Clinical Record Data Research Articles

Digital health technology to support patient-centered shared decision making at point of care for juvenile idiopathic arthritis

Despite availability of multiple FDA approved therapies, many children with juvenile idiopathic arthritis (JIA) suffer pain and disability due to uncontrolled disease. The term JIA includes a heterogeneous set of conditions unified by chronic inflammatory arthritis, collectively affecting 1:1,000 children. When reviewing treatment options with families the rheumatologist currently refers to the experience of the average patient in relatively small controlled clinical trials, to consensus-based treatment plans, or increasingly the choice is dictated by the formulary restrictions of insurance payers. The current paradigm for treatment selection does not incorporate real-world evidence of treatment effectiveness centered to the individual patients with whom decisions are to be made. Treatment decisions based on the evidence of the average patient are not optimized to reflect the unique clinical characteristics of an individual with JIA and their disease course, nor does it account for heterogeneous treatment effects. To guide treatment choices centered around each patient, we describe a novel concept of utilizing digital health technology to bring patient-centered information into shared decision-making discussions based on comparative effectiveness analysis of electronic health record or observational clinical registry data of patients with similar characteristics. The envisioned digital tool will organize and present data relevant to the individual patient and enable evidence-based individualized treatment decision making when used in a collaborative manner with the patient family and rheumatologist. Capabilities in digital health technology, data capturing, and analytical methodologies are ripe for this endeavor. This brings the concept of a learning health system directly to the point of care.

Oral health and chronic kidney disease: Findings from a descriptive survey in Lagos, Nigeria.

Background: Chronic kidney disease (CKD) is a global public health problem, characterized by a progressive and irreversible decline in renal functions, and affecting up to 22.3% of Nigerians. Oral diseases are increasingly recognized to have a bidirectional relationship with CKD, contributing to systemic inflammation, infections, protein-energy wasting, and atherosclerotic complications. Given this interconnectedness, we aimed to explore the relationship between CKD and oral conditions among LASUTH patients to better understand and address these co-occurring health issues. Methods: This descriptive observational study was conducted in the nephrology unit of LASUTH. Patients aged >20 years with a diagnosis of CKD were enlisted and a validated questionnaire with the modified WHO oral health status proforma was utilized to record clinical data: Estimated Glomerular Filtration Rate (EGFR), End-Stage Renal Disease (ESRD), Creatinine and Urinalysis from medical records and oral examination findings, Oral Hygiene Index-Simplified (OHI-S), Gingival Index (GI), Community Periodontal Index of Treatment needs (CPITN), oral malodour, and Oral lesions. Multivariate logistic regression analysis was conducted with adjustments for covariates like age, alcohol use, and BMI to determine the association between oral diseases and CKD. The significance level (p) was set at 0.05, with a confidence interval (CI) of 95%. Results: A total of 200 patients at different stages of CKD were included. The age range was 22–83 years. The majority were aged 31-60 years (mean age 55.22 ± 14.35 years); 69% were males; 7% were current smokers while 12% currently drank alcohol; 27% had eGFR< 15 mL/min/1.73m2 (ESRD); 27% had Creatinine values >1.3mg/dl; prevalence of Gingivitis was 72%; periodontitis was 14% (CPI score ≥3: Pocket depth of ≥4 mm); and poor OHI was 22%. The commonest oral lesions were white lesions 2%, candidiasis 4.5%, hyperpigmentation 22%, oral ulcers 5%, hemorrhagic lesions 12.5%, and Oral malodor 74.5%. Multiple logistic regression analysis revealed significantly increased odds of ESRD among uneducated respondents (OR 1.194; CI: 0.832-1.713); those >60years (OR: 1.129; CI:0.436-2.923); current alcohol drinkers (OR:1.125; CI: 0.281-4.409); and smokers (OR:2.328; CI: 0.27-20.289). The odds of low stimulated saliva flow rate (OR: 1.181; CI:0.768-4.512), oral malodor (OR:1.093; CI: 0.763-1.565), and periodontal disease (OR: 1.242; CI: 0.698-2.209) were also significantly higher among those with ESRD. Conclusion: Individuals with CKD and ESRD may have a higher prevalence of oral diseases and conditions. There were significantly increased odds of ESRD among uneducated respondents, those over 60, current alcohol consumers, and smokers. Additionally, the odds of low stimulated saliva flow rate, oral malodor, and periodontal disease was also significantly higher among those with ESRD. This relationship may also be bidirectional, highlighting the need for appropriate oral self-care and regular dental-care utilization in patients with renal disease. The findings underscore the need for integrated healthcare approaches that consider both oral and renal health, providing a foundation for further research and targeted interventions.

Effects of testosterone and metformin on the GlycanAge index of biological age and the composition of the IgG glycome.

With aging, the body's ability to maintain regular functions declines, increasing susceptibility to age-related diseases. Therapeutic interventions targeting the underlying biological changes of aging hold promise for preventing or delaying multiple age-related diseases. Metformin, a drug commonly used for diabetes treatment, has emerged as a potential gerotherapeutic agent due to its established safety record and preclinical and clinical data on its anti-aging effects. Glycosylation, one of the most common and complex co- and post-translational protein modifications, plays a crucial role in regulating protein function and has been linked to aging and various diseases. Changes in immunoglobulin G (IgG) glycosylation patterns have been observed with age, and these alterations may serve as valuable biomarkers for disease predisposition, diagnosis, treatment monitoring, and overall health assessment. In this study, we analyzed the IgG glycosylation patterns of white men from Europe, aged 29-45years, under treatment with metformin, testosterone, metformin plus testosterone, and placebo (trial registration number NCT02514629, 2013/07/04), and investigated the longitudinal changes in glycosylation over time. We observed statistically significant differences in the IgG glycome composition between participants on testosterone therapy and placebo, with decreased agalactosylation and increased galactosylation and sialylation. However, metformin therapy did not result in statistically significant changes in glycosylation patterns. These findings contribute to our understanding of the impact of therapeutic interventions on IgG glycosylation and confirm the value of IgG glycosylation as a significant biomarker, capable of assessing biological age using the GlycanAge index and providing insight into overall health compared to chronological age.

