Health Care Procedures Research Articles

Understanding Factors Influencing Geographic Variation in Healthcare Expenditures: A Small Areas Analysis Study.

Dramatic geographic variations in healthcare expenditures were documented by developed countries, but little is known about such variations under China's context, and what causes such variations. This study aims to examine variations of healthcare expenditures among small areas and to determine the associations between demand-, supply-factors, and per capita inpatient expenditures. This cross-sectional study utilized hospital discharge data aggregated within delineated hospital service areas (HSAs) using the small-area analysis approach. Linear multivariate regression modeling with robust standard errors was used to estimate the sources of variation of per capita inpatient expenditures across HSAs covering the years 2017 to 2019; the Shapley value decomposition method was used to measure the respective contributions of demand-, supply-side to such variations. Among 149 HSAs, demand factors explained most of the (87.4%) overall geographic variation among HSAs. With each 1% increase in GDP per capita and urbanization rate was associated with 0.099% and 0.9% increase in inpatient expenditure per capita, respectively, while each 1% increase in the share of females and the unemployment rate was associated with a 0.7% and 0.4% reduction in the per capita inpatient expenditures, respectively. In supply-side, for every 1 increase in hospital beds per 1000 population, the per capita inpatient expenditures rose by 2.9%, while with every 1% increase in the share of private hospitals, the per capita inpatient expenditures would decrease by 0.4%. With Herfindahl-Hirschman Index decrease 10%, the per capita inpatient expenditures would increase 1.06%. This study suggests demand-side factors are associated with large geographic variation in per capita inpatient expenditures among HSAs, while supply-side factors played an important role. The evaluation of geographic variations in per capita inpatient expenditures as well as its associated factors have great potential to provide an indirect approach to identify possibly existing underutilized or overutilized healthcare procedures.

Factors influencing unplanned ICU readmissions: A retrospective cohort study

AimThe goal of this study is to explore the factors that predict ICU readmissions and their correlations with readmissions that occur early and those that occur later. It evaluates various elements, including demographic information, clinical attributes, and variables related to treatment, to gain a more comprehensive understanding of the risk factors influencing the timing of ICU readmissions. MethodsWe conducted a retrospective cohort study, utilizing electronic medical records, to pinpoint adult patients who were repeatedly admitted to the ICU between January 1, 2022, and December 31, 2022. Predictors of early and late ICU readmissions were evaluated, employing statistical analyses that involved logistic regression models. ResultsThe study analyzed data from 136 ICU patients. Patients admitted from the emergency department exhibited 2.22 times higher odds of early readmission in comparison to those admitted from the ward (p-value = 0.044). However, no significant correlations were observed between gender and readmission, and univariate analyses demonstrated no noteworthy variances in age, APACHE II score at discharge, Braden score, and length of ICU stay with regard to the nature of readmission. ConclusionThe findings from our study hold considerable implications for healthcare procedures and policies. These outcomes suggest that the source of ICU admission plays a pivotal role in foretelling early readmission, which could potentially influence patient care and administration. The correlation between the source of ICU admission and early readmissions accentuates the necessity for patient-centric care, especially for those admitted from the emergency department, who face heightened risks.

Use of iron in perinatal anaemia: Indications for women’s health care policies and procedure

This paper reviews management of obstetric anaemia and the role of intravenous iron for the treatment of obstetric anaemia. Red blood cell transfusions are routinely used for haemoglobin restoration in anaemic women. The decision for red blood cell transfusion is made on a combination of haemoglobin level and clinical status, and it is suggested that transfusions are not necessary in those who are well compensated or when alternative therapy is available. To reduce the risk, intravenous iron infusion is proposed as a bloodless therapeutic approach. There are a variety of iron preparations. Intravenous iron infusion can reduce the requirement for blood transfusion in hemodynamically stable women with perinatal anaemia, especially in resource-scarce settings. It a cost-effective bloodless approach for the treatment of anaemia than can enhance patient outcomes. According to the literature, when haemoglobin is greater than 90 g/L, blood transfusion is not often required. In perinatal women with anaemia, the decision whether to administer blood or iron is based on patient preferences, haemoglobin levels, clinical symptoms, past and present medical conditions and the clinician’s judgement. Nevertheless, due to the lack of rigid criteria for blood transfusions in the majority of clinical settings, it is considered the default treatment for anaemia in perinatal women.

