PKU) centers on medical nutrition therapy, including dietary phenylalanine (Phe) restriction in addition to Phe-free or low-Phe medical foods/protein substitutes. Studies have reported low bone mineral density (BMD) in mixed-age PKU populations, possibly related to long-term Phe restriction. Therefore, a meta-analysis investigating BMD specifically in adults with PKU was conducted. Methods: Studies reporting BMD-related outcomes were identified from a systematic literature review evaluating somatic comorbidities experienced by adults with PKU on a Phe-restricted diet (searched February 1, 2022, updated November 1, 2023). Risk of study bias was assessed (Scottish Intercollegiate Guidelines Network checklists). The primary outcome of the meta-analysis was pooled mean BMD Z-scores of different bones. Secondary outcomes were the prevalence of low BMD Z-scores at pre-specified thresholds. Subgroup analyses of mean BMD Z-scores (decade of study publication, controlled versus uncontrolled blood Phe levels, gender) were conducted. Results: BMD-related data from 4097 individuals across 10 studies rated as at least acceptable quality were included. Mean BMD Z-scores were statistically significantly lower compared with an age-matched control or reference (non-PKU) population, across bones, but still within the expected range for age (> -2.0): lumbar spine (seven studies, n = 304), -0.63 (95% confidence interval (CI): -0.74, -0.52); femoral neck (four studies, n = 170), -0.74 (95% CI: -1.25, -0.22); radius (three studies, n = 114), -0.77 (95% CI: -1.21, -0.32); total body (four studies, n = 157), -0.61 (95% CI: -0.77, -0.45). The small number of observations in the subgroup analyses resulted in a high degree of uncertainty, limiting interpretation. Estimated prevalence of BMD Z-scores ≤ -2.0 was 8% (95% CI: 5%, 13%; four studies, n = 221) and < -1.0 was 42% (95% CI: 35%, 51%; five studies, n = 144). Conclusions: Adults with PKU had lower BMD Z-scores than the reference (non-PKU) population but < 1 in 10 were below the expected range for age. The low number of studies prevents identification of which population characteristics are most impacting BMD. This meta-analysis was supported by BioMarin Pharmaceutical Inc., Novato, CA and is registered with the Research Registry (reviewregistry1476). [ABSTRACT FROM AUTHOR]

When using point-by-point data input with former series models for wind power prediction, the prediction accuracy decreases due to data distribution shifts and the inability to extract local information. To address these issues, this paper proposes an ultra-short-term wind power prediction model based on the Z-score (ZS), Dish-TS (DT), and Patch time series Transformer (PatchTST). Firstly, to reduce the impact of data distribution shift on prediction accuracy, ZS standardization is applied to both training and testing datasets. Additionally, the DT algorithm, which can self-learn the mean and variance, is introduced for window data standardization. Secondly, the PatchTST model is employed to convert point input data into local-level input data. Feature extraction is then performed using the multi-head attention mechanism in the Encoder layer and a feed-forward network composed of one-dimensional convolution to obtain the prediction results. These results are subsequently de-standardized using DT and ZS to restore the original data amplitude. Finally, experimental analysis is conducted, comparing the proposed ZS-DT-PatchTST model with various prediction models. The proposed model achieves the highest prediction accuracy, with a mean absolute error of 5.95 MW, a mean squared error of 10.89 MW, and a coefficient of determination of 97.38%. [ABSTRACT FROM AUTHOR]

