Health Status Of Patients Research Articles

Oral health of chemotherapy patients before and after provision of oral hygiene instructions at a tertiary care hospital: pre-post design

ObjectiveDisturbances in the oral mucosa is a major concern among patients undergoing chemotherapy. One of the most significant barriers in the implementation of oral care is the lack of knowledge. The aim of the study was to assess gingival and periodontal health status of chemotherapy patients before and after the provision of oral hygiene instructions.MethodsA single group, pre-post test was conducted to assess oral health status of patients at the daycare chemotherapy, Aga Khan University Hospital, Karachi, Pakistan. Oral hygiene instructions were given with study models and leaflets. Patients were followed for 6-weeks. Oral health was assessed by using Simplified-Oral Hygiene Index (OHI-S) and Community Periodontal Index (CPI). Differences in indices were analyzed in STATA version-15.0 using Generalized Estimating Equation (GEE) and Wilcoxon Signed-rank test.ResultsOut of 74, 53 (72%) patients completed study follow-up. Improvement in the OHI-S was found in 14 (26%) patients (p-value < 0.001). GEE showed that age [adjusted OR = 1.10; 95% CI: 1.03–1.11], current chemotherapy cycle [adjusted OR = 1.19; 95% CI: 0.98–1.46], highest education level [Adjusted OR = 1.37; 95% CI: 1.08–12.7] and cancer therapy [Adjusted OR = 0.12; 95% CI: 0.24–0.55] were significantly associated with the change in OHI-S. Wilcoxon signed-rank test showed positive changes in the CPI (p-value < 0.001).ConclusionsBasic oral hygiene instructional intervention can be effective in improving the oral hygiene of chemotherapy patients. Nurses should also play a key role in providing psychological and nutritional support to patients.

Standardization use of the international classification of functioning, disability and health in the determination of health status in patients with post-acute COVID-19 syndrome

Purpose To propose a standardized method for the use of the International Classification of Functioning, Disability and Health (ICF) to describe the health status in Post-Acute COVID-19 Syndrome (PACS) and investigate interrater agreement in the linking process in instruments and clinical exams using the ICF categories. Materials and Methods Cross-sectional and interrater agreement study that followed the Guidelines for Reporting Reliability and Agreement Studies. Two raters performed the linking coding process in instruments of quality of life, anxiety and depression, fatigue and pulmonary function, inspiratory muscle strength and cardiopulmonary exercise testing. The codes were qualified by standards defined to each instrument and exams. Results The instrument with the lowest Cohen’s Kappa coefficient was anxiety and depression (k = 0.57). Forty ICF codes were linked to clinical instruments and exams. The fatigue instrument presented a higher degree of disability by the qualification process, from severe to complete, in the linked codes. Conclusion The study presents a standardized method for the assessment of the health status of patients with PACS through ICF. Restriction in work performance, socialization and family relationships as well as disabilities in physical endurance, fatigue and exercise tolerance were found in the sample. The agreement between the raters was moderate to perfect, demonstrating that the method can be reproducible.

Noncontact Sensors for Vital Signs Measurement: A Narrative Review.

Vital signs are crucial for monitoring changes in patient health status. This review compared the performance of noncontact sensors with traditional methods for measuring vital signs and investigated the clinical feasibility of noncontact sensors for medical use. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE) database for articles published through September 30, 2023, and used the key search terms "vital sign," "monitoring," and "sensor" to identify relevant articles. We included studies that measured vital signs using traditional methods and noncontact sensors and excluded articles not written in English, case reports, reviews, and conference presentations. In total, 129 studies were identified, and eligible articles were selected based on their titles, abstracts, and full texts. Three articles were finally included in the review, and the types of noncontact sensors used in each selected study were an impulse radio ultrawideband radar, a microbend fiber-optic sensor, and a mat-type air pressure sensor. Participants included neonates in the neonatal intensive care unit, patients with sleep apnea, and patients with coronavirus disease. Their heart rate, respiratory rate, blood pressure, body temperature, and arterial oxygen saturation were measured. Studies have demonstrated that the performance of noncontact sensors is comparable to that of traditional methods of vital signs measurement. Noncontact sensors have the potential to alleviate concerns related to skin disorders associated with traditional skin-contact vital signs measurement methods, reduce the workload for healthcare providers, and enhance patient comfort. This article reviews the medical use of noncontact sensors for measuring vital signs and aimed to determine their potential clinical applicability.