Hospital- and county-level characteristics explain geographic variability in prices of cancer-related procedures: Implications for policy and interventions.

Healthcare costs in the U.S. are high and variable, which can hinder access and impact health outcomes across communities. This study examined hospital- and county-level characteristics to identify factors that explain geographic variation in prices for four cancer-related procedures. Data sources included Turquoise Health, which compiles publicly-available price data from U.S. hospitals. We examined list prices for four procedures: abdominal ultrasound, diagnostic colonoscopy, brain MRI, and pelvis CT scan, which we linked to characteristics of hospitals (e.g., number of beds) and counties (e.g., metropolitan status). We used multilevel linear regression models to assess multivariable relationships between prices and hospital- and county-level characteristics. Supplementary analyses repeated these models using procedures prices for commercial insurance plans. For each procedure, list prices varied across counties (intraclass correlation: abdominal ultrasound = 23.2%; colonoscopy = 17.1%; brain MRI = 37.2%; pelvis CT = 50.9%). List prices for each procedure were associated with hospital ownership (all p < 0.001) and percent of population without health insurance (all p < 0.05). For example, list prices for abdominal ultrasound were higher for proprietary versus Government-owned hospitals (β = 539.10, 95% confidence interval [CI]: 256.12, 822.08, p < 0.001) and for hospitals in counties with more uninsured residents (β = 23.44, 95% CI: 2.55, 44.33, p = 0.03). Commercial insurance prices were negatively associated with metropolitan status. Prices for cancer-related healthcare procedures varied substantially, with considerable heterogeneity associated with county location as well as county-level social determinants of health (e.g., health insurance coverage). Interventions and policy changes are needed to alleviate the financial burden of cancer care among patients, including geographic variation in prices for cancer-related procedures.

Employing Advanced Deep Learning Technology for the Detection of Kidney Stones in Unenhanced Computed Tomography (CT) Imaging: A Model-Based Approach

Kidney stones are currently considered a very common disease and recent studies have shown a tendency for the incidence of this disease to increase in recent years. The disease is recognized as a serious threat to the population's health because it is associated with other serious illnesses that can greatly compromise people's quality of life. The development of technologies and strategies aimed at aiding the diagnosis and treatment of this disease has the potential to improve the quality and effectiveness of services provided by health professionals. Diagnosis based on medical images has been one of the main tools for diagnosing kidney stones and Deep Learning techniques have been widely proposed to perform this task. This study proposes a Deep Learning model for detecting kidney stones in computed tomography images. The model was trained with a dataset composed of images obtained from individuals who underwent examinations to analyze diseases in the urinary system. The model achieved an accuracy rate of 96.20% in its predictions and proved to be a suitable tool for treating the problem in question. The results obtained in this study demonstrate the potential of Deep Learning techniques as tools to help improve healthcare procedures related to imaging diagnosis.

Analysis of Implementation of Infection Prevention and Control at Royal Prima Marelan General Hospital

Nosocomial infections or Healthcare-Associated Infections (HAIs) are a serious problem for global public health, including Indonesia. HAIs are infections experienced by patients during treatment and health care procedures ≥ 48 hours and ≤ 30 days after leaving the health facility. This study aims to analyze the implementation of infection prevention and control at the Royal Prima Marelan General Hospital. This research is a quantitative study with an observational analytical approach with a Cross Sectional Study design, namely in the form of data collection aimed at analyzing the implementation of infection prevention and control at the Royal Prima Marelan General Hospital for the period July to August 2023. The population in this study was 100 people who included hospital management who were considered competent in providing information. The population sample for this study that met the inclusion and exclusion criteria was 50 people. The results of bivariate analysis show that the variables related to infection prevention and control are knowledge, motivation, supervision and workload. The results of multivariate analysis show that the variable that partially influences the prevention and control of nosocomial infections in hospitals is knowledge.

