Medical Health Research Articles

Frame-level nonverbal feature enhancement based sentiment analysis

Multimodal Sentiment Analysis (MSA) comprehensively utilizing data from multiple modalities to obtain more accurate sentiment attribute, has important applications in other fields, such as social media analysis, user experience evaluation and medical health, etc. It is worth noting that previous studies have paid little attention to the inconsistency of the initial representation granularity between verbal (textual) and nonverbal (acoustic and visual) modalities. As a result, the imbalanced emotional information between them complicates the interaction process, and ultimately affects the model’s performance. To solve this problem, this paper proposes a Frame-level Nonverbal feature Enhancement Network (FNENet) to improve performance on MSA by reducing the gap and integrating asynchronous affective information between modalities. Specifically, Vector Quantization (VQ) is applied to nonverbal modalities to reduce the granularity differences and improve the performance of the model. Additionally, nonverbal information is integrated through the Sequence Fusion mechanism (SF) into a pre-trained language model to enhance the textual representation, which benefits the word-level semantic expression according to the asynchronous affective cues preserved in unaligned frame-level nonverbal features. Extensive experiments on three benchmark datasets demonstrate that FNENet significantly outperforms baseline methods. It indicates that our model has potential application on MSA.

Oral Microbiome Dysbiosis as a Risk Factor for Stroke: A Comprehensive Review.

Stroke represents a significant global health burden, with a substantial impact on mortality, morbidity, and long-term disability. The examination of stroke biomarkers, particularly the oral microbiome, offers a promising avenue for advancing our understanding of the factors that contribute to stroke risk and for developing strategies to mitigate that risk. This review highlights the significant correlations between oral diseases, such as periodontitis and caries, and the onset of stroke. Periodontal pathogens within the oral microbiome have been identified as a contributing factor in the exacerbation of risk factors for stroke, including obesity, dyslipidemia, atherosclerosis, hypertension, and endothelial dysfunction. The alteration of the oral microbiome may contribute to these conditions, emphasizing the vital role of oral health in the prevention of cardiovascular disease. The integration of dental and medical health practices represents a promising avenue for enhancing stroke prevention efforts and improving patient outcomes.

The maternal and newborn health eCohort to track longitudinal care quality: study protocol and survey development.

The MNH eCohort was developed to fill gaps in maternal and newborn health (MNH) care quality measurement. In this paper, we describe the survey development process, recruitment strategy, data collection procedures, survey content and plans for analysis of the data generated by the study. We also compare the survey content to that of existing multi-country tools on MNH care quality. The eCohort is a longitudinal mixed-mode (in-person and phone) survey that will recruit women in health facilities at their first antenatal care (ANC) visit. Women will be followed via phone survey until 10-12 weeks postpartum. User-reported information will be complemented with data from physical health assessments at baseline and endline, extraction from MNH cards, and a brief facility survey. The final MNH eCohort instrument is centered around six key domains of high-quality health systems including competent care (content of ANC, delivery, and postnatal care for the mother and newborn), competent systems (prevention and detection, timely care, continuity, integration), user experience, health outcomes, confidence in the health system, and economic outcomes. The eCohort combines the maternal and newborn experience and, due to its longitudinal nature, will allow for quality assessment according to specific risks that evolve throughout the pregnancy and postpartum period. Detailed information on medical and obstetric history and current health status of respondents and newborns will allow us to determine whether women and newborns at risk are receiving needed care. The MNH eCohort will answer novel questions to guide health system improvements and to fill data gaps in implementing countries.

A preliminary study on the effects of long-term robot suit exercise training on gait function and quality of life in patients with spinal and bulbar muscular atrophy

Spinal and bulbar muscular atrophy (SBMA) progressively impairs gait function, resulting in the need for patients to use a wheelchair approximately 20 years after onset. No reports have investigated the effects of long-term exercise training using the Hybrid Assisted Limb (HAL) in patients with multiple SBMA. This study investigated the effects of long-term exercise training using HAL in patients with SBMA and its effects on the quality of life (QoL). Six courses of HAL treatment were administered to three males with SBMA, and leuprorelin was administered to each patient. Each course had a 4–5 week duration, during which the treatment was performed nine times, with a rest period of at least 2 months between each course. A 2-minute walk test (2MWT) and a 10-m walk test (10MWT) were performed to measure gait ability, and a blood test to measure the serum creatine kinase (CK) and creatinine (CRE) levels was performed before and after each course of treatment. We evaluated QoL using the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36).The average 2MWT distance improved over 2 years (p = 0.038), and the 10MWT showed neither improvement nor decline. No increase or decrease in serum CK or CRE levels was observed. There were no significant changes in the SF-36 physical, mental, or social summary scores.In combination with leuprorelin therapy, robot-assisted training using HAL maintained gait ability and QoL in patients with SBMA for 2 years.