Abdominal aortic calcification among gastroenterological and transplant surgery

AbstractThis review discusses the increasing global trend towards an aging population, which has resulted in a growing number of surgeries being performed on elderly patients, particularly those living with cancer. The focus was on the implications of abdominal aortic calcification (AAC), an indicator of systemic atherosclerosis, in these patients. This comprehensive review provided evidence detailing the complex processes of atherosclerosis and vascular calcification and various approaches to assess this condition. The prevalence of AAC is related to multiple factors, including cardiovascular disease, inflammation, frailty in various types of gastroenterological surgery. Additionally, notable links were found between AAC, postoperative complications, and patient survival following gastroenterological surgery. This study highlights how AAC could negatively impact the health status of elderly patients and undermine treatment efficacy, stressing the need for more research in this domain to improve patient outcomes.

Quality of life and mental health status of glaucoma patients.

Glaucoma, a leading cause of irreversible blindness worldwide, poses significant challenges to patients' quality of life (QOL) and mental well-being. This study aimed to investigate the complex interplay between clinical, demographic, and psychological factors and their impact on QOL among patients diagnosed with glaucoma. A cohort of 201 glaucoma patients, with a mean age of 70 years, participated in the study. Descriptive analyses revealed that participants reported living with a glaucoma diagnosis for an average of 13.38 years, highlighting the chronic nature of the disease in the cohort. Comorbidity was shown to be in close relationship with QOL, where with additional health problems have lower QOL scores (M = 34.86, SD = 18.25), as well as higher levels of anxiety (M = 10.64, SD = 5.38) and depression (M = 13.42, SD = 7.37). Correlation analyses further unveiled robust associations between clinical characteristics and psychological outcomes, with lower visual acuity strongly correlated with reduced QOL (rR = -0.74, pR < 0.001; rL = -0.78, pL < 0.001) and higher levels of anxiety and depression. Additionally, longer duration of glaucoma diagnosis was moderately associated with poorer QOL (r = 0.56, p < 0.001) and increased psychological distress, highlighting the cumulative burden of living with the disease over time. Mediation analyses indicated that duration of diagnosis partially mediated the relationship between depression and QOL, as well as anxiety and QOL, suggesting that the prolonged experience of living with glaucoma may exacerbate the impact of psychological distress on QOL. These findings underscore the importance of holistic patient care approaches that address both the physical and psychological aspects of glaucoma to improve patient outcomes and enhance overall well-being.

Sarcopenia diagnosis in patients with colorectal cancer: a review of computed tomography-based assessments and emerging ways to enhance practicality.

Traditionally, cancer treatment has focused on the stages of the disease; however, recent studies have highlighted the importance of considering the overall health status of patients in the prognosis of cancer. Loss of skeletal muscle, known as sarcopenia, has been found to significantly affect outcomes in many different types of cancers, including colorectal cancer. In this review, we discuss the guidelines for diagnosing sarcopenia, with a specific focus on CT-based assessments. Many groups worldwide, including those in Europe and Asia, have introduced their own diagnostic guidelines for sarcopenia. Seemingly similar yet subtle discrepancies, particularly in the cutoff values used, limit the use of these guidelines in the general population, warranting a more universal guideline. Although CT-based measurements, such as skeletal muscle index and radiodensity, have shown promise in predicting outcomes, the lack of standardized values in these measurements hinders their universal adoption. To overcome these limitations, innovative approaches are being developed to assess changes in muscle mass trajectories and introduce new indices, such as skeletal and appendicular muscle gauges. Additionally, machine learning models have shown superior performance in predicting sarcopenic status, providing an alternative to CT-based diagnosis, particularly after surgery. CT has tremendous benefits and a significant role in visually as well as quantitatively retrieving information on patient body composition. In order to compensate for the limitation of standard cutoff value, 3-dimensional analysis of the CT, artificial intelligence-based body composition analysis, as well as machine learning algorithms for data interpretation and analysis have been proposed and are being utilized. In conclusion, despite the varying definitions of sarcopenia, CT-based measurements coupled with machine-learning models are promising for evaluating patients with cancer. Standardization efforts can improve diagnostic accuracy, reduce the reliance on CT examinations, and make sarcopenia assessments more accessible in clinical settings.