EPH224 Temporal Trends of Percutaneous Transluminal Coronary Angioplasty Procedure and Mortality Rates in the Brazilian Public Healthcare: A Real World Data Analysis From 2014 to 2022

EPH224 Temporal Trends of Percutaneous Transluminal Coronary Angioplasty Procedure and Mortality Rates in the Brazilian Public Healthcare: A Real World Data Analysis From 2014 to 2022

Penanganan Limbah Medis Padat di Puskesmas X

Public Health Centre facilities are integral to the healthcare system, playing a vital role in safeguarding public health at the primary level. These facilities, beyond delivering medical services, generate substantial quantities of medical waste due to various healthcare procedures. The management of medical waste in these centers presents challenges, notably the need for interim storage before third-party collection. Additionally, monthly solid medical waste transportation from all District health centers poses concerns about potential waste accumulation. This study falls into the category of descriptive research, aiming to provide an illustrative snapshot of current solid medical waste management. A survey at Public Health Centre X found that each polyclinic produces an average of 0.49 kg of solid medical waste daily, totaling 76.4 kg per month. Notably, all samples during packaging, transportation, and storage phases failed to meet specified criteria. Similarly, during sorting, the majority (83%) did not meet standards, with only one sample (16.3%) complying. This underscores the pressing need for staff training in medical waste procedures. To elevate medical waste management standards, health centers must integrate policies and regulations into their daily operations. Additionally, improving current facilities, infrastructure, and procedures is paramount to address this issue effectively. In conclusion, Public Health Centre facilities, vital for primary healthcare, grapple with medical waste management challenges. This study underscores the importance of immediate action in staff training and policy integration while investing in facility enhancements to achieve optimal medical waste management.

Healthcare and Cloud Computing: Exploring Opportunities, Addressing Challenges, and Charting Future Directions

Cloud computing has become a revolutionary technology in the healthcare industry, providing chances to increase patient care, simplify operations, and promote collaboration among healthcare providers. This review paper investigates the implementation of cloud computing in the healthcare industry, analyzing its prospective advantages, existing obstacles, and forthcoming advancements. The text explores the potential offered by cloud technologies, including expandable storage, data analysis, and telemedicine options, while also considering obstacles associated with data security, regulatory adherence, and interoperability. The study assesses methods for surmounting these obstacles and delineates prospective avenues for utilizing cloud computing to enhance healthcare provision and foster innovation. The suggested method exhibits robust performance in evaluating and forecasting outcomes, highlighting the potential of cloud computing to greatly revolutionize healthcare procedures, with an accuracy of 97.6%, a mean absolute error (MAE) of 0.403, and a root mean square error (RMSE) of 0.203.

Adjusting for Confounders in Outcome Studies Using the Korea National Health Insurance Claim Database: A Review of Methods and Applications.

Adjusting for potential confounders is crucial for producing valuable evidence in outcome studies. Although numerous studies have been published using the Korea National Health Insurance Claim Database, no study has critically reviewed the methods used to adjust for confounders. This study aimed to review these studies and suggest methods and applications to adjust for confounders. We conducted a literature search of electronic databases, including PubMed and Embase, from January 1, 2021 to December 31, 2022. In total, 278 studies were retrieved. Eligibility criteria were published in English and outcome studies. A literature search and article screening were independently performed by 2 authors and finally, 173 of 278 studies were included. Thirty-nine studies used matching at the study design stage, and 171 adjusted for confounders using regression analysis or propensity scores at the analysis stage. Of these, 125 conducted regression analyses based on the study questions. Propensity score matching was the most common method involving propensity scores. A total of 171 studies included age and/or sex as confounders. Comorbidities and healthcare utilization, including medications and procedures, were used as confounders in 146 and 82 studies, respectively. This is the first review to address the methods and applications used to adjust for confounders in recently published studies. Our results indicate that all studies adjusted for confounders with appropriate study designs and statistical methodologies; however, a thorough understanding and careful application of confounding variables are required to avoid erroneous results.

Decreases in Rhinology Care Utilization by People with Cystic Fibrosis on Highly Effective Modulator Therapy.