A Machine Learning Approach for Prediction of Surgical Outcomes in Elective Surgery

The aim of this research was to design a Machine Learning (ML) approaches to predict surgical outcome associated with perioperative risks factors among patients undergoing elective surgery. The research employed descriptive cross-sectional survey and a sample size of 292 patients. Only adult patients undergoing elective surgery were considered. Machine Learning (ML) Algorithm such as Logistic regression, Support vector machine, k-nearest neighbors and random forest were used to provide insights into how different factors such as patient related perioperative risk, procedure related perioperative risk and health system related perioperative risk influence the likelihood of successful surgical outcome. The study found that Random Forest model achieved the highest cross validation accuracy of 100%, which means it correctly classified all data points in the test set. It implies that the random Forest model was the most suitable for classifying surgical outcome among elective surgery patient at Chuka County Referral Hospital. It had a Kappa of 1 indicating a perfect agreement between its predictions and the ground truth in comparison with other algorithms. In addition, Random Forest model achieves a perfect score (1.0) for sensitivity, precision, F1-Score, and balanced accuracy. This suggests that the model is doing extremely well at correctly classifying both positive and negative cases. Availability of main surgical supplies (health system related perioperative risk factors) had the highest score indicating that it was more important factor for the models predictions than other perioperative risk factors. In this study, the Machine Learning analysis identified unknown parameters associated with successful surgical outcome. An application of Machine Learning algorithms as a decision support tool could enable the medical health practitioners to predict the surgical outcome of patients undergoing elective surgery and consequently optimize and personalize clinical management of patient.

Evaluating the Governance Ability of Urban Public Health Using EM-AHP-TOPSIS Method: A Case Study in China.

Evaluating the governance capacity of urban public health is the key to improving the level of urban public health. We aimed to evaluate the governance ability of urban public health. An index system of governance ability of urban public health was established. The governance ability of urban public health was evaluated, and major constraints against the ability improvement were analyzed through the EM (Entropy Method)-AHP (Analytic Hierarchy Process)-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) model and data of urban agglomeration in Yangtze River Delta, China in 2023. Shanghai, Nanjing, Hangzhou, Suzhou, and Ningbo rank top 5 in terms of governance ability of public health, and they are in the first echelon. Hefei, Yancheng, Wuxi, Taizhou and Shaoxing rank 6-10, and they are in the second echelon. The remaining 17 cities are in the third echelon. Major sources of governance ability of urban public health and major factors that decrease governance ability are Medical Facility (A12), Health Improvement (A33), Medical Staff (A13), Government Ability (A11), and Health Loss (A34). For urban agglomeration in Yangtze River Delta, China, public health foundations, environmental exposure risks, public health performance, and public health emergencies all can influence the governance ability of public health. Accurate evaluation of the governance ability of urban public health can provide guidance and policy propositions to improve the governance system of public health and improve the emergency coordination ability of the government.

The importance of geographic and sociodemographic aspects in the characterization of mucopolysaccharidoses: a case series from Ceará state (Northeast Brazil).

Geographic and sociodemographic aspects may influence the natural history and epidemiology of mucopolysaccharidoses (MPS). The main objective in this work was to evaluate the clinical, molecular, and geographic profile of MPS in a population from Ceará (Northeast Brazil). For this, we have performed a descriptive cross-sectional study based on clinical evaluation, interviews with patients and/or family members, and review of medical records of 76 MPS patients. MPS II was the most common type, with the most affected individuals presenting missense pathogenic variants. Patients with MPS I proved to be the most severe clinical phenotype, presenting the first symptoms (mean: 7.1 months; SD = 4.5) and being diagnosed earlier (2.2 years; SD = 2.1) in comparison with the other types. In addition, we have shown that 13 individuals with MPS VI were born of consanguineous marriages in small, nearby cities, in a place where geographical isolation, consanguinity, and clusters of genetic diseases were previously reported. Ten of these individuals (at least, seven different families) presented a rare pathogenic variant in the ARSB gene, c.1143-8T > G in homozygosity, previously reported only among Iberian and South American patients. The results presented here provide a comprehensive picture of MPS in an important state of the Brazilian Northeast, a region that concentrates many risk factors for rare genetic diseases, such as endogamy, inbreeding, and reproductive isolation. We discuss the possible evolutionary processes and biosocial dynamics that can help to explain this finding in terms of population medical genetics and public health.