The Relationship Between Patient-Reported Outcome Measures (PROMs) in Patients Undergoing Hip and Knee Joint Replacement Surgery and Social Deprivation on the Wirral.

This study aimed to investigate the associa-tion between patient-reported outcome measures (PROMs), both pre- and post-operatively, and socio-economic deprivation among patients undergoing hip and knee replacement surgeries in the diverse socioeconomic region of Wirral. A retrospective cohort study was conducted, involving 1666 adult patients who underwent hip or knee replacement procedures between 2012 and 2019. Socioeconomic deprivation was assessed using the Index of Multiple Deprivation (IMD). Pre- and post-operative outcomes were measured using the Oxford Hip and Knee scores. The mean scores for both pre-and post-operative assessments (Q1 and Q2) exhibited a strong positive correlation with PROM scores, regardless of gender, across both hip and knee replacements. However, the mean difference in scores between Q1 and Q2 showed no significant correlation with the IMD decile. Notably, patients residing in areas of higher socioeconomic deprivation demonstrated lower PROMs both before and after the surgery. The Oxford Hip and Knee scores are widely employed for evaluating health status in patients. In our study, these scores were influenced by IMD decile, supporting the holistic assessment approach employed by the treating unit, which does not rely solely on PROM scores as a trigger for arthroplasty discussions. Furthermore, our findings align with the practice of NHS Digital, which publishes PROM scores based on changes in PROM scores pre- and post-operation rather than absolute PROM scores. This approach appears to be less influenced by deprivation in the catchment area, as the improvement or change in scores was poorly correlated with socioeconomic factors.

Development and validation of a novel web application for patient-reported outcome measures monitoring.

e23173 Background: Patient Reported Outcome Measures (PROM) and its role in managing cancer treatment associated symptoms can not only improve the quality of life but also often prevent complication related mortality. PROM can be defined as a self-reported status of a patient's health condition without physician interpretation. One key limitation of using an app based PROM monitoring is a digital divide, (unequal distribution and knowledge regarding modern information and communication technology). Integrating PROM with technology allows for an efficient and effective method to communicate disease management. Methods: We developed a web application called Meeval consisting of two tools - PROM monitoring and medication reconciliation. Patients are able to track the severity of their symptoms on a ten point likert scale and add the medication details to their profile. We conducted a pilot study of patients with cancer who were handed a pamphlet, invited to download the app and assess its usability. We aimed to find the proportion of patients who would download and use the app following a simple introduction by the doctor using a pamphlet. We postulated that greater than fifty percent of downloads would happen, thereby negating a possible digital divide when it comes to app based PROM monitoring. Results: We recruited 95 patients with cancer. It was determined that 60% of the study population had downloaded the app without much prompt. Of this population of users, it was found that 36.8% downloaded after a seven day follow up call and 63.2% required no follow up call for app installation. When looking at app usage it was found that 53.1% of patients are tracking symptoms, 15.6% are tracking medications and 31.3% are tracking both symptoms and medication. Conclusions: The Meeval application allows for a ‘Measure, Track and Respond’ model to be implemented in a clinical setting and further enforce patient-centric healthcare. Furthermore, this app allows for seamless interaction between the patient and the physician. Patients who log their symptoms daily allow for the physician to have a more comprehensive understanding of the disease profile and any adverse effects associated with the treatment plan. Patient Reported Outcome Measures can significantly improve the quality of life and prevent any medical oversight. Through PROM tools, early detection and intervention is possible. The goal of the novel Meeval application is to improve both patient and physician experience when it comes to a chronic diagnosis and disease management. We found that the Meeval application will bridge the digital divide and provide a platform for wider use in the field of oncology.