Many people with cystic fibrosis (PwCF) have chronic rhinosinusitis (CRS). CRS requires additional management beyond that of pulmonary disease and leads to increased utilization of healthcare resources. Elexacaftor/tezacaftor/ivacaftor (ETI) is a highly effective modulator therapy that has been shown to improve CRS in PwCF. However, the impact of ETI on rhinologic healthcare utilization is understudied. To compare rates of rhinologic healthcare utilization and procedures among PwCF prior to and after initiating ETI therapy. A single-center, cohort study investigating adult PwCF was performed in January 2023. Demographics, clinical characteristics, and data related to CF treatment were retrospectively abstracted. Characteristics of the cohort were compared over 2 periods: the 12-months prior to ETI initiation and the 12-months after ETI initiation. Post-ETI data were linearly extrapolated if a subject had not yet completed the full 12 months of ETI. Paired t-testing, Wilcoxon signed rank testing, and regression analysis were performed. Of 126 PwCF, 98 (77.8%) were on ETI therapy and 35 (27.7%) were both on ETI and concurrently followed by the rhinology service (ETI-ENT). Rhinology clinic visits (P = .007) and frequency of obtaining nasal cultures (P = .046) decreased for the ETI-ENT cohort after initiating ETI treatment. There were no significant changes in the number of endoscopic sinus surgeries (P = .452) performed. Beyond ETI use, regression analysis did not identify any factors associated with changes in utilization. Aspects of rhinology healthcare utilization by PwCF decreased after initiation of ETI therapy. Additional studies are needed to determine rhinologic healthcare requirements for PwCF who remain on ETI for the long-term and to evaluate larger cohorts of PwCF on ETI.

One-year outcome of elderly patients with endocarditis: a retrospective observational study

Abstract Background The incidence of infective endocarditis (IE) is rising in general population, especially in elderly, where it is associated with high morbidity and mortality. Health care procedures, degenerative heart valve diseases and intracardiac electronic devices are the main risk factors for IE in elderly population. Cardiac surgery is largely underused in these patients and the few available observational studies seem to confirm the positive outcome of surgery. Purpose The aim of the present study is to assess differences in survival between elderly patients affected by endocarditis treated with a conservative strategy or cardiac surgery. Methods We conducted a retrospective observational study of 143 elderly patients (age ≥ 70 years old) affected by endocarditis with at least one year of follow-up who were hospitalized between 2016 and 2022. The primary endpoint was the difference in one-year all-cause mortality between patients treated with a conservative strategy or cardiac surgery. The secondary endpoint was one-year mortality for sepsis or septic shock. The cumulative probability of survival was calculated using the Kaplan-Meier estimator. The log-rank test was used to compare between-group differences in survival and cox regression was used in the uni and multivariate analysis, a p&amp;lt;0.05 was considered significant. Results Between 2016 and 2022, 242 patients have been diagnosed with IE. Between them, 143 patients were at least 70 years old (59%). Cardiac surgery was performed in 16 patients, while 127 were treated with medical therapy alone. Patients treated with cardiac surgery were younger (74y vs 80y, p=0.005) and had higher prevalence of severe valvular heart disease (69% vs 23%, p&amp;lt; 0.001). The primary endpoint of one-year all-cause mortality occurred in 80 patients in the conservative strategy group and in 5 patients treated with surgery (p=0.015); the secondary endpoint occurred in 42 patients in conservative strategy group, while no patients treated with surgery died for sepsis or septic shock (p=0.006). Finally, surgery was associated with better one-year survival (HR 0.34, 95% CI 0.14 - 0.85). Conclusions IE in elderly patients is an emerging clinical matter since its incidence is rising but mortality has not significantly decreased. Current clinical guidelines do not give specific indication for elderly, who are generally excluded from surgery due to the high risk carried by age and comorbidities. Few previous studies have analyzed the best treatment strategy in this cohort of patients, but data from observational studies shows a better outcome among those undergone surgery. The result of our work confirmed that elderly patients with IE treated with cardiac surgery have better one-year survival and lower rate of death for all causes, sepsis or septic shockKaplan Mayer Curve For One-Year Survival