Vision loss and diabetic retinopathy prevalence and risk among a cohort of Indigenous and non-Indigenous Australians with type 2 diabetes receiving renal haemodialysis treatment: The retinopathy in people currently on renal dialysis (RiPCORD) study

AimsDiabetic nephropathy, vision loss and diabetic retinopathy (DR) are frequent comorbidities among individuals with type 2 diabetes (T2D). The Retinopathy in People Currently On Renal Dialysis (RiPCORD) study sought to examine the epidemiology and risk of vision impairment (VI) and DR among a cohort of Indigenous and non-Indigenous Australians with T2D currently receiving haemodialysis for end-stage renal failure (ESRF). MethodsA total of 106 Indigenous and 109 non-Indigenous Australians were recruited in RiPCORD across five haemodialysis centres in urban and remote settings. Clinical assessments, questionnaires and medical record data determined the rates of ocular complications and risk factor profiles. ResultsPrevalence rates include unilateral VI, 23.5 %; bilateral VI, 11.7 %; unilateral blindness, 14.2 %; and bilateral blindness, 3.7 %, with no significant differences between sub-cohorts (p=0.30). DR prevalence rates were 78.0 % among non-Indigenous Australians and 93.1 % among Indigenous Australians (p=<0.001). Non-Indigenous ethnicity (OR: 0.28) and pre-dialysis diastolic blood pressure (OR: 0.84 per 10-mmHg) were protective, while peripheral vascular disease (OR: 2.79) increased DR risk. ConclusionsOcular complications among individuals with T2D and ESRF are disproportionately high, especially for Indigenous Australians, and beyond what can be accounted for by risk factor variation. Findings suggest a need to improve screening and preventative efforts within this high-risk population group.

Electronic data capture in resource-limited settings using the lightweight clinical data acquisition and recording system

Our prototype system designed for clinical data acquisition and recording of studies is a novel electronic data capture (EDC) software for simple and lightweight data capture in clinical research. Existing software tools are either costly or suffer from very limited features. To overcome these shortcomings, we designed an EDC software together with a mobile client. We aimed at making it easy to set-up, modifiable, scalable and thereby facilitating research. We wrote the software in R using a modular approach and implemented existing data standards along with a meta data driven interface and database structure. The prototype is an adaptable open-source software, which can be installed locally or in the cloud without advanced IT-knowledge. A mobile web interface and progressive web app for mobile use and desktop computers is added. We show the software’s capability, by demonstrating four clinical studies with over 1600 participants and 679 variables per participant. We delineate a simple deployment approach for a server-installation and indicate further use-cases. The software is available under the MIT open-source license. Conclusively the software is versatile, easily deployable, highly modifiable, and extremely scalable for clinical studies. As an open-source R-software it is accessible, open to community-driven development and improvement in the future.

Applications of Multimodal Artificial Intelligence in Non-Hodgkin Lymphoma B Cells.

Given advancements in large-scale data and AI, integrating multimodal artificial intelligence into cancer research can enhance our understanding of tumor behavior by simultaneously processing diverse biomedical data types. In this review, we explore the potential of multimodal AI in comprehending B-cell non-Hodgkin lymphomas (B-NHLs). B-cell non-Hodgkin lymphomas (B-NHLs) represent a particular challenge in oncology due to tumor heterogeneity and the intricate ecosystem in which tumors develop. These complexities complicate diagnosis, prognosis, and therapy response, emphasizing the need to use sophisticated approaches to enhance personalized treatment strategies for better patient outcomes. Therefore, multimodal AI can be leveraged to synthesize critical information from available biomedical data such as clinical record, imaging, pathology and omics data, to picture the whole tumor. In this review, we first define various types of modalities, multimodal AI frameworks, and several applications in precision medicine. Then, we provide several examples of its usage in B-NHLs, for analyzing the complexity of the ecosystem, identifying immune biomarkers, optimizing therapy strategy, and its clinical applications. Lastly, we address the limitations and future directions of multimodal AI, highlighting the need to overcome these challenges for better clinical practice and application in healthcare.

Artificial intelligence and headache.

In this narrative review, we introduce key artificial intelligence (AI) and machine learning (ML) concepts, aimed at headache clinicians and researchers. Thereafter, we thoroughly review the use of AI in headache, based on a comprehensive literature search across PubMed, Embase and IEEExplore. Finally, we discuss limitations, as well as ethical and political perspectives. We identified six main research topics. First, natural language processing can be used to effectively extract and systematize unstructured headache research data, such as from electronic health records. Second, the most common application of ML is for classification of headache disorders, typically based on clinical record data, or neuroimaging data, with accuracies ranging from around 60% to well over 90%. Third, ML is used for prediction of headache disease trajectories. Fourth, ML shows promise in forecasting of headaches using self-reported data such as triggers and premonitory symptoms, data from wearable sensors and external data. Fifth and sixth, ML can be used for prediction of treatment responses and inference of treatment effects, respectively, aiming to optimize and individualize headache management. The potential uses of AI and ML in headache are broad, but, at present, many studies suffer from poor reporting and lack out-of-sample evaluation, and most models are not validated in a clinical setting.