Edge Server Deployment for Health Monitoring With Reinforcement Learning in Internet of Medical Things

The Internet of Medical Things (IoMT) has recently gained a lot of interest in the health care industry. IoMT enables real-time and omnipresent monitoring of a patient's health status, resulting in massive amounts of medical data being generated. The centralized massive data processing places enormous strain on the typical cloud computing, rendering it incapable of supporting a variety of real-time health care applications. Therefore, edge computing that moves application programs and data processing from central infrastructure to the edge nodes has attracted wide attention. However, adopting existing edge server (ES) deployment strategies for IoMT is not suitable due to the decentralized and high real-time service requirements of IoMT systems. In particular, traditional ES deployment strategies in IoMT system confront major load imbalance across ESs, latency issues, and energy consumption concerns. To address these challenges, a deployment strategy of ESs based on the state-action-reward-state-action (SARSA) learning, named ESL, is designed. Specifically, ESs are quantified by evaluating the silhouette coefficient (SC) and the sum of squared errors. Then, through fuzzy C-means (FCM) algorithm, the preliminary division of health monitoring units (HMUs) and the initial locations of ESs are obtained. Finally, SARSA learning is adopted to determine the deployment of ESs. Furthermore, extensive experiments and analyses confirm that ESL achieves the core objective of optimizing load balancing among ESs while also optimizing request-response latency and request processing energy consumption.

Association of bioimpedance analysis parameters trajectories with clinical outcomes in neurocritical patients

Background and objectiveNeurocritical patients often experience uncontrolled high catabolic metabolism state during the acuta phase of the disease. The complex interactions of neuroendocrine, inflammation, and immune system lead to massive protein breakdown and changes in body composition. Bioelectrical impedance analysis (BIA) evaluates the content and proportions of body components based on the principles of bioelectricity. Its parameters reflect the overall health status of the body and the integrity of cellular structure and function, playing an important role in assessing the disease status and predicting prognosis of such patients. This study explored the association of BIA parameters trajectories with clinical outcomes in neurocritical patients. MethodsThis study prospectively collected BIA parameters of 127 neurocritical patients in the Department of Neurology admitted to the NICU for the first 1–7 days. All these patients were adults (≥18 years old) experiencing their first onset of illness and were in the acute phase of the disease. The group-based trajectory modeling (GBTM), which aims to identify individuals following similar developmental trajectories, was used to identify potential subgroups of individuals based on BIA parameters. The short-term prognosis of patients in each trajectory group with variations in phase angle (PA) and extracellular water/total body water (ECW/TBW) over time was differentially analyzed, and the logistic regression model was used to analyze the relationship between potential trajectory groups of PA and ECW/TBW and the short-term prognosis of neurocritical patients. The outcome was Glasgow Outcome Scale (GOS) score at discharge. ResultsFour PA trajectories and four ECW/TBW trajectories were detected respectively in neurocritical patients. Among them, compared with the other latent subgroups, the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup” had higher incidences of adverse outcomes at discharge (GOS:1–3), in-hospital mortality, and length of neurology intensive care unit stay (all P < 0.05). After correcting for potential confounders, compared with the “Low PA rapidly decreasing subgroup”, the risk of adverse outcome (GOS:1–3) was lower in the other three PA trajectories, with OR values of 0.0003, 0.0004, and 0.003 respectively (all P < 0.05). Compared with the “High ECW/TBW slowly rising subgroup”, the risk of adverse outcome (GOS:1–3) was lower in the other three ECW/TBW trajectories, with OR values of 0.013, 0.035 and 0.038 respectively (all P < 0.05). ConclusionLatent PA trajectories and latent ECW/TBW trajectories during 1–7 days after admission were associated with the clinical outcomes of neurocritical patients. The risk of adverse outcomes was highest in the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup”. These results reflected the overall health status and nutritional condition of neurocritical patients at the onset of the disease, and demonstrated the dynamic change process in body composition caused by the inflammatory response during the acute phase of the disease. This provided a reference basis for the observation and prognostic evaluation of such patients.

Clinical and financial burden of mental health (MH) conditions in patients (pts) with low-grade non-Hodgkin lymphoma (LG-NHL).