Malnutrition drives infection susceptibility and dysregulated myelopoiesis that persists after refeeding intervention.

Undernutrition is one of the largest persistent global health crises, with nearly 1 billion people facing severe food insecurity. Infectious disease represents the main underlying cause of morbidity and mortality for malnourished individuals, with infection during malnutrition representing the leading cause of childhood mortality worldwide. In the face of this complex challenge, simple refeeding protocols have remained the primary treatment strategy. Although an association between undernutrition and infection susceptibility has been appreciated for over a century, the underlying mechanisms remain poorly understood and the extent to which refeeding intervention is sufficient to reverse nutritionally acquired immunodeficiency is unclear. Here we investigate how malnutrition leads to immune dysfunction and the ability of refeeding to repair it. We find that chronic malnutrition severely impairs the ability of animals to control a sub-lethal bacterial infection. Malnourished animals exhibit blunted immune cell expansion, impaired immune function, and accelerated contraction prior to pathogen clearance. While this defect is global, we find that myelopoiesis is uniquely impacted, resulting in in reduced neutrophil and monocyte numbers prior to and post-infection. Upon refeeding, we observe that animals recover body mass, size, cellularity across all major immune organs, the capacity to undergo normal immune cell expansion in response to infection, and a restoration in T cell responses. Despite this broad improvement, refed animals remain susceptible to bacterial infection, uncoupling global lymphoid atrophy from immunodeficiency. Mechanistically, we find peripheral neutrophil and monocyte numbers fail to fully recover and refed animals are unable to undergo normal emergency myelopoiesis. Altogether, this work identifies a novel cellular link between prior nutritional state and immunocompetency, highlighting dysregulated myelopoiesis as a major driver. We believe these findings illustrate how exposure to food scarcity is an immunologic variable, even post-recovery, which should be accounted for in patient medical history and current global public health policy.

A scoping review of Deaf awareness programs in Health professional education.

Deaf awareness aims to promote understanding about Deaf and hard of hearing people, with the goal of reducing barriers between Deaf and hearing populations; and is particularly pertinent for health professional students as they need to learn to communicate effectively with a range of population groups. This scoping review aims to provide an overview of literature examining Deaf awareness programs provided to health professional students during their initial training. We searched four medical and public health databases and registers using terms related to Deaf awareness. We used the PRISMA-ScR reporting standards checklist for scoping reviews. We identified 10,198 citations, with 15 studies included in the final review. Searches were performed during August to September 2022, and April 2023. Studies were included provided they examined Deaf awareness content or programs within health professional education. Data were extracted by two independent reviewers who screened all abstracts using Rayyan software, followed by discussion to achieve knowledge synthesis and agreement. In all, a total of 15 articles from six countries were identified across health professional student disciplines including pharmacy, nursing, audiology, inter-professional and medical programs. The review found sparse evidence of research into Deaf awareness programs delivered to health professional students, with delivery often solely to small groups of students, indicating why so few students can access information about how to communicate effectively with Deaf and hard of hearing patients during their initial training programs. This scoping reviewed showed evidence of promising benefits for health professional students undertaking Deaf awareness programs during their undergraduate education. The importance of communicating with Deaf and hard of hearing patients and attaining Deaf cultural competencies for health professional students should be investigated in future research.

Prevalence of Medical Conditions and Medication Usage: Implications for Oral Health among Older Adults in Rural Victoria

(1) Background: A study was undertaken to provide a comprehensive profile of the prevalence and distribution, by selected socio-demographic characteristics, of chronic diseases and health conditions including those that impact the oral health and oral health self-care of independently living older adults in rural areas of the state of Victoria; (2) Methods: The study analyzed data from the Crossroads-II project, with a total of 1407 participants aged 55 years and older. Participants responded to questionnaires about their medical health history, health service use, and socio-demographics. In total, 572 attended a 2-h health screening that included an assessment of prescribed medications; (3) Results: Most participants were female (55.3%), with a mean age of 69.1 (SD = 9.2) years. Participants had a high prevalence of medical conditions; the most common were high blood pressure, arthritis, high lipids, hearing loss, and chronic pain. Almost all participants reported taking medications, with an average of 4.3 medications per person. Among those who attended the health screening, 78.1% were taking medications that could cause xerostomia (dry mouth); (4) Conclusions: This study provides initial information on the prevalence of medical conditions, medication usage, and the potential impact on the oral health of older adults living in rural Victoria. This information would be valuable for healthcare and dental workforce planning, policy development, and improving the overall well-being of this population.