The number of interacting devices is increasing every day, and with this constant innovation, serious security challenges arise. The concept of the Internet of Things is being actively applied in both domestic and industrial settings. Researchers are increasingly highlighting the challenges and importance of network security. Data preprocessing plays an important role in security by transforming the input data corresponding to algorithmic criteria and thereby contributing to the prediction accuracy. The data preprocessing process is determined by many factors, including the processing algorithm, the data, and the application. Moreover, in Internet of Things interactions, data normalisation and aggregation can significantly improve security and reduce the amount of data used further decision making. This paper discusses the challenges of data normalisation and aggregation in the IoT to handle large amounts of data generated by multiple connected IoT devices. A secure data normalisation and aggregation method promotes successful minimised data transfer over the network and provides scalability to meet the increasing demands of IoT deployment. The proposed work presents approaches used in data aggregation protocols that address interference, fault tolerance, security and mobility issues. A local aggregation approach using the run-length encoding algorithm is presented. The proposed technique consists of data acquisition, data preprocessing, data normalisation and data aggregation steps. Data normalisation was performed via the Z-score algorithm, and the LEACH algorithm was used for data aggregation. In the experimental study, the percentage of faulty nodes reached 35%. The performance of the proposed solution was 0.82. The results demonstrate a reduction in resource consumption while maintaining the value and integrity of the data. [ABSTRACT FROM AUTHOR]

Urban transportation has changed dramatically in the recent years through the large scale implementation of shared micro-mobility services, especially bike sharing systems (BSS) and electric scooter sharing (ESS). The COVID-19 pandemic brought further changes and uncertainty to this turbulent business environment. In 2020, the major BSS operator in Poland filed for bankruptcy claiming that its problems arise from the COVID-19 pandemic. Market reports and media speculated that BSS business, despite being publicly financed, and considered to be a of part of public transportation system, could be unsustainable in face of the competition from ESS. We used Z‑score analysis to investigate if bike sharing systems operators' problems began before or during the COVID-19 pandemic and large scale development of ESS. Our study focuses on the Nextbike company, which held a dominant stake in the Polish BSS market. It also covers two other major Polish operators and includes a German operator for comparative analysis. To complement the quantitative findings from z‑score analysis, we have also interviewed representatives of major stakeholders, which deepened our understanding of BSS problems. The results of our research indicate that although the market was affected by the COVID-19 pandemic and growing scooter-sharing competition, the problems of the largest BSS operator were specific to this company, and the entire market was not under the risk of failure. [ABSTRACT FROM AUTHOR]

Our study investigates risk-taking behavior among Vietnamese listed companies during 20 years (2000–2020). We acknowledge that regardless stages of companies, firms have tendency to take more risks, and that risk-taking activities in the course of the introduction and maturity phases can have both negative and positive forces on current and future performance. Additionally, the paper explored the moderating forces of the Z-score and HHI Index on this relationship. The paper contributes to the state-of-the-art by supplying empirical evidence about the relation between corporate life phases and willingness to take risk in Vietnamese non-financial firms. It provides a firm life cycle methodology to aid managers in developing appropriate strategies and sheds new light on the moderating effects of Z-score as well as market competition on the link. [ABSTRACT FROM AUTHOR]

We assess the relation of macroprudential policy and competition to bank risk for a sample of 1373 banks from 13 East Asian countries, using the IMF iMaPP dataset of macroprudential policy from 1990 to 2018. To our knowledge, this is the first paper to include both macroprudential policy and individual bank market power, as well as their interaction, as determinants of bank risk. On the one hand, we find direct effects of both macroprudential policy and competition on risk, in line with the existing literature. On the other hand, we detect important interaction effects. Notably in the developing and emerging East Asian countries, the interactions between competition and macroprudential measures often show a lesser response to such measures in terms of risk reduction for banks with more market power. We suggest that this links in turn to ability of such banks to undertake risk-shifting in response to macroprudential policy. We also find for banks in advanced East Asian countries—and in wider samples—some tendency in the long term for banks facing intense competition to take relatively more risks in face of macroprudential measures, in line with the traditional "franchise value" view of bank competition and risk taking. These findings have important implications for regulators. [ABSTRACT FROM AUTHOR]

