Physicians Research Articles

An educational review on over-the-counter drugs- A Pharmacovigilance-based approach

Over-the-counter (OTC) medicines, a crucial component of the healthcare system, can be sold to the consumer without a registered medical practitioner (RMP) prescription. They are safe and effective when used according to the instructions on the label and as directed by healthcare professionals. OTC medications are effective in treating common ailments. Switching drugs from prescription to OTC has increased worldwide, saving time and reducing the burden on the healthcare system. Many people rely on OTC to treat everyday ailments like headaches, colds, fever, coughs, indigestion, flu, and dermatitis. Therefore, a wide safety margin must be established for the OTC drugs. OTC product benefits must outweigh the risks, and the chances of misuse of it should be low. Consumers think that OTC medicines are safe since pharmacists dispense them without a prescription from a registered medical practitioner. However, OTC has adverse effects and could be misused, abused, or interact with prescription drugs. Failure to comply with directions may lead to serious side effects. For example, an overdose of Acetaminophen has been associated with liver damage. Analgesics increase gastrointestinal tract bleeding even when taken at appropriate doses. Cough products such as Dextromethorphan and Diphenhydramine may be abused due to their euphoric and alcohol-like effects. A distinct Pharmacovigilance system should be implemented to optimize the safe use of OTC drugs.3

DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation.

Cardiac magnetic resonance imaging (MRI) plays a crucial role in monitoring disease progression and evaluating the effectiveness of treatment interventions. Cardiac MRI allows medical practitioners to assess cardiac function accurately by providing comprehensive and quantitative information about the structure and function, hence making it an indispensable tool for monitoring the disease and treatment response. Deep learning-based segmentation enables the precise delineation of cardiac structures including the myocardium, right ventricle, and left ventricle. The accurate segmentation of these structures helps in the diagnosis of heart failure, cardiac functional response to therapies, and understanding the state of the heart functions after treatment. The objective of this study is to develop a multiscale deep learning model to segment cardiac organs based on MRI imaging data. Good segmentation performance is difficult to achieve due to the complex nature of the cardiac structure, which includes a variety of chambers, arteries, and tissues. Furthermore, the human heart is also constantly beating, leading to motion artifacts that reduce image clarity and consistency. As a result, a multiscale method is explored to overcome various challenges in segmenting cardiac MRI images. This paper proposes DeSPPNet, a multiscale-based deep learning network. Its foundation follows encoder-decoder pair architecture that utilizes the Spatial Pyramid Pooling (SPP) layer to improve the performance of cardiac semantic segmentation. The SPP layer is designed to pool features from densely convolutional layers at different scales or sizes, which will be combined to maintain a set of spatial information. By processing features at different spatial resolutions, the multiscale densely connected layer in the form of the Pyramid Pooling Dense Module (PPDM) helps the network to capture both local and global context, preserving finer details of the cardiac structure while also capturing the broader context required to accurately segment larger cardiac structures. The PPDM is incorporated into the deeper layer of the encoder section of the deep learning network to allow it to recognize complex semantic features. An analysis of multiple PPDM placement scenarios and structural variations revealed that the 3-path PPDM, positioned at the encoder layer 5, yielded optimal segmentation performance, achieving dice, intersection over union (IoU), and accuracy scores of 0.859, 0.800, and 0.993, respectively. Different PPDM configurations produce a different effect on the network; as such, a shallower layer placement, like encoder layer 4, retains more spatial data that need more parallel paths to gather the optimal set of multiscale features. In contrast, deeper layers contain more informative features but at a lower spatial resolution, which reduces the number of parallel paths required to provide optimal multiscale context.

Individual liberty, safety and police liabilities under the mental health (care and treatment) act.