Patient characteristics associated with frequent telehealth utilization in 2022: Evaluation of a national virtual integrated medical and behavioral health practice within the United States

ObjectivesAs permanent telehealth policies are considered in the United States (U.S.), it is important to understand who uses telehealth most often following the pandemic. We described patients who used a national virtual care practice frequently, identified how they differed from patients who used it less often, and characterized the types of care frequent telehealth patients utilized. MethodsWe used video visit data for commercially-insured patients, aged 18+, from a national virtual integrated medical and behavioral health practice in 2022 in the U.S. Patients were categorized into three groups: one visit (’minimal use’), two to four visits (’some use’), and five or more visits (’frequent use’). We compared patient and geographic characteristics between the three groups and estimated an ordinary least squares linear regression to identify predictors of ‘frequent’ use relative to ‘minimal’ or ‘some’ use. ResultsThe probability of being a frequent user declined with age (−0.4 percentage points (p.p.) per year; 95 % CI, −0.4 – −0.3), was higher for females (5.4 p.p.; 95 % CI, 4.1 – 6.7) and patients with greater clinical complexity (7.9 p.p. for highest relative to lowest quartile risk score; 95 % CI, 5.9 – 10.0), and lower for patients in the Northeast (−9.2 p.p.; 95 % CI, −15.5 – −2.9) or West (−3.2 p.p.; 95 % CI, −5.7 – −0.7) regions relative to the Southern region of the U.S. The five most common diagnoses were mental health conditions. ConclusionsOur results highlight the need for comprehensive telehealth policy that enables access, particularly for patients who rely on it as their primary source of care.

Predictors of six-month change in health-related quality of life in people with multiple sclerosis: A secondary data analysis of a randomized controlled trial

BackgroundSymptomatic treatment in people with multiple sclerosis (pwMS) requires multidisciplinary rehabilitation to alleviate disease progression and increasing health-related quality of life (HRQoL). However, the participant- and disease-specific factors that predict sustained improvement in HRQoL in pwMS undergoing inpatient rehabilitation remain unclear. Identifying these factors can help individually tailor inpatient rehabilitation programmes. Therefore, the aim of this study was to identify factors of pwMS at clinic entry for a three-week multidisciplinary inpatient rehabilitation that predict the change in physical and mental HRQoL over six months. MethodsThis is a secondary data analysis of a randomized controlled trial (NCT04356248) conducted at the Valens Rehabilitation Centre, Switzerland. HRQoL was assessed with the Medical Outcome Study 36-item Short Form Health Survey (SF-36) at clinic entry (T0; baseline) and six months after (T3; six-month follow-up). Data for 99 pwMS (mean age in years: 49.60 ± 10.17 SD, mean Expanded Disability Status Scale (EDSS) score: 4.62 ± 1.33 SD, 68.7 % female) were analysed using multiple linear regression. Outcome variables were six-month change in SF-36 Physical (ΔPCS) and Mental Component Scale (ΔMCS) scores. Predictor variables included baseline scores of PCS or MCS, fatigue, anxiety, depressive mood, cardiorespiratory fitness (V̇O2peak/kg), self-efficacy, smoking status, education level, age, EDSS, sex, time since diagnosis and MS phenotype. ResultsThe regression model with ΔPCS as outcome variable explained 18.6 % of the variance of the ΔPCS score (p = .003). Lower PCS score (p < .001) and lower depressive mood (p = .032) at baseline predicted higher ΔPCS score. The regression model with ΔMCS as outcome variable explained 26.8 % of the variance of the ΔMCS score (p < .001). Lower MCS score (p < .001) and longer time since diagnosis (p = .048) at baseline predicted higher ΔMCS score. ConclusionPwMS with lower physical HRQoL and better mood at clinic entry improved most in physical HRQoL over six months. PwMS with lower mental HRQoL and longer time since diagnosis at clinic entry improved most in mental HRQoL over six months. The results of this study contribute to the development of individualized rehabilitation programmes with the aim of maintaining and/or improving HRQoL of pwMS beyond the inpatient rehabilitation stay.