Accompaniment of minors during health care procedures

In clinical practice, it is not rare to encounter situations in which parents and families are asked to leave the child alone with the health care team in rooms full of devices throughout the performance of procedures, which at times may give rise not only to conflicts but, more importantly, emotional sequelae in children or adolescents.We conducted a narrative review of the literature by searching the digital library of the public health care system of Andalusia for articles concerning the experiences of health care professionals and families with the accompaniment of paediatric patients during health care procedures. We restricted the search to studies published in Spanish or English and conducted in humans.The review evinced the need to humanise care in order to improve care quality. The need to accompany minors is supported by the evidence from works that have analysed the factors involved in the persistence of these behaviours and attitudes in both professionals and parents. We consider it necessary to develop institutional policies and appoint mediators to compile the statements of different national and international societies, taking into account legal aspects but, above all, the pertinent values from a health care ethics perspective, and in pursuit of the best interests of the child.

Collaborative Virtual Reality Real-Time 3D Image Editing for Chest Wall Resections and Reconstruction Planning

The integration of extended reality (XR) technologies into health care procedures presents transformative opportunities, particularly in surgical processes. This study delves into the utilization of virtual reality (VR) for preoperative planning related to chest wall resections in thoracic surgery. Leveraging the capabilities of 3-dimensional (3D) imaging, real-time visualization, and collaborative VR environments, surgeons gain enhanced anatomical insights and can develop predictive surgical strategies. Two clinical cases highlighted the effectiveness of this approach, showcasing the potential for personalized and intricate surgical planning. The setup provides an immersive, dynamic representation of real patient data, enabling collaboration among teams from separate locations. While VR offers enhanced interactive and visualization capabilities, preliminary evidence suggests it may support more refined preoperative strategies, potentially influence postoperative outcomes, and optimize resource management. However, its comparative advantage over traditional methods needs further empirical validation. Emphasizing the potential of XR, this exploration suggests its broad implications in thoracic surgery, especially when dealing with complex cases requiring multidisciplinary collaboration in the immersive virtual space, often referred to as the metaverse. This innovative approach necessitates further examination, marking a shift toward future surgical preparations. In this article, we sought to demonstrate the technique of an immersive real-time volume-rendered collaborative VR-planning tool using exemplary case studies in chest wall surgery.

Patient Safety Culture among Nurses: Case Study

Introduction: Patient safety is the concerted effort to prevent errors in healthcare procedures that may endanger patients. Every healthcare provider faces the risk of making mistakes in delivering healthcare services, potentially jeopardizing patient safety. This study aims to assess the patient safety culture among nurses at Gambiran Hospital, identify strengths, weaknesses, opportunities, and threats (SWOT), and formulate strategies for Gambiran Hospital.&#x0D; Methods: This quantitative study employed a case study design conducted at Gambiran Hospital. A total of 150 respondents were selected using a total sampling technique, and data were collected through the distribution of questionnaires. Data analysis was conducted using univariate analysis.&#x0D; Results: The prioritization of issues is essential to develop strategies aimed at improving the patient safety culture among nurses. This approach ensures that nurses are more receptive to reporting incidents (RRI) during their shifts.&#x0D; Conclusion: Assessing the patient safety culture among nurses in the Dhaha room is crucial, as it encourages nurses to report incidents and facilitates the socialization of initiatives aimed at enhancing patient safety culture among nurses.

Improving patient safety governance andsystems through learning from successes andfailures: qualitative surveys andinterviews with international experts.