How should a society strike a balance between the objective of ensuring safety from dangers that may be posed by individuals believed to have a mental disorder and the deprivation of their liberty? How should police officers discharge their duties in apprehending such individuals with a view to conveying them to a medical practitioner at a psychiatric institution? These legal issues took centrestage in the Singapore High Court decision of Mah Kiat Seng v Attorney-General in which the apprehended individual brought claims in false imprisonment against a police officer. The decision examined the underlying purposes of the Singapore Mental Health (Care and Treatment) Act, the right of the person to be informed of the grounds of apprehension, the bases of the police officer's belief that the person posed a danger to himself or others, and the circumstances in which the police officers may be entitled to immunity from liability to civil or criminal proceedings. The High Court judgment led to statutory amendments to clarify police duties when apprehending such individuals and discussions about enhancements to police training and crisis support services for persons with mental illnesses. With reference to the law and/or policy in Australia and the UK, the paper critiques the judicial findings, the statutory amendments and policy alternatives.

Cultural safety and the medical profession in Aotearoa New Zealand: a training framework and the pursuit of Māori health equity.

The concept of cultural safety, developed in the training of nurses over 30 years ago, was adopted by the Medical Council of New Zealand in 2019. We report on the journey of the Medical Council of New Zealand, Te ORA (the Māori Medical Practitioners Association) and the Council of Medical Colleges, and our increasing understanding of cultural competence and cultural safety in promoting best outcomes for Māori patients over the years. We describe in detail the key components of a cultural safety training framework as a tool for medical colleges' training of registrars and the Continuing Professional Development (CPD) of specialist medical practitioners. Finally, we discuss pathways forwards for cultural competence and cultural safety training that apply to a society with diverse cultural needs, noting that such training has been proposed as significant in shifting "difficult to change" Māori health inequities.

Relative Citation Ratio Among Pediatric Orthopaedic Surgeons: Examining the Factors Associated With Higher Scores.

Academic scholarship is often valued by clinicians, peers, and intuitions. Quantifying the effect of research publications is challenging. Various metrics have been used to assess this. This study aimed to examine the relatively new research metric, relative citation ratio (RCR), introduced by the National Institutes of Health, for pediatric orthopaedic surgeons to establish the benchmarking of research effect within the field and understand the distribution and basis for the use of this metric among pediatric orthopaedic surgeons. The RCR indices were assessed for members of the Pediatric Orthopaedic Society of North America using the iCite online web service. The mean RCR (mRCR, the yearly average RCR) and weighted RCR (wRCR, the cumulative RCR score) were assessed for each member. This information was used to perform univariate and two multivariate ordinary least squares regressions for the two metrics. Independent variables were physician sex, years since receiving national provider identifier, MD versus DO degree, whether the physician had a PhD, and geographic region of practice (Northeast, Southeast, Midwest, West, and Southwest). A total of 770 pediatric orthopaedic physicians were identified. The median [interquartile range] wRCR was 15.6 [4.9 to 54.2], and median mRCR was 1.4 [1.0 to 1.9]. Multivariable squares regression for wRCR showed an independently increased wRCR associated with male sex (39.11), PhD (23.32), years since receiving national provider identifier (4.51), and northeast region (48.44). However, these trends were not notable for mRCR where only southeast region was notable. Although each has its caveats, both mRCR and wRCR have a place in evaluating an author's publication history and other research metrics. Furthermore, it is important to know the overall research metrics within a field to allow for inter- and intraspecialty comparisons. Understanding RCR is helpful because it allows for new comparisons within and across fields and career lengths.

The Birth of the “Indian” Clinic: Daktari Medicine in A Ballad of Remittent Fever

This article locates the clinic as a historically contingent space which faced cultural resistance and remained alien to the colonized population in India. It corroborates the socio-political tension in setting up a clinic within the colony and investigates how the Western clinic as a colonial apparatus was resituated as the “Indian clinic” per se. With the historical emergence of a new class of medical practitioners called “daktars” (a Bengali vernacularization of the term “doctor”), the health-seeking behaviour and public health model of colonial India witnessed a decolonial shift. Unlike their English counterparts, daktars did not enjoy a privileged position within the medical archives of colonial India. This archival gap within Indian medical history presents itself as a viable topic for discussion through the means of the literature of the colonized. Bengali writer Ashoke Mukhopadhyay’s novel Abiram Jwarer Roopkotha (2018), translated into English as A Ballad of Remittent Fever in 2020, remedies the colonial politics of the archive by reconstructing the lives of various daktars and their pursuit of self-reliance. The article takes a neo-historical approach towards understanding and assessing the past of daktari medicine and thereby offers comments on its traces in the contemporary public health of India.