Risk factors for fasting blood glucose control in middle-aged and elderly type 2 diabetes patients.

This study aimed to investigate and analyze the medication use, fasting blood glucose control, and associated risk factors among residents with type 2 diabetes at the grassroots level in Xinjiang Production and Construction Corps. A multi-stage cluster sampling method was employed to conduct a questionnaire survey among residents aged 45 and above in battalions (communities) as the smallest unit. The medication use was recorded, and fasting blood glucose control was considered as the dependent variable. Logistic regression analysis was performed to identify the risk factors influencing fasting blood glucose control among different population characteristics. A total of 2316 participants were included in the study, of which 1072 were male (45.12%), 1418 were aged 65 and above (61.23%), 2031 were Han Chinese (87.69%), and 1551 were from the surrounding areas of Urumqi (66.97%). The main medications used among the top three classes were metformin, insulin, and α-glucosidase inhibitors. The treatment rate for type 2 diabetes was 71.80%, and the fasting blood glucose control rate was 27.98%. Multivariate analysis identified living outside the Urumqi surrounding area, age 65 and above, body mass index ≥ 24, abnormal blood lipids, and untreated hypertension as independent risk factors for poor fasting blood glucose control, while treatment was a protective factor for achieving blood glucose control. The treatment rate and fasting blood glucose control rate among grassroots residents with type 2 diabetes in Xinjiang Production and Construction Corps need improvement. Efforts should be made to enhance patient medication adherence and health management awareness through education. Targeted interventions should be implemented for high-risk populations with identified risk factors to reduce or delay the occurrence of diabetes and its complications, ultimately aiming to reduce mortality rates and improve quality of life.

Strategy to Improve Electronic Medical Certification of Cause of Death at Rumah Sakit Persahabatan, Jakarta, Indonesia

Proper death certification has broad medical and public health benefits. Therefore, death certificates should be completed accurately according to the medical certification of cause of death (MCCD) scheme. To improve the data quality of MCCD, Rumah Sakit Persahabatan (RSP) has implemented an electronic form (e-SMPK) since 2023. Although equipped with a user manual and coordination support system, incomplete and inaccurate e-SMPKs are still found. This study aims to identify interventions that can improve the quality (completeness and accuracy) of e-SMPK in RSP using one action research cycle consisting of 4 stages, i.e., diagnosing, planning, taking, and evaluating action. Qualitative data was collected through focused group discussions and field observations. Quantitative data was collected by comparing the completeness and accuracy of e-SMPKs before and after the intervention agreed upon with the participants. Triangulation of the data was carried out to maintain the credibility of the research. This study found that obstacles to e-SMPK consist of system and regulatory factors, skills, practical tools, and processes. Interventions are implemented by adjusting regulations, providing guidance and training, revising electronic forms, improving coordination, and facilitating consultation and verification to overcome obstacles. An increase in the completeness and accuracy of filling in the e-SMPK elements was obtained, most of which were statistically significant.

Characterizing the Adoption and Experiences of Users of Artificial Intelligence-Generated Health Information in the United States: Cross-Sectional Questionnaire Study.