Background: The application of z-scores in normalizing the cardiac size function and structural dimension will be of immense benefit to the clinician, especially in evaluating children with cardiac anomalies. However, heterogeneity in the obtained z- score results is high, thus a subgroup analysis by region (or continent) to assist healthcare practitioners is necessary. Objectives: The review aimed to ascertain the overall mean z-scores for cardiac structures and function. Methods: A thorough search of several databases, EMBASE, PubMed/MEDLINE, and Google Scholar was made. Articles published between January 1999 and December 2023 were recruited, of which the last search was done in December 2023. Keywords used in the search were "z-scores", Children; echocardiography; cardiac structures; cardiac function; and body surface area (BSA)". We restricted our search to children. Besides, additional relevant articles were manually searched. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) was used to highlight selected studies using a pre-defined search protocol. The I2 statistics were used to ascertain statistical heterogeneity. Results: Two hundred and forty citations were identified in our search strategy, of which a total of 34 studies were identified. Twenty-four were excluded from the thirty-four studies. A total of 11 studies met our inclusion criteria shown in the PRISMA. Apart from different z scores reading obtained from various countries and regions, some authors focused on few cardiac parameters while others were exhaustive. The mean z-scores of the cardiac structures from various countries/regions range as follows; The range of Z scores obtained by different studies and regions above are as follows; MV;-1.62-0.7 AV: -1.8 -0.5 TV: -2.71 -0.7; PV ; -1.52- (-0.99) MPA; -1-81 -0.8 LPA;-1.07-0.4; RPA;-0.92- 0.1 IVSD; -0.1.77–1.89 LVPWD; -0.12-1.5 LVPWS; -0.1-0.15 LVPWS; 0.03–0.18 LVIDD; -1.13- (-0.98) LVIDS; -0.84-10.3 respectively. The mean z-score from the pooled studies showed mitral valve diameter as -0.24 ± 0.9 and pulmonary valve annuls as -1.10 ± 0.3. The left ventricular end diastolic diameter is -0.93 ± 0.3 while the left ventricular end systolic diameter is -0.05 ± 0.5. The total pooled sample size of the eleven included studies was 9074 and the mean at 95% interval was 824.9 ± 537.344. The pooled mean is presented under the model of the Mean raw (MRAW) column. The heterogeneity discovered among the selected studies was statistically significant. Conclusion: Due to heterogeneity involved in the reportage of the z-scores of cardiac structures and function, it may be necessary for every region to use their z-scores domiciled in their locale. However, having a pooled mean z-score of cardiac structures and function may be useful in the near future. [ABSTRACT FROM AUTHOR]

Aim: To assess inpatient growth parameter trajectories and to identify the type of opioid exposure and treatment characteristics influencing growth parameters of infants admitted to the newborn intensive care unit (NICU) for pharmacological treatment of neonatal opioid withdrawal syndrome (NOWS). Methods: Charts of term infants with NOWS admitted to NICU from 2012 to 2019, who received pharmacologic treatment, were reviewed. Intake (volume: mL/kg/day; calorie: kcal/kg/day) and growth parameter trajectories (weight, head circumference, and length) were analyzed based on the type of prenatal opioid exposure (short‐acting opioids (SAOs), long‐acting opioids (LAOs), and polysubstance), pharmacologic treatment, and sex. Growth measurement patterns over time were compared between groups using longitudinal mixed‐effects models. Results: One hundred nineteen infants were included in the study with median birth weight Z‐score of −0.19 at birth and decreased to a median of −0.72 at discharge. Exposure to SAO was associated with an increase in Z‐scores nearing discharge across all growth parameters (Z‐score for weight p = 0.03). Polysubstance exposure was associated with a decrease in Z‐scores for length and head circumference throughout hospitalization. Infants with adjunct clonidine treatment had an increase in Z‐score for weight trends. Male infants had a decrease in Z‐scores for weight (male −0.96, female −0.59, interaction p = 0.06) and length (male −1.17, female −0.57, interaction p = 0.003) at Day 28. Despite the difference in growth trajectories, intake in terms of amount (mL/kg/day) and calorie intake (kcal/kg/day) was similar based on prenatal exposure, treatment, and sex. Conclusion: Infants with NOWS requiring pharmacologic treatment have a decrease in Z‐scores for weight, length, and head circumference at birth and at hospital discharge. Infants with prenatal polysubstance exposure were at particular risk for poorer inpatient growth relative to infants exposed to SAO and LAO, indicated by lower Z‐scores for length and occipital frontal circumference (OFC). [ABSTRACT FROM AUTHOR]