7072 Background: LG-NHL is mostly incurable, imposing a prolong impact of cancer care burden for pts. This study aimed to quantify the burden of MH conditions in pts with newly diagnosed chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), follicular lymphoma (FL), mantle cell lymphoma (MCL), Waldenström macroglobulinemia (WM), or marginal cell lymphoma (MZL). Methods: A retrospective study was conducted using Optum Clinformatics Data Mart to identify pts ≥18 years with ≥1 new diagnosis for CLL, FL, MCL, WM, or MZL from 6/2016-6/2022 (index period). Pts were required to be continuously enrolled for 60 days pre- and 365 days post-index date, defined as the date of first cancer diagnosis. Incidence and prevalence of MH conditions of interest (anxiety, depression, stress reaction/adjustment disorder, insomnia, post-traumatic stress disorder [PTSD]) were categorized based on if diagnoses were post- or pre-index date. All-cause healthcare resource utilization (HCRU) and costs were measured during the 1-yr follow-up period. Results: Approximately half of newly diagnosed 36,054 LG-NHL pts (CLL/SLL=48.0%; FL=52.7%; MCL=57.2%; WM=50.5%; MZL=52.5%) had either an incident (19.4-25.7%) or prevalent (28.6-32.1%) MH condition diagnosis following their cancer diagnosis (Table). There were no significant demographic differences in pts with and without MH conditions. LG-NHL pts suffered most from anxiety (30.9-38.2%) and depression (27.5-31.9%), followed by insomnia (16-23.1%), stress (10.3-13.5%), and PTSD (1.4-1.9%). Median time from cancer diagnosis to onset of a MH condition was 334 days for CLL/SLL, 301 for FL, 248 for MCL, 351 for WM, and 328 for MZL. LG-NHL pts with an identifiable MH diagnosis had significantly higher costs and HCRU compared to those without; for example, in CLL/SLL pts with MH diagnosis, outpatient visits were 1.4 times higher, inpatient admissions 3.0 times higher, and costs 2.1 times higher than those without (all P=0.0001). HCRU and cost increases were also observed in MCL, FL, WM, and MZL pts with MH diagnosis. Conclusions: This real-world study uncovered a high proportion of LG-NHL patients suffer from MH conditions, incurring higher financial burden than those without. With advancements in new treatments, there remains unmet need of MH burden in these pts. [Table: see text]

Effective Oral Indicators With Medical and Dental Collaboration in Open Heart Surgery: A Representative Survey.

Purpose Postoperative infections pose an important problem for patients with cardiac disease. Moreover, oral health status is associated with the risk of longer hospital stays. Therefore, the oral health status of patients was assessed before open-heart surgery. This study aimed to determine the relationship between oral health status and postoperative status. Methods The study included 25 patients who underwent open-heart surgery at our university hospital in 2020. Upon admission, dentists conducted an oral examination and assessed the oral health status of the patients, also using the Japanese version of the Oral Health Assessment Tool (OHAT-J), Revised Oral Assessment Guide (ROAG), oral moisture level, oral bacteria, and other relevant factors. The study investigated the association with postoperative status. Findings Significant postoperative infections were found in patients aged ≥70 years, with an OHAT-J score of ≥5, OHAT-J lip score of ≥1, Streptococcus γ count of 1.0 × 10^6 or higher (CFU/mL), and increased Streptococcus γ before and after surgery. The duration of hospitalization correlated with the OHAT-J, OHAT-J gum and tissue, and ROAG scores. The duration of intensive care unit (ICU) stays correlated with the OHAT-J score. Conclusions The study demonstrates that OHAT-J scores are linked with predicting not just postoperative infection but also the length of hospitalization and ICU stay. As OHAT-J scores do not necessitate specialized dental instruments, they are straightforward and beneficial for healthcare professionals outside of dentistry.

Biochemical assessment in a cohort of pediatric patients with cystic fibrosis.

Cystic fibrosis (CF) is a recessive inherited disorder caused by genetic mutations in the CF transmembrane conductance regulator (CFTR) gene. It is a multisystem condition that primarily induces abnormal mucus accumulation in the respiratory system and obstructs the intrapancreatic common bile duct, causing a reduction in the delivery of digestive enzymes to the small intestine. Thus, patients with CF are characterized by maldigestion, malabsorption, and recurrent airway bacterial infections. Clinical monitoring of the health status of patients with CF is mandatory for increasing the patients' lifespan. To assess the feasibility of monitoring life quality (LQ) in pediatric patients with cystic fibrosis (CF) and to explore the relationship between biochemical parameters and clinical symptoms, our study analyzed inflammatory responses related to CF, medication, and pulmonary bacterial infections in 52 patients diagnosed with CF. Blood, hypo-pharyngeal exudate, and fecal samples were analyzed using clinical biochemistry, hematology, and microbiology techniques at the Alessandrescu-Rusescu National Institute for Mother and Child Health central laboratory in Bucharest, Romania. All the participants adhered to their prescribed outpatient CF regimens and appeared clinically stable. The overall clinical status of patients with CF was observed and compared with that of a healthy control group, which consisted of individuals similar in number and age. The screened patients with CF presented an impaired lipid status and chronic infections with various bacteria, iron, and vitamin (A, D, and E) deficiencies. Our findings provide insights into the pathophysiological mechanisms of CF and suggest that tailored monitoring and personalized therapeutic strategies could improve patient management.