Differential Pace: Technology and Inequality in the Making of Episodic Disability

This article reworks disability frameworks to account for the sustained denial of recognition and care experienced by many episodically disabled people. This reworking is grounded in an ethnographic examination of how people obtain an epilepsy diagnosis in the Midwestern United States. Diagnosis can be straightforward for people whose seizures are witnessed by other people or medical technologies and people who can access specialty care. Others remain undiagnosed for long periods because first-line medical practitioners may not recognize epilepsy due to a confluence of social and technical factors. The article proposes the notion of differential pace to account for temporal relations in the construction and experience of episodic disability. Unpacking the interaction between time, technology, and inequality in patient experience, the article advances disability theory and makes critical contributions to debates in disability studies, the medical humanities, and medical anthropology.

Pavlovian theory and the development of traditional Chinese medicine, 1949-1961.

After the founding of the People's Republic of China in 1949, the leadership of the new country carried out a political, cultural, and scientific campaign to "comprehensively learn from the Soviet Union," with the goal of rapid development on all fronts. In the realm of medicine, this had profound consequences. The hegemonic Soviet theory of physiology and psychology-Pavlovianism-became highly influential in China, first as Party Line and second as the basis for a reformed "traditional Chinese medicine". In the early 1950s, Pavlov's theory of higher nervous activity had the status of unquestioned orthodoxy. However, a disagreement between the Ministry of Health and national leader Mao Zedong led to an important shift in 1954. After that date, instead of adopting the Soviet theories wholesale, Chinese medical practitioners used Pavlovianism to shape Chinese medicine's underlying theoretical constructs. The influence of this reconstruction persists to this day, in practices thought of by the public as thoroughly Chinese, like acupuncture, holistic thinking, inner organs theory, and acupoint injection therapy.

Exploring the Lived Experiences of Clinical Educators: Challenges, Motivations, and Future Perspectives

Introduction: This study examines the factors contributing to the shortage of medical doctors teaching medical students despite their crucial role in training the future medical workforce. Methods: To analyze the factors behind the lack of medical doctors in the training of medical students, we used ‘phenomenology’ to understand clinical educators' lived experiences and their constructed meanings. Within the domain of phenomenology, we applied hermeneutic (interpretive) phenomenology. The experiences of eight clinical educators at the Gulf Medical University were explored through interviews and analyzed using Interpretative Phenomenological Analysis (IPA) and Socio-Cognitive Career Theory (SCCT). Results: The findings revealed that entry into medical education often occurred serendipitously due to inadequate career counseling and the undervaluation of the field. Acquiring a postgraduate medical education qualification in medical education enhanced one’s professional life and fostered a sense of identity as a clinical educator. Key motivators included a passion for the field, student interaction, support from colleagues, and an encouraging working environment. Clinical educators faced challenges, such as the field's low value, vague professional identity, delays in promotion, specifically in UAE, low income, and insufficient dedicated teaching time. Coping strategies involved cultivating a positive work environment and maintaining optimism. Growing awareness and a positive outlook for medical education were noted. Conclusion: This study uncovered the underlying issues faced by clinical educators through their lived experiences. To change the status quo, we propose facilitating medical students and young doctors in joining this field early in their careers through strong career counseling and advocating clear entry and progression pathways. Young medical educators should be facilitated by providing an encouraging environment, acknowledging their medical education-related qualifications, and improving remuneration.