Background/Objectives: To evaluate the quality of an ultrasound practice, both large-scale and focused audits are recommended by professional organizations, but such audits can be time-consuming, inefficient, and expensive. Our objective was to develop a time-efficient, quantitative, objective, large-scale method to evaluate fetal biometry measurements for an entire practice, combined with a process for focused image review for personnel whose measurements are outliers. Methods: Ultrasound exam data for a full year are exported from commercial ultrasound reporting software to a statistical package. Fetal biometry measurements are converted to z-scores to standardize across gestational ages. For a large-scale audit, sonographer mean z-scores are compared using analysis of variance (ANOVA) with Scheffe multiple comparisons test. A focused image review is performed on a random sample of exams for sonographers whose mean z-scores differ significantly from the practice mean. A similar large-scale audit is performed, comparing physician mean z-scores. Results: Using fetal abdominal circumference measurements as an example, significant differences between sonographer mean z-scores are readily identified by the ANOVA and Scheffe test. A method is described for the blinded image audit of sonographers with outlier mean z-scores. Examples are also given for the identification and interpretation of several types of systematic errors that are unlikely to be detectable by image review, including z-scores with large or small standard deviations and physicians with outlier mean z-scores. Conclusions: The large-scale quantitative analysis provides an overview of the biometry measurements of all the sonographers and physicians in a practice, so that image audits can be focused on those whose measurements are outliers. The analysis takes little time to perform after initial development and avoids the time, complexity, and expense of auditing providers whose measurements fall within the expected range. We encourage commercial software developers to include tools in their ultrasound reporting software to facilitate such quantitative reviews. [ABSTRACT FROM AUTHOR]

Copyright of Journal of International Business Studies is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Growth has improved between 2000 and 2022 in children with cystic fibrosis. • The occurrence of stunting in children with CF decreased over the period. • During the same time, the occurrence of overweight children increased. • Individualized nutrition care throughout early childhood remains imperative. Improved growth in children with CF may have resulted from advances in treatment for cystic fibrosis (CF) over the past two decades, including the implementation of newborn screening in Denmark in 2016. This observational cohort study focuses on changes in early growth in Danish children with CF born between 2000 and January 2022. Age, length/height, and weight data of children 0–5 years old were obtained from the Danish CF Cohort. Data were stratified to four birth cohorts born between 2000 and 2022. Weight-for-age (WAZ), length-for-age (LAZ), height-for-age (HAZ) and body-mass-index (BMZ) z-scores were computed using WHO growth curves. Cubic spline mixed effects models were used to evaluate growth over 5 years between birth cohorts. We included 255 children in the analyses. Cubic spline mixed effects models show that catch-up growth improved in birth cohorts over time, with the 2016–2022 birth cohort achieving growth reference curve values in WAZ, LAZ/HAZ and BMZ the earliest. The proportion of underweight and stunting observations among children born 2000–2004 decreased by the 2016–2022 birth cohort, while the proportion of overweight, low BMZ and high BMZ observations increased. Advances in care for young children with CF have led to improvements in growth – with the 2016–2022 birth cohort approaching potential for overweight. Nonetheless, low BMZ remains. Immediate, individualized nutrition care throughout early childhood remain crucial in mitigating malnutrition. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a practical method for bivariate z-score analysis which can be applied to the survey of an external quality assessment programme. To develop the bivariate z-score analysis, the results of four surveys of the international D-Dimer external quality assessment programme of 2022 of the ECAT Foundation were used. The proposed methodology starts by identifying the bivariate outliers, using a Supervised Sequential Hotelling T2 control chart. The outlying data are removed, and all the remaining data are used to provide robust estimates of the parameters of the assumed underlying bivariate normal distribution. Based on these estimates two nested homocentric ellipses are drawn, corresponding to confidence levels of 95 and 99.7 %. The bivariate z-score plot described provides the laboratory with an indication of both systematic and random deviations from zero z-score values. The bivariate z-score analysis was examined within survey 2022-D4 across the three most frequently used methods. The number of z-score pairs included varied between 830 and 857 and the number of bivariate outliers varied between 20 and 28. The correlation between the z-score pairs varied between 0.431 and 0.647. The correlation between the z-score pairs for the three most frequently used varied between 0.208 and 0.636. The use of the bivariate z-score analysis is of major importance when multiple samples are distributed around in the same survey and dependency of the results is likely. Important lessons can be drawn from the shape of the ellipse with respect to random and systematic deviations, while individual laboratories have been informed about their position in the state-of-the-art distribution and whether they have to deal with systematic and/or random deviations. [ABSTRACT FROM AUTHOR]