OpenAI's ChatGPT is a source of advanced online health information (OHI) that may be integrated into individuals' health information-seeking routines. However, concerns have been raised about its factual accuracy and impact on health outcomes. To forecast implications for medical practice and public health, more information is needed on who uses the tool, how often, and for what. This study aims to characterize the reasons for and types of ChatGPT OHI use and describe the users most likely to engage with the platform. In this cross-sectional survey, patients received invitations to participate via the ResearchMatch platform, a nonprofit affiliate of the National Institutes of Health. A web-based survey measured demographic characteristics, use of ChatGPT and other sources of OHI, experience characterization, and resultant health behaviors. Descriptive statistics were used to summarize the data. Both 2-tailed t tests and Pearson chi-square tests were used to compare users of ChatGPT OHI to nonusers. Of 2406 respondents, 21.5% (n=517) respondents reported using ChatGPT for OHI. ChatGPT users were younger than nonusers (32.8 vs 39.1 years, P<.001) with lower advanced degree attainment (BA or higher; 49.9% vs 67%, P<.001) and greater use of transient health care (ED and urgent care; P<.001). ChatGPT users were more avid consumers of general non-ChatGPT OHI (percentage of weekly or greater OHI seeking frequency in past 6 months, 28.2% vs 22.8%, P<.001). Around 39.3% (n=206) respondents endorsed using the platform for OHI 2-3 times weekly or more, and most sought the tool to determine if a consultation was required (47.4%, n=245) or to explore alternative treatment (46.2%, n=239). Use characterization was favorable as many believed ChatGPT to be just as or more useful than other OHIs (87.7%, n=429) and their doctor (81%, n=407). About one-third of respondents requested a referral (35.6%, n=184) or changed medications (31%, n=160) based on the information received from ChatGPT. As many users reported skepticism regarding the ChatGPT output (67.9%, n=336), most turned to their physicians (67.5%, n=349). This study underscores the significant role of AI-generated OHI in shaping health-seeking behaviors and the potential evolution of patient-provider interactions. Given the proclivity of these users to enact health behavior changes based on AI-generated content, there is an opportunity for physicians to guide ChatGPT OHI users on an informed and examined use of the technology.

Kebijakan Pemerintah Daerah Bali dalam Mewujudkan Penyelenggaraan Pelayanan Kesehatan Tradisional Integrasi

Progress and changing ages have an impact on changes in various areas of life, one of which is health. A variety of cutting-edge discoveries related to medical methods and medicines led to advances in both conventional and traditional health care. This development has led to various policies made by countries including Indonesia. Indonesia sheds health-related policy as a constitutional right of the people as set forth in the rules of enforcement. The guarantee of good health care gives the public the right to use the kind of medical or traditional health care. There are three types of traditional health care within the rules of enforcement: empirical, complementary, and integrated. This paper highlights the integration of traditional health services which, based on the authority of the Indonesian Government Regulations, mandate local governments to make regional policies that are in line with national policies. This writing uses normative methods with a legislative and conceptual approach. The results showed that the policy of the regional government of Bali in the maintenance of traditional health services integration implemented by issuing the regulation of the governor of Bali No. 55 Year 2019 on the traditional health service of Bali which provides guarantees on the implementation of health services traditional integration of bali as a collaboration carried out between the traditional complementary health services with conventional health services in health services facilities such as Puskesmas and hospitals. Progress and changes of the era have an impact on related types of traditional health services the integration given in its organization is established on the basis of the Decision of the Governor of Bali of the results of the analysis of the study team which is further established by the respective heads of the health service facilities.

Automated Multi-Class Facial Syndrome Classification Using Transfer Learning Techniques.

Genetic disorders affect over 6% of the global population and pose substantial obstacles to healthcare systems. Early identification of these rare facial genetic disorders is essential for managing related medical complexities and health issues. Many people consider the existing screening techniques inadequate, often leading to a diagnosis several years after birth. This study evaluated the efficacy of deep learning-based classifier models for accurately recognizing dysmorphic characteristics using facial photos. This study proposes a multi-class facial syndrome classification framework that encompasses a unique combination of diseases not previously examined together. The study focused on distinguishing between individuals with four specific genetic disorders (Down syndrome, Noonan syndrome, Turner syndrome, and Williams syndrome) and healthy controls. We investigated how well fine-tuning a few well-known convolutional neural network (CNN)-based pre-trained models-including VGG16, ResNet-50, ResNet152, and VGG-Face-worked for the multi-class facial syndrome classification task. We obtained the most encouraging results by adjusting the VGG-Face model. The proposed fine-tuned VGG-Face model not only demonstrated the best performance in this study, but it also performed better than other state-of-the-art pre-trained CNN models for the multi-class facial syndrome classification task. The fine-tuned model achieved both accuracy and an F1-Score of 90%, indicating significant progress in accurately detecting the specified genetic disorders.

A Wearable Electrochemical Sensor Based on a Molecularly Imprinted Polymer Integrated with a Copper Benzene-1,3,5-Tricarboxylate Metal-Organic Framework for the On-Body Monitoring of Cortisol in Sweat.