Expert consensus on endovascular reconstruction of visceral branch arteries in the treatment of aortic expansion diseases (2024 edition)

Aortic expansion diseases, especially those involving visceral branch arteries, pose significant challenges for clinicians in terms of treatment strategy selection and implementation. With the advancement of endovascular repair techniques, the mode of treatment is shifting gradually from open surgery to minimally invasive surgery, significantly reducing perioperative mortality and complication rates. However, the application of techniques for reconstructing visceral artery branches is not yet widespread, and there is considerable controversy in the management of complex cases. In response, the Vascular Surgery Group of Surgery Society of Chinese Medical Association, the Vascular Surgery Group of Cross-straits Medicine Exchange Association and the Thoracic Aorta Group of Vascular Surgeons Society of Chinese Medical Doctor Association convened relevant experts in China with extensive experience in the endovascular reconstruction of visceral branches for aortic expansion diseases, based on systematic reviews of clinical practice and domestic and international literature, and after in-depth discussions, have developed the Expert consensus on endovascular reconstruction of visceral branch arteries in the treatment of aortic expansion diseases (2024 edition). The consensus focuses on endovascular techniques involving the reconstruction of visceral artery branches, aiming to provide principled guidance for clinicians and to promote the improvement of diagnostic and treatment levels in this field within China.

Visualizing Empathy in Patient-Practitioner Interactions Using Eye-Tracking Technology: Proof-of-Concept Study.

Communication between medical practitioners and patients in health care settings is essential for positive patient health outcomes. Nonetheless, researchers have paid scant attention to the significance of clinical empathy in these interactions as a practical skill. This study aims to understand clinical empathy during practitioner-patient encounters by examining practitioners' and patients' verbal and nonverbal behaviors. Using eye-tracking techniques, we focused on the relationship between traditionally assessed clinical empathy and practitioners' actual gaze behavior. We used mixed methods to understand clinical encounters by comparing 3 quantitative measures: eye-tracking data, scores from the Korean version of the Jefferson Scale of Empathy-Health Professional, and Consultation and Relational Empathy survey scores. We also conducted qualitative interviews with patients regarding their encounters. One practitioner and 6 patients were involved in the experiment. Perceived empathy on the part of the practitioner was notably higher when the practitioner focused on a patient's mouth area during the consultation, as indicated by gaze patterns that focused on a patient's face. Furthermore, an analysis of areas of interest revealed different patterns in interactions with new as opposed to returning patients. Postconsultation interviews suggested that task-oriented and socially oriented empathy are critical in aligning with patients' expectations of empathetic communication. This proof-of-concept study advocates a multidimensional approach to clinical empathy, revealing that a combination of verbal and nonverbal behaviors significantly reinforces perceived empathy from health care workers. This evolved paradigm of empathy underscores the profound consequences for medical education and the quality of health care delivery.

Biography of Prof. Dr. Albert Eckstein and His Studies in Türkiye.

The aim of the article is to contribute to the international academic literature within the scope of Web of Science with a comprehensive article that complies with academic criteria on Prof. Eckstein and his studies in Türkiye. First, this study scans all the literature on the subject and found the necessary books and articles. It uses Prof. Baskan's archive for the photographs. We found the work of Dr. Nuriye Peker with the help of Prof. Akar. The article covers Prof. Eckstein's life and focuses on the period in Türkiye. During the 1930s, a group of German medical doctors, led by German-Jewish pediatrician Prof. Eckstein, migrated to Türkiye. Prof. Eckstein initiated scientific research on children's health and healthcare in remote Anatolian regions in 1937. This approach had a profound impact on the development of healthcare systems for large population segments in developing nations such as Türkiye at that time. Prof. Eckstein and his assistants like Dr. Demirağ, Dr. Doğramacı, and Dr. Cura are regarded as the pioneers of modern Turkish healthcare and health sciences. Prof. Eckstein excelled as a clinician, educator, and researcher, specializing in infectious diseases, disorders of the central nervous system, the biology of premature and newborn infants, and preventive pediatric care. His work in Türkiye transformed pediatric practice and education by introducing Western medical knowledge and techniques. Eckstein's achievements include groundbreaking treatments for noma, an oral mucosa infection caused by Borrelia, and malaria.

Factors associated with low birth weight in low-income populations in the Western Balkans: insights from the multiple indicator cluster survey

IntroductionLow birth weight, defined as a birth weight below 2,500 g, represents a significant public health concern with a multifactorial risk dimension. Socio-demographic factors and individual characteristics of women and their social environment could influence low birth weight. This study aimed to analyze the association between the socio-demographic and reproductive characteristics of women living in low-income households and low birth weight in Serbia, Kosovo, and Montenegro.MethodsThis study was conducted as secondary data analysis during the Multiple Indicator Cluster Survey – Round 6 in Serbia, Kosovo, and Montenegro. The household questionnaire and the individual questionnaire for women aged 15–49 were used as standard research instruments. We analyzed 1,019 women whose households belonged to the first (poorest) or second (poor) wealth index quintiles and who had given birth to a live child within the 2 years preceding the study. A multivariate logistic regression was applied with low birth weight in newborns as the outcome variable.ResultsThe univariate regression analysis showed that women with low birth weight newborns were significantly more likely to live in settlements mainly inhabited by Roma, reside in urban areas, marry or enter a union before age 18, have lower education levels, experience higher illiteracy rates, and receive antenatal care not provided by a medical doctor compared to women whose newborns weighed 2.5 kg or more. A multivariate logistic regression model with a low birth weight of newborns as an outcome variable showed the association between women’s illiteracy (OR: 1.741; 95% CI: 1.060–2.859) and antenatal care not provided by a medical doctor (OR: 2.735; 95% CI: 1.229–6.087).DiscussionIlliteracy and limited access to medical doctor services during pregnancy were factors that increased the likelihood of low birth weight in newborns born to women living in low-income households in the selected Western Balkans populations. The cross-sectional design of this study does not allow the establishment of causal relationships among variables, but it can provide important evidence for future prevention strategies. Interventions are needed to enhance the education of women and to improve access to antenatal care across Serbia, Kosovo, and Montenegro.

Mediation in Healthcare: Enhancing Conflict Resolution Between Patients and Physicians Beyond the Courtroom.

Healthcare is defined by rapidly advancing technologies and increased patient expectations, resulting in frequent disagreements between patients, their families, and medical practitioners. Historically, these conflicts have been settled through the adversarial court system, which frequently fails to produce equitable results due to unequal legal representation, procedural difficulties, and other shortcomings. This analysis investigates mediation, a type of Alternative Dispute Resolution (ADR), as a viable option for addressing healthcare disputes. Mediation is a voluntary, flexible, and confidential process in which a neutral third party organizes negotiations to help conflicting parties reach an agreement. Unlike litigation, mediation promotes open communication, empathy, and the preservation of relationships, which enhances patient trust and satisfaction. Furthermore, mediation resolves disputes more quickly and cost-effectively than traditional court proceedings, significantly reducing the emotional and financial burdens on all parties involved. This review examines the benefits of mediation, focusing on its role in preserving physician-patient relationships, reducing legal costs, and improving overall healthcare outcomes. The use of mediation in healthcare conflict resolution provides a more effective, compassionate, and lasting resolution that benefits healthcare institutions, practitioners, and patients.

Predicting Exploration Crew Medical Officer Training Needs: Applying Evidence-Based Predictive Analytics to Space Medicine Training.

Predictive analytics may be a useful adjunct to identify training needs for exploration class medical officers onboard deep space vehicles. This study used a preliminary version of NASA's newest medical predictive analytics tool, the Medical Extensible Database Probabilistic Risk Assessment Tool (MEDPRAT), to test the application of predictive analytics to exploration crew medical officer curriculum design for 5 distinct design reference mission (DRM) profiles. Partial and fully treated paradigms were explored. Curriculum elements were identified using a leave-one-out analysis and a threshold of 5% risk increase over the fully treated baseline. For the partial treatment scenario, among the 5 DRM profiles 4-32 curriculum elements met the 5% RRI increase. For the absolute treatment scenario, among the 5 DRM profiles, 13-126 curriculum elements met the 5% RRI increase. For the partial treatment paradigm, 13 capabilities are present in at least 3 of the 5 DRM profiles, and these elements may constitute a common baseline curriculum. This covers 41% of the skillsets needed for an ISS-like profile, 100% of a late Artemis-like profile, 41% of a Mars mission-like profile, 100% of a Starship orbital-like profile, and 68% of a Starship lunar flyby-like profile. This proof-of-concept study demonstrated that predictive analytics can rapidly generate generic and mission profile-specific exploration CMO curricula using an evidence-based process driven by optimizing mission risk reduction. This technique may serve as part of a human-machine team approach to medical curriculum planning for future space missions. It has significant potential to improve astronaut health and save time and effort for planners, trainers, and trainees.

Efficient Explainable Models for Alzheimer's Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning.

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and is the most common cause of dementia. Early diagnosis of Alzheimer's disease is critical for better management and treatment outcomes, but it remains a challenging task due to the complex nature of the disease. Clinical data, including a range of cognitive, functional, and demographic variables, play a crucial role in Alzheimer's disease classification. Also, challenges such as data imbalance and high-dimensional feature sets often hinder model performance. Objective: This paper aims to propose a computationally efficient, reliable, and transparent machine learning-based framework for the classification of Alzheimer's disease patients. This framework is interpretable and helps medical practitioners learn complex patterns in patients. Method: This study addresses these issues by employing boosting algorithms, for enhanced classification accuracy. To mitigate data imbalance, a random sampling technique is applied, ensuring a balanced representation of Alzheimer's and healthy cases. Extensive feature analysis was conducted to identify the most impactful clinical features followed by feature reduction techniques to focus on the most informative clinical features, reducing model complexity and overfitting risks. Explainable AI tools, such as SHAP, LIME, ALE, and ELI5 are integrated to provide transparency into the model's decision-making process, highlighting key features influencing the classification and allowing clinicians to understand and trust the key features driving the predictions. Results: This approach results in a robust, interpretable, and clinically relevant framework for Alzheimer's disease diagnosis. The proposed approach achieved the best accuracy of 95%, demonstrating its effectiveness and potential for reliable early diagnosis of Alzheimer's disease. Conclusions: This study demonstrates that integrating ensemble learning algorithms and explainable AI, while using a balanced dataset with feature selection, improves quantitative results and interpretability. This approach offers a promising method for early and better-informed clinical decisions.

The Role of Medical Doctors in Political Advocacy Across the Globe.

The Role of Medical Doctors in Political Advocacy Across the Globe.

A portable biosensor for simultaneous diagnosis of TNF-α and IL-1β in saliva biomarkers using twin electronic devices

Abstract. For several types of diseases, such as meningitis or oral cancers, the simultaneous diagnosis and measurement of the tumour necrosis factor α (TNF-α) and interleukin-1 β (IL-1β) immune-modulating biomarkers, with respect to both quality and quantity, are important. For example, although meningitis is generally caused by bacteria or viruses, the differences between viral and bacterial structures can be problematic for medical doctors to distinguish, as laboratory data assay techniques for the two are often similar and can overlap; moreover, in such cases, distinguishing between virial and bacterial structures is especially problematic following the use of antibiotics prior to cerebrospinal fluid testing. In this work, we simultaneously evaluated the precision of both TNF-α and IL-1β for the diagnosis of disease. In this research area, twin electrochemical biosensors have been designed as strong tools for the wide-spectrum assessment of biomarkers, thereby aiding in the screening, diagnosis, and monitoring of pathologies and treatment performance. In this research, we present a sensor platform model that can enable one to detect biomarkers quickly; specifically, this platform can be used to detect TNF-α and IL-1β in saliva. A two-peptide recognition element was created and designed using the phage display technique. This element selectively binds TNF-α and IL-1β to an electronics-based metal–oxide–semiconductor field-effect transistor/electrolyte-gated transistor (MOSFET/GT) bio-detector device and label-free biosensor, allowing for the rapid, simultaneous detection of both biomarkers. These bio-affinity recognition methods have been successfully implemented to realize the experimental twin-model sensor, based on electrolyte-gated transistor (EGT) and semiconductor field-effect transistor (ZnO-SFET) biosensors, to test for these two disease biomarkers, both individually and simultaneously, with high performance. In summary, we developed a sensor platform that can be used for rapid oral cancer signature analysis of biomarkers in multiple bio-fluids of saliva. This system works by arraying metal–oxide–semiconductor field-effect transistors (MOSFETs), with each targeting a biorecognition element (BRE) specific to one of these two important biomarkers. This system can also be extended upon to aid in a wide variety of cancer research applications.

Association Between Patient Signs and Symptoms and Critical Care Center Admissions in Prehospital Settings: A Retrospective Observational Study

Background: The system to ensure the quality of care when doctors entrust prehospital care to qualified non-doctors is called Medical Control (MC) in Japan. There have been few previous studies that have focused on prehospital care as a way to predict admission to critical care centers. Therefore, we attempted to clarify the factors in prehospital settings that predict admission to critical care centers. We believe that this will help establish an MC system,including the role of emergency medical technicians (EMTs) and doctors in selecting emergency transport destinations. Methods: This retrospective observational study included 1685 adult patients admitted through the Emergency Department (ED) of a 700-bed tertiary care facility over a 9-month period. The main predictive variables were prehospital patient factors, which were broadly categorized into vital signs, signs of shock, and respiratory symptoms. Prehospital patient factors were collected from prehospital records registered inelectronic medical records, and a multivariate logistic regression model was used to analyze the association between prehospital patient factors and admission to the critical care center. Results: A total of 1,685 patients who did not meet the exclusion criteria out of 2,353 patients transported by emergency were analyzed: 350 patients were admitted to the critical care center, 642 patients were admitted to the general ward, and 693 patients returned home. The subjects were patients who were rushed to the ED, and patient data were collected from electronic medical records and emergency transport forms. The level of consciousness, cyanosis, skin wetness or coldness at the time of contact with emergency services were significantly associated with admission to the critical care center (OR 0.92 [0.87-0.97], p = 0.001;OR 2.93 [1.75-4.92], p < 0.001; OR 3.87 [2.63-5.67], p < 0.001;OR 9.57 [5.18-18.3], p < 0.001). Conclusion: In a prehospital setting, the level of consciousness and signs of shock were suggested to be associated with admission to critical care centers.

Prediction of cyanotic and acyanotic congenital heart disease using machine learning models.

Congenital heart disease is most commonly seen in neonates and it is a major cause of pediatric illness and childhood morbidity and mortality. To identify and build the best predictive model for predicting cyanotic and acyanotic congenital heart disease in children during pregnancy and identify their potential risk factors. The data were collected from the Pediatric Cardiology Department at Chaudhry Pervaiz Elahi Institute of Cardiology Multan, Pakistan from December 2017 to October 2019. A sample of 3900 mothers whose children were diagnosed with cyanotic or acyanotic congenital heart disease was taken. Multivariate outlier detection methods were used to identify the potential outliers. Different machine learning models were compared, and the best-fitted model was selected using the area under the curve, sensitivity, and specificity of the models. Out of 3900 patients included, about 69.5% had acyanotic and 30.5% had cyanotic congenital heart disease. Males had more cases of acyanotic (53.6%) and cyanotic (54.5%) congenital heart disease as compared to females. The odds of having cyanotic was 1.28 times higher for children whose mothers used more fast food frequently during pregnancy. The artificial neural network model was selected as the best predictive model with an area under the curve of 0.9012, sensitivity of 65.76%, and specificity of 97.23%. Children having a positive family history are at very high risk of having cyanotic and acyanotic congenital heart disease. Males are more at risk and their mothers need more care, good food, and physical activity during pregnancy. The best-fitted model for predicting cyanotic and acyanotic congenital heart disease is the artificial neural network. The results obtained and the best model identified will be useful for medical practitioners and public health scientists for an informed decision-making process about the earlier diagnosis and improve the health condition of children in Pakistan.