Federated learning as an emerging distributed computing paradigm with privacy protection, safeguards user privacy and data security to a certain extent. However, in federated learning systems, the frequent exchange of model parameters between clients and servers results in significant communication overhead. In bandwidth-limited wireless communication scenarios, this has become the primary bottleneck restricting the development of federated learning. To solve this problem, this paper proposed a dynamic sparse compression algorithm based on Z-Score. By utilizing Z-Score, it performed outlier detection on local model updates, considering significant update values as outliers and subsequently selecting them. Without complex sorting algorithms or prior knowledge of the original model updates, it achieved model update sparsification. At the same time, with the increase of communication rounds, the sparse rate was dynamically adjusted according to the loss value of the global model to minimize the total traffic while ensuring the accuracy of the model. Experiments show that in the I. I. D. data scenario, the proposed algorithm can reduce communication traffic by 95% compared with the federated average algorithm, and the accuracy loss is only 1.6%. Additionally, compared with the FTTQ algorithm, the proposed algorithm can also reduce communication traffic by 40%~50%, with only 1.29% decrease in accuracy. It proves that the method can significantly reduce the communication cost while ensuring the performance of the model. [ABSTRACT FROM AUTHOR]

Copyright of Celal Bayar Üniversitesi Saglik Bilimleri Enstitüsü Dergisi is the property of Celal Bayar University Health Sciences Institute Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Many neonatal intensive care units use feeding protocols where infants born at 30-34 weeks' gestation are maintained exclusively on parenteral fluids for variable periods without enteral feedings, until there is confirmed hemodynamic stability without any doubt. In addition to the pain and discomfort, intravenous infusions are associated with an increased risk of hospital-acquired infections, which makes it an undesirable practice if not essential. Objective: In this quality improvement (QI) effort, we tested the safety and efficacy of enteral feedings starting within the first 2 hours after birth in infants born at 30-34 weeks' gestation. Materials and methods: Instead of intravenous fluids, we initiated fluid management in infants born at 30-34 weeks' gestation using oral/nasogastric milk feedings at 70-80 mL/kg/day divided every 3 hours, with 5 mL increments every 12-24 hours until 200 mL/kg/day was achieved. We compared the utilization of parenteral fluids, the incidence of infection, and growth before and after initiation of this new feeding policy. Results: In our experience, these infants tolerated and utilized enteral feedings well with stable growth and biochemical parameters. They also tolerated daily volume increments in the enteral feedings. We did not find any hypoglycemic events as the first enteral feeding was administered within 2 hours after birth. The enterally fed group showed a similar safety profile with similar weight at discharge and weight Z-scores. We report that infants born as early as 30 weeks gestation can safely tolerate ab initio full enteral feedings. Conclusion: Enteral feedings beginning within 2 hours after birth are a safe and efficacious strategy for fluid management in premature infants born at 30-34 weeks gestation. Routine use of parenteral fluids is not necessary in the initial management of these infants. [ABSTRACT FROM AUTHOR]

Copyright of Optimum. Economic Studies is the property of University of Bialystok and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of effective targeting mechanisms for identifying households or individuals eligible for poverty reduction, development, and social protection programs is a pressing issue for practitioners and civil society. The paper presents a validation strategy that practitioners could use to identify potential beneficiaries of poverty reduction, inclusion, and institutional programs, especially in the resource-constrained settings prevalent in developing countries. The approach integrates a multistep process to ensure internal and external validity when using the Poverty Probability Index to identify students living in poor households. The results strongly support the internal and external validity of the proposed strategy’s targeting mechanism. The combination of the Poverty Probability Index and z-scores allows for identifying vulnerable students, offering an opportunity for a low-cost and time-efficient poverty analysis that practitioners could use in diverse settings. This will enable the implementation of unbiased scholarship programs for students of higher education institutions in developing economies.

There is a growing consensus on the translation of monetary policy actions into changes in credit demand on account of changes in interest rates. The study investigates monetary policy, macroprudential policy, bank-specific and macroeconomic determinants of bank risk-taking from 2010–2022 in Indonesia. The study aims to address a gap in the literature because most previous studies have focused on advanced markets. First, three POLS and fixed effect models are estimated. However, the Durbin Wu-Hausman test indicated endogeneity issues with the estimated models. The second stage uses a system GMM estimation to investigate the impact of central bank rates and macroprudential policy on bank risk-taking. Dynamic-GMM estimations find that, partially the central bank rate and macroprudential policy have a positive impact on bank Z-Score. Furthermore, when central bank rate and macroprudential policy are included in a model, we still find a positive impact of both policies on bank Z-Score.

Worldwide, breast cancer (BC) represents one of the serious health concerns for adult females. The early detection and accurate prediction of risks are vital for the provision of optimum care and enhancement of patient outcomes. In the past few years, promising large data merging and ensemble learning algorithms appeared for the purpose of classification and prediction of BC risk. In the area of medical applications, methods of machine learning (ML) are crucial. Early diagnosis is necessary for a more efficient carcinoma treatment. This study’s aim is to classify the carcinoma with the use of the 10 predictors that are found in Breast Cancer Coimbra dataset (BCCD). Presently, early diagnoses are necessary. The rates of cancer survival could be raised in the case where it is discovered early. Methods of machine learning offer effective way for data classifying and making early disease diagnoses. This study utilizes BCCD for the classification of BC cases utilizing XGBoost algorithm. Based on performance criteria, early detection of BC is the primary goal. The XGBoost classifier in this research achieved 98% precision, 98.32% accuracy, 99% f1-score, and 97% recall.

The present research evaluated the prospects of utilizing rainfall and temperature combined with Landsat-8 derived HANTS (Harmonic Analysis of Time Series) reconstructed NDVI for estimating the metrics of the mangrove phenology. The selected period of the study was from 2013 to 2020 for the Pichavaram mangroves of Tamil Nadu. The NDVI and ERA5 (ECMWF Re-Analysis) datasets of rainfall and temperature were the input datasets for developing the new algorithm. The ‘z-score sum’ provided a measure of the cumulative impact of rainfall and temperature, displaying its most negative value coinciding with the peak positive value of the NDVI time series datasets. The algorithm developed for phenological metrics estimation identified the common inflection points of the z-score sum and NDVI curves. The temporal analysis of metrics revealed the average Length of Season (LoS) as 230 days. The metrics also identified the drought year 2016 with the shortest LoS and the least Gross Primary Productivity (GPP) values. The analysis showed the influences of the preceding year’s monsoon rainfall on the GPP values of the later part of the phenological cycle. The temperatures during the days of PoS were found to be the optimum temperature for the growth of mangroves. HIGHLIGHTS The combined influence of rainfall and temperature on mangrove phenology is more significant than individual influences.; The z-score sum of rainfall and temperature exhibited an inverse relationship with NDVI values.; GPP values of mangroves and estimated phenological metrics showed good correspondence.; The estimated phenological metrics captured the influences of drought and abundant rainfall on mangrove phenology.;