Machine Learning-Based Cardiovascular Disease Detection and Intelligent Healthcare Workflow Automation

Cardiovascular diseases (CVDs) are a major cause of death worldwide, emphasizing the importance of better early detection methods. This study introduces a machine learning model to detect CVDs by analyzing vital sign information. The model, which was trained using a cardiovascular dataset, utilizes three algorithms: Support Vector Machine (SVM), Naïve Bayes, and Decision Tree. It assesses the health status of patients by predicting vital sign values, allowing healthcare providers to receive timely alerts. Following the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, a proof-of-concept web application was created with object-oriented design principles and implemented using Python. This application predicts the likelihood of CVD and streamlines the scheduling of doctor appointments, promoting quick medical intervention. Our findings reveal that the Decision Tree classifier performed the best in accurately identifying patients who are at risk based on abnormalities in vital signs. This method can potentially enhance early detection of CVDs and improve the timing of medical care.

Optimization of resources in intelligent electronic health systems based on internet of things to predict heart diseases via artificial neural network

As a paradigm shift in tandem with the expansion of ICT, smart electronic health systems hold great promise for enhancing healthcare delivery and illness prevention efforts. These systems acquire an in-depth understanding of patient health states through the real-time collection and analysis of medical data enabled by the Internet of Things (IoT) and machine learning. With the widespread use of cutting-edge artificial intelligence and machine learning techniques, predictive analytics in medicine can assist in making the shift from a reactive to a proactive healthcare strategy. With the ability to rapidly and precisely evaluate massive amounts of data, draw intelligent conclusions, and solve difficult issues, artificial neural networks could revolutionize several industries. Two cardiac illnesses were assessed in this study using a multilayer perceptron artificial neural network that incorporated a genetic algorithm and an error-back propagation mechanism. The ability of artificial neural networks to handle consecutive time series data is crucial for optimizing resources in smart electronic health systems, especially with the increasing volume of patient information and the broad use of electronic clinical records. This requires the creation of more accurate predictive models. Through the use of Internet of Things (IoT) sensors, the proposed system gathers data, which is then used to do predictive analytics on patient history-related electronic clinical data saved in the cloud. A smart healthcare system that uses Mu-LTM (multidirectional long-term memory) to accurately monitor and predict the risk of heart disease has a coverage error of 97.94 %, an accuracy of 97.89 %, a sensitivity of 97.96 %, and a specificity of 97.99 %. In comparison to other smart heart disease prediction systems, the F1-score of 97.95 % and precision of 97.71 % is very good.

Knowledge on oral health and periodontal status among type II diabetes mellitus (DM) patients in Libya

Diabetes mellitus (DM) is one of the common diseases in the world. Its dramatic increase annually is considered a global issue to the people, in which raising awareness about the disease and its complication is crucial. It has been well documented by the literature that smoking and DM are two major risk factors for periodontal disease. Knowledge of oral health is vital for type II DM patients and is a key factor in the treatment and prevention of periodontal disease. A cross-sectional study was conducted among three hundred diabetic patients in a Benghazi diabetic treatment center. The participants were 40.3% (n = 121) male and 59.7% (n = 179) female adults whose ages ranged from 16 to 80 years. Inclusion criteria included Libyan citizens diagnosed with type II DM. The participants were questioned through a structured questionnaire and followed by the examination of their oral status. Periodontal examination was performed by two periodontists using the following indices: plaque index (PI) and periodontal disease index (PDI). Knowledge about oral health and periodontal status for Libyan patients with type II DM was tested through eight core questions using a structured questionnaire. The results showed about half of the sample had poor knowledge regarding the condition and its detrimental effect on oral and general health. Only 31% of participants provided good knowledge about type II DM and its relationship to oral health and periodontal status. The P-value showed a significant relationship between the knowledge and PI and PDI indices. Participants with poor knowledge showed higher scores in both indices. A significant relation was found between PI, PDI and knowledge. As knowledge was fair, the lower the PI and PDI scores. To lessen diabetic complications and their deleterious effects on oral and general health, raising knowledge and awareness could be a solution. Multidisciplinary cooperation between the medical and dental staff could be implemented to increase public knowledge. Key words: Oral health, Periodontal, Patients, Diabetes mellitus, Libya, Health awareness, Dentistry

Together or Apart? Revealing the Impact of Dietary Interventions on Bioavailability of Quinolones: A Systematic Review with Meta-analyses.

Managing drug-food interactions is essential for optimizing the effectiveness and safety profile of quinolones. Following PRISMA guidelines, we systematically reviewed the influence of dietary interventions on the bioavailability of 22 quinolones. All studies describing or investigating the impact of food, beverages, antacids, and mineral supplements on pharmacokinetic parameters or pharmacokinetic/pharmacodynamic indices of orally taken quinolones were considered for inclusion. We excluded reviews, in vitro and in silico studies, studies performed on animals, and those involving alcohol. We performed the search in Medline (via PubMed), Embase, and Cochrane Library, covering reports from database inception to December 2022. We used the following tools to assess the risk of bias: version 2 of the Cochrane risk-of-bias tool for parallel trials, the Cochrane risk-of-bias tool for cross-over studies, and the NIH quality assessment tool for before-after studies. We performed quantitative analyses for each quinolone if two or more food-effect studies with specified and comparable study designs were available. If meta-analyses were not applicable, we qualitatively summarized the results. We included 109 studies from 101 reports. Meta-analyses were conducted for 12 antibiotics and qualitative synthesis was employed for the remaining drugs. Of the studies, 60.5% were open-label, cross-over, as recommended by FDA. We judged 46% of studies as having a high risk of bias and only 4% of having a low risk of bias. Among 19 quinolones with available food impact data, 14 (74%) had potentially clinically important interactions. For nalidixic acid, oxolinic acid, and tosufloxacin, food exerted a high positive impact on bioavailability (AUC or Cmax increased by > 45%), whereas, for all the remaining drugs, postprandial absorption was lower. The most significant negative influence of food (AUC or Cmax decreased by > 40%) occurred for delafloxacin capsules and norfloxacin, whereas the moderate influence (AUC or Cmax decreased by 30-40%) occurred for nemonoxacin and rufloxacin. All 14 analysed quinolones showed a substantial reduction in bioavailability when co-administered with antacids and mineral supplements, except for calcium preparations. The impact of beverages was evaluated for 10 quinolones, with 50% experiencing significantly reduced absorption in the presence of milk (the highest negative impact for ciprofloxacin). Moreover, both ciprofloxacin and levofloxacin demonstrated compromised bioavailability when consumed with orange juice, particularly calcium-fortified. Several factors may influence interactions, including the physicochemical characteristics of quinolones, the type of intervention, drug formulation, and the patient's health status. We assessed the quality of evidence as low due to the poor actuality of included studies, their methodological diversity, and uneven data availability for individual drugs.

The Importance of Nutrigenetics and Microbiota in Personalized Medicine: From Phenotype to Genotype.

Background After the completion of the Human Genome Project in 2003, the impact of genetic variations among people on human health was better understood. Precision medicine, also called 4P (Predictive, Preventive, Personalized, Participatory) medicine, is used to determine personal health risks, prevent, diagnose, and treat chronic diseases, and aims to identify the phenotypic, genotypic, and environmental factors that affect individual health risks instead of applying the same approach to everyone. Methods The study was conducted with 24 patients aged between 7 and 57. The patient group was selected from individuals who had undergone genetic and microbiota testing at Epigenetic Coaching Company. The patients' age, gender, and health status were documented. Genomic analysis of buccal samples was subsequently conducted using a custom Infinium HTS iSelect microarray on an Illumina iScan instrument, and microbiota metagenome analysis was performed using an Illumina NextSeq 500 platform. This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Biruni University Molecular Biology and Genetics Ethics Committee, with the decision number 2023/78-03. Results The genotypes of 19 cases carrying genetic variants involved in the metabolism of Vitamin D, Folate, B12, and Choline were analyzed. Eight of the cases were included in our study as autism patients, eight as allergy patients, and three as autoimmune thyroiditis patients. The Vitamin D receptor (VDR) genetic variants and microbiota diversity (using the Firmicutes/Bacteroides ratio, an indicator of dysbiosis) of 11 cases (9 allergy and two autism patients) participating in the study were evaluated together. Conclusions Translating nutrigenetic and nutrigenomic research into multidisciplinary clinical practice is the most challenging aspect. It is now evident that integrating data regarding phenotype and genotype, and using nutrition, lifestyle, and supplements tailored to an individual's genetics can increase clinical success. Importantly, if we wish to adopt an epigenomic approach, we must incorporate analyses of nutrigenetics, microbiota, and personalized risk based on test results.

Long-term PM2.5 exposure associated with severity of angina pectoris and related health status in patients admitted with acute coronary syndrome: Modification effect of genetic susceptibility and disease history

Long-term particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5) exposure has been associated with the occurrence of acute coronary syndrome (ACS). However, the impact of PM2.5 exposure and its components on the severity of angina pectoris and disease-related health status in patients hospitalized for ACS is understudied. To assess the association between long-term exposure to PM2.5 components and the angina pectoris severity in ACS patients, as well as the modification effects of genetic factors and disease history in north China. During 2017–2019, 6729 ACS patients were collected in Shandong Province and Beijing, with their angina pectoris severity evaluated using Seattle Angina Questionnaire (SAQ). The 0–3 years' average concentrations of PM2.5 and its five major components were assigned to each patient's residential address. Linear mixed-effects model, weighted quantile regression, and quantile g-computation were used to estimate the effects of both single and joint associations between PM2.5 components and SAQ scores. The interactive effect was estimated by polygenic risk scores and disease history. For each interquartile range increase in PM2.5, the overall SAQ score changed by −3.71% (95%CI: −4.54% to −2.88%), with score of angina stability more affected than angina frequency and other dimensions of angina pectoris severity. Sulfate and ammonium were major contributors to the effect of PM2.5 exposure. Significant modification effect was only observed for disease history, especially for the dimension of physical limitation. Among a series of pre-existing diseases, patients with a family history of coronary artery disease, previous percutaneous coronary intervention or coronary artery bypass grafting, and stroke were more susceptible to PM2.5 exposure than others. Greater exposure to PM2.5 is associated with more serious angina pectoris and worse disease-related health status in ACS patients. Public health and clinical priority should be given to cutting down key effective components and protecting highly vulnerable individuals.

Implementation of Nurse Doctor Collaboration in Surgical Cases for Children Patients at The Central Surgery Installation (IBS) Arjawinangun Hospital Cirebon

The increasingly complex health needs of children require treatment from various scientific disciplines, especially when faced with surgery. Children who are hospitalized and undergo surgery for the first time will be at risk of experiencing physiological and psychological problems that affect the length of stay in hospital. It is hoped that collaboration can be a solution in pediatric surgical cases in the operating room to reduce medical errors and maintain the stability of the health status of pediatric patients until the operation is completed. To describe the application of nurse-doctor collaboration in surgical cases for pediatric patients at the Central Surgery Installation (IBS) of Arjawinangun Regional Hospital, Cirebon. This research is a quantitative study with a cross sectional design. The instrument used is the CPAT consisting of 53 assessment items divided into 8 domains. The number of samples used was 41 people from the nursing and doctor professions. Data analysis used univariate and bivariate analysis using the Kruskall Walls test to see the significance of the difference in CPAT scores between nurses and doctors. The research results show that there is a significant difference in perception between nurses and doctors in pediatric surgical cases in the IBS room at Arjawinangun Hospital, Cirebon, in domain 4 (p=0.000), domain 5 (p=0.000), domain 6 (p=0.010) and domain 8 (p=0.040). There are significant differences in perceptions between the nursing and medical professions regarding collaboration in pediatric surgical cases in the IBS ward.