Owing to their potential to transform traditional medical diagnostics and health monitoring, wearable biosensors have become an alternative evolutionary technology in the field of medical care. However, it is still necessary to overcome some key technique challenges, such as the selectivity, sensitivity, and stability of biometric identification. Herein, a novel, wearable electrochemical sensor based on a molecularly imprinted polymer (MIP) integrated with a copper benzene-1,3,5-tricarboxylate metal-organic framework (MOF) was designed for the detection of stress through the on-body monitoring of cortisol in sweat. The MOF was used as the substrate for MIP deposition to enhance the stability and sensitivity of the sensor. The sensor consisted of two layers, with a microfluidic layer as the top layer for spontaneous sweating and a modified electrode as the bottom layer for sensing. The sensor measured cortisol levels by detecting the current change that occurred when the target molecules bound to the imprinted cavities, using Prussian blue nanoparticles embedded in the MIP framework as the REDOX probe. The proposed sensor exhibited a linear detection range of 0.01-1000 nM with a detection limit of 0.0027 nM, and favorable specificity over other analogies. This facile anti-body free sensor showed excellent stability, and can be successfully applied for in situ cortisol monitoring.

Determining Deviation of the Growth Pattern of Preterm Infants and Its Causes According to the Fenton Growth Chart: A Longitudinal Follow-up Study

Background: Birth weight is a crucial indicator of infant health. In Iran, child growth monitoring for children under six years old is integrated into the healthcare system. However, existing growth charts have limitations in accurately representing preterm infants. Objectives: This study was conducted to determine the frequency of postnatal growth retardation and its causes in preterm infants from hospitalization to six months after birth. Methods: After informing parents, we recruited 255 preterm singleton infants born at the Afzalipour Medical Education and Health Center in Kerman, Iran, over one year. The Fenton growth chart was used to compare the anthropometric characteristics of the infants at birth, and at ages 7, 14, and 28 days, and then monthly up to 6 months. A special questionnaire also recorded the type of feeding, length of hospital stay, use of mechanical ventilation and oxygen, duration of total parenteral nutrition (TPN), and associated causes and complications. Results: The mean Z-score weights at birth, discharge, one month, three months, and six months were -0.34, -1.19, -0.85, -0.94, and -1.79, respectively. The mean Z-score heights at birth, discharge, one month, three months, and six months were 0.74, 0.20, -0.07, -0.79, and -2.5, respectively. Additionally, the mean Z-scores for head circumference at birth, discharge, one month, and three months were 0.41, -0.19, -0.53, and -1.17, respectively. Deviation from the Fenton preterm growth chart was detected in 109 infants (42.7%) at the time of discharge, 79 infants (31%) at one month, 82 infants (32.2%) at three months, and 134 infants (52.5%) at six months of age. Conclusions: The weight at discharge and the length of NPO [due to surgical problems, feeding intolerance, necrotizing enterocolitis (NEC), etc.] were significantly inversely related. Preterm infants grow more slowly in hospitals, so their longitudinal growth data should be interpreted carefully. The incidence of postnatal growth failure can be reduced by improving NICU quality, optimizing nutrition, and increasing enteral feeding rates.

Transforaminal lumbar endoscopic discectomy: should we abandon it for L5-S1 foraminal and extraforaminal lumbar disc herniations? A prospective non-randomised study and literature review

Purpose The aim of this study is to investigate the clinical outcomes of transforaminal lumbar endoscopic discectomy (TLED) in patients with L5-S1 lumbar disc herniation (LDH). Materials and methods Seventy-five consecutive individuals with diagnosed foraminal/extraforaminal L5-S1 LDH were included in this study. All patients underwent TLED, being subsequently evaluated in a 2-year follow-up period. Assessment was performed preoperatively and at 6 weeks and 3, 6, 12 and 24 months postoperatively. Visual Analogue Scale (distinctly applied for lower limb – VAS-LP and low back – VAS-BP pain) and Short-Form 36 (SF-36) Medical Health Survey Questionnaire were implemented to assess pain and health-related quality of life (HRQoL) of enrolled individuals, respectively. Results No major perioperative complications were observed. Recorded values of all studied indices were demonstrated to feature a clinically and statistically significant amelioration at 6 weeks, presenting lesser improvement at 3 months with subsequent stabilisation. VAS-LP and VAS-BP values were displayed to reach a plateau in 6 months postoperatively, whereas all parameters of SF-36 continued to present a statistically significant improvement until the end of follow-up at 2 years. Conclusions TLED represent a safe and efficient technique in terms of diminishing perceived pain and improving HRQoL in patients with L5-S1 LDHs. However, specific patient- and technique-related circumstances on the ground of low surgical experience may limit its effectiveness in these patients.