Research Question: What is the utilization rate of embryos that exert inadequate zygote cleavage into three daughter cells? Design: This study used a retrospective dataset from a single IVF Unit. A total of 3,060 embryos from 1,811 fresh IVF cycles were analyzed. The cleavage pattern, morphokinetics, and outcome were recorded. Only 2pn embryos, fertilized by ejaculated sperm, and cultured in a time-lapse system for at least 5 days were included. We generated three study groups according to the embryo's cleavage pattern: (I) Control, normal cleavage (n = 551); (II) fast cleavage, zygote to three cells within 5 h (n = 1,587); and (III) instant direct tripolar cleavage (IDC) from zygote to three cells (n = 922). Results: The rate of usable fast cleavage blastocysts was 108/1,587 (6.81%) and usable control blastocysts was 180/551 (32.67%). The time of PN fading and from fading to first cleavage differed significantly between the three groups. Although the pregnancy rate of control and fast cleavage blastocysts were comparable (40.35% and 42.55%, respectively), the amount of instant direct cleavage embryos that reached blastocyst stage was neglectable (only four embryos out of 922 analyzed IDC embryos) and unsuitable for statistical comparison of pregnancy rates. Conclusion: Our results indicate the need to culture instant direct cleavage embryos for 5 days, up to the blastocyst stage, and avoid transfer of embryos that are fated to arrest even when their morphological grade on day 3 is acceptable, whereas fast cleavage embryos could be transferred on day 3 when there is no alternative. [ABSTRACT FROM AUTHOR]

This work exploits a large panel dataset on Italian manufacturing SMEs to examine the relationship between leverage and firms' financial stability. Specifically, we evaluate whether and to what extent this link is affected by the degree of competition characterising the local credit market in which firms operate. Using two measures of local banking competition – the H-statistic and the Boone indicator – our evidence indicates that the negative impact of leverage on firms' financial health is greater for firms operating in more competitive banking markets. A plausible interpretation of this finding is that the competition drawbacks could prevail on its expected advantages, leading banks to be less inclined to establish lending relationships with risky firms, thus exacerbating their financial vulnerability. [ABSTRACT FROM AUTHOR]

In recent decades, the importance of transport and logistics companies has increased considerably, especially for Lithuania, where this sector is on the rise and creating benefits for various users. Therefore, this study aims to analyse the economic–financial situation of transport and logistics companies operating in Lithuania, focusing mainly on their financial risk, probability of bankruptcy, and level of solvency. To achieve these results, 416 companies were analysed based on their data from 2022. The employed methodology included descriptive analysis, quartile ratio analysis, the use of Altman's Z-score model to predict bankruptcy, and, finally, logistic regression analysis to answer the hypotheses. The results show that the companies analysed in this study were highly profitable, with a high level of solvency and liquidity that did not compromise their continuity in the market. These results were confirmed by the Z-score analysis. In addition, it was observed that the age and size of the companies did not affect their survival on the market. This study presents results that are of great interest for the academic literature, as well as for the management of logistics companies. The originality of the study lies in its relevance and timeliness, presenting robust results for different stakeholders, such as policymakers or new entrepreneurs, among others. [ABSTRACT FROM AUTHOR]

Advances through Research and Development (R&D) companies have marked a meaningful change worldwide. The products developed by these companies are known. However, little is written about how they work, mainly whether they are solvent companies, whether they generate a profit from their activity, how long the life of these companies is, or whether they tend to go bankrupt. In addition, the pandemic caused by Covid-19 has had a significant impact on all types of companies, and it is worth asking whether the effect on R&D companies has been negative or positive. Taking all of this into account, the main objective of this study is to analyze the profitability, liquidity, and solvency situation of Spanish R&D companies considering their size, age and type of field. The impact of the Covid-19 pandemic on these companies will be analyzed too. In total, 135 Spanish companies have been studied, and whether they are R&D companies in natural and technical sciences or social sciences and Humanities has been considered. The Altman Z-score indicator has been used after descriptive analysis of the companies by ratios. This methodology has been used to assess whether the health crisis has compromised the solvency of these companies. The analysis of the study has shown that they are companies of great relevance at the national economic level, which have a favourable liquidity and solvency situation. In case of profitability of these companies the results could not be generalized. Also, results have shown that Covid19 had a significant impact on Spanish R&D companies and their financial and economic situation. This study is an essential contribution to the academic literature, public administration, and management of R&D companies. [ABSTRACT FROM AUTHOR]

This paper investigates the application of machine learning to develop a response model to cardiovascular problems and the use of AdaBoost which incorporates an application of Outlier Detection methodologies namely; Z-Score incorporated with Grey Wolf Optimization (GWO) as well as Interquartile Range (IQR) coupled with Ant Colony Optimization (ACO). Using a performance index, it is shown that when compared with the Z-Score and GWO with AdaBoost, the IQR and ACO, with AdaBoost are not very accurate (89.0% vs. 86.0%) and less discriminative (Area Under the Curve (AUC) score of 93.0% vs. 91.0%). The Z-Score and GWO methods also outperformed the others in terms of precision, scoring 89.0%; and the recall was also found to be satisfactory, scoring 90.0%. Thus, the paper helps to reveal various specific benefits and drawbacks associated with different outlier detection and feature selection techniques, which can be important to consider in further improving various aspects of diagnostics in cardiovascular health. Collectively, these findings can enhance the knowledge of heart disease prediction and patient treatment using enhanced and innovative machine learning (ML) techniques. These findings when combined improve patient therapy knowledge and cardiac disease prediction through the use of cutting-edge and improved machine learning approaches. This work lays the groundwork for more precise diagnosis models by highlighting the benefits of combining multiple optimization methodologies. Future studies should focus on maximizing patient outcomes and model efficacy through research on these combinations. [ABSTRACT FROM AUTHOR]

Background/Aim: Proton pump inhibitors (PPIs), despite being the most prescribed medications today, have generated controversy due to their potential impact on bone metabolism. Numerous studies have emphasized the potential of prolonged PPI use to reduce bone mineral density, thereby increasing the risk of bone fractures among elderly and young individuals. However, the precise impact of PPI usage for 1 year or less on bone mineral density in young adults remains incompletely understood. Method: In this retrospective cohort study, we conducted a comprehensive review of all dual x-ray bone densitometric examinations conducted on females under 40 years old at our tertiary care center between 2010 and 2014. Among the initial 685 patients assessed, 117 samples met the predefined inclusion criteria and were consequently enrolled in the study. Subsequently, the enrolled cases were categorized into three distinct groups: Group 1 (n=46), which received PPI treatment for less than six months; Group 2 (n=31), which received PPIs for a duration ranging from 6 to 12 months; and Group 3 (n=40), comprising individuals with no history of PPI use, thus serving as the control group. Comprehensive baseline descriptive data, encompassing bone mineral density, t-scores, and z-scores, were meticulously compared among the three groups mentioned above. Results: The overall mean age of the study population was 32.84 (5.27) years, with an age range spanning from 20 to 40 years. No statistically significant differences in age were discerned among the three groups. Similarly, the groups exhibited no significant body mass index (BMI) variations. Noteworthy findings emerged after examining the effects of PPI usage on bone mineral density, z-scores, and t-scores across the three groups. Specifically, the data suggested that PPIs might influence t-scores (Group 1: -0.48 (0.77); Group 2: -1.25 (0.86); Group 3: -0.33 (0.78)), yielding an F-value of 13.28 for (2.116), signifying statistical significance at P<0.001. Moreover, the observed mean square error (MSE) was 64, while the effect size (eta²) was 0.19. Subsequent post-hoc Tukey tests indicated a significant distinction in the Tscore of Group 2 compared to the other two groups. Furthermore, the analysis of z-scores (Group 1: 0.46 (0.79); Group 2: -1.27 (0.76); Group 3: -0.35 (0.86)) revealed a similar trend, with an F-value of 13.21 for (2.116) and a P-value below 0.001. The corresponding MSE was 0.65, and the eta² stood at 0.19. Additional post-hoc Tukey tests indicated that the Z-score of Group 2 significantly diverged from the other groups. However, it is noteworthy that both t and z-scores for Group 1 and Group 3 did not exhibit statistically significant differences. Conclusion: Prolonged use of PPIs for durations surpassing 6 months may potentially reduce bone mineral density among young adults. Nevertheless, this observed impact does not attain clinically significant levels of osteopenia. Conversely, using PPIs for periods under 6 months did not significantly affect bone mineral density. [ABSTRACT FROM AUTHOR]