Patient harm is a leading cause of global disease burden with considerable morbidity, mortality, and economic impacts for individuals, families, and wider society. Large bodies of evidence exist for strategies to improve safety and reduce harm. However, it is not clear which patient safety issues are being addressed globally, and which factors are the most (or least) important contributors to patient safety improvements. We aimed to explore the perspectives of international patient safety experts to identify: (1) the nature and range of patient safety issues being addressed, and (2) aspects of patient safety governance and systems that are perceived to provide value (or not) in improving patient outcomes. English-speaking Fellows and Experts of the International Society for Quality in Healthcare participated in a web-based survey and in-depth semistructured interview, discussing their experience in implementing interventions to improve patient safety. Data collection focused on understanding the elements of patient safety governance that influence outcomes. Demographic survey data were analysed descriptively. Qualitative data were coded, analysed thematically (inductive approach), and mapped deductively to the System-Theoretic Accident Model and Processes framework. Findings are presented as themes and a patient safety governance model. The study was approved by the University of South Australia Human Research Ethics Committee. Twenty-seven experts (59% female) participated. Most hailed from Africa (n = 6, 22%), Australasia, and the Middle East (n = 5, 19% each). The majority were employed in hospital settings (n = 23, 85%), and reported blended experience across healthcare improvement (89%), accreditation (76%), organizational operations (64%), and policy (60%). The number and range of patient safety issues within our sample varied widely with 14 topics being addressed. Thematically, 532 textual segments were grouped into 90 codes (n = 44 barriers, n = 46 facilitators) and used to identify and arrange key patient safety governance actors and factors as a 'system' within the System-Theoretic Accident Model and Processes framework. Four themes for improved patient safety governance were identified: (1) 'safety culture' in healthcare organizations, (2) 'policies and procedures' to investigate, implement, and demonstrate impact from patient safety initiatives, (3) 'supporting staff' to upskill and share learnings, and (4) 'patient engagement, experiences, and expectations'. For sustainable patient safety governance, experts highlighted the importance of safety culture in healthcare organizations, national patient safety policies and regulatory standards, continuing education for staff, and meaningful patient engagement approaches. Our proposed 'patient safety governance model' provides policymakers and researchers with a framework to develop data-driven patient safety policy.

A Novel LSTM-based Data Synthesis Approach for Performance Improvement in Detecting Epileptic Seizures

Bio-electrical time signals play a significant role in assisting non-invasive observational procedures in healthcare. These bioelectrical signals are weak signals with inherently low voltage and low frequency, hidden mostly under relatively large high-voltage noise signals. Hence it is extra challenging to analyze them. In modern clinical data analysis, these signals could be further analyzed using conventional machine learning (ML) methods. Also, in the recent past, two-dimensional spectrum-based classification, predominantly with Convolutional Neural Networks (CNN), has been tried with time-series data. One of the objectives of this study is to find which approach would suit better for biomedical signal analysis when data are scarce and signals are weak. Also, in bio-medical signal analysis data is scarce. Yet, to effectively train either an ML or a deep learning (DL) model, a sample clinical dataset of a significant size is required. Hence, the second objective of this research is to present a novel data synthesis method to address data scarcity. With these objectives, the study compares the performance of the time-series-based classification with traditional ML approaches, against the 2D spectrum-based classification for bio-electrical signal classification. For this purpose the study utilizes learning models; Multi-layer Perceptron (MLP), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Long Short-Term Memory Networks (LSTMs), Auto Encoder (AE), and Convolutions Neural Network (CNN). Also, the authors propose a novel data synthesis method based on LSTMs to improve the sample size of the standard CHB-MIT Scalp EEG dataset. The results show that with the expanded dataset, the two-dimensional spectrum-based classification architecture was able to achieve a precision level of 85% at the classification. The conventional ML-based methods showed on average a precision level of 82%. In conclusion with the proposed virtual sample generation approach, 2D spectrum-based classification with Convolutional Neural Networks showed promising performances.

Acompañamiento a los menores durante los procedimientos asistenciales

In clinical practice, it is not rare to encounter situations in which parents and families are asked to leave the child alone with the health care team in rooms full of devices throughout the performance of procedures, which at times may give rise not only to conflicts but, more importantly, emotional sequelae in children or adolescents.We conducted a narrative review of the literature by searching the digital library of the public health care system of Andalusia for articles concerning the experiences of health care professionals and families with the accompaniment of paediatric patients during health care procedures. We restricted the search to studies published in Spanish or English and conducted in humans.The review evinced the need to humanise care in order to improve care quality. The need to accompany minors is supported by the evidence from works that have analysed the factors involved in the persistence of these behaviours and attitudes in both professionals and parents. We consider it necessary to develop institutional policies and appoint mediators to compile the statements of different national and international societies, taking into account legal aspects but, above all, the pertinent values from a health care ethics perspective, and in pursuit of the best interests of the child.

HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis.

Synthetic digital twins based on medical data accelerate the acquisition, labelling and decision making procedure in digital healthcare. A core part of digital healthcare twins is model-based data synthesis, which permits the generation of realistic medical signals without requiring to cope with the modelling complexity of anatomical and biochemical phenomena producing them in reality. Unfortunately, algorithms for cardiac data synthesis have been so far scarcely studied in the literature. An important imaging modality in the cardiac examination is three-directional CINE multi-slice myocardial velocity mapping (3Dir MVM), which provides a quantitative assessment of cardiac motion in three orthogonal directions of the left ventricle. The long acquisition time and complex acquisition produce make it more urgent to produce synthetic digital twins of this imaging modality. In this study, we propose a hybrid deep learning (HDL) network, especially for synthetic 3Dir MVM data. Our algorithm is featured by a hybrid UNet and a Generative Adversarial Network with a foreground-background generation scheme. The experimental results show that from temporally down-sampled magnitude CINE images (six times), our proposed algorithm can still successfully synthesise high temporal resolution 3Dir MVM CMR data (PSNR=42.32) with precise left ventricle segmentation (DICE=0.92). These performance scores indicate that our proposed HDL algorithm can be implemented in real-world digital twins for myocardial velocity mapping data simulation. To the best of our knowledge, this work is the first one investigating digital twins of the 3Dir MVM CMR, which has shown great potential for improving the efficiency of clinical studies via synthesised cardiac data.

Dysmenorrhea Impact and Insights: A Statistical Analysis among Allied Health Professional Students in West Bengal, India

Introduction: Dysmenorrhea is a prevalent gynecological disorder that is characterized by the presence of unpleasant menstrual cramps. This condition has been found to have significant medical, psychological, and social implications for individuals who experience it. Although commonly seen as an inherent characteristic of a properly functioning reproductive system, it can potentially operate as a diagnostic tool for underlying illnesses. Regrettably, dialogues pertaining to dysmenorrhea are sometimes prohibited, particularly among males, within diverse cultural contexts.&#x0D; Objective: The primary objective of this study is to evaluate the level of knowledge and attitudes among allied health professions students enrolled at various universities of West Bengal (WB), India with regard to dysmenorrhea. This study aims to examine the impact of cultural variables on the knowledge and communication surrounding dysmenorrhea, specifically within conservative Indian districts.&#x0D; Methods: The study sample consisted of 494 students enrolled in allied health professions faculties at different universities of WB. Data collection took place from September 2021 to February 2023. A meticulously designed survey was employed to gather data pertaining to the various sources of knowledge, levels of awareness, attitudes toward discussing dysmenorrhea, and willingness to engage in conversations about menstruation with prospective females. Data interpretation involved the utilization of statistical analysis techniques, such as descriptive statistics and correlation analysis.&#x0D; Results: In terms of demographic composition, the study consisted of 86% female participants and 14% male participants. The mean knowledge scores of females (14.41 ± 3.14) were found to be considerably higher compared to males (13.75 ± 4.56). The primary sources of information were the internet (58.3%), maternity figures (48.8%), and educational institutions (46.2%). An observed positive connection (r = 0.244) was found between age and knowledge levels. The participants exhibited a general hesitancy to openly engage in conversations on menstrual symptoms, however, they demonstrated a readiness to engage in discussions about menstruation with their prospective daughters.&#x0D; Conclusions: The present study brings attention to the gender discrepancies in knowledge levels pertaining to dysmenorrhea among allied health professions university students of WB. Additionally, it emphasizes the influence of cultural norms on knowledge acquisition and communication around this topic. The statement underscores the need for destigmatization initiatives, comprehensive teaching on menstruation health, and fostering open communication within academic institutions and the broader community. The aforementioned findings offer valuable insights that can inform future educational endeavors and healthcare procedures within this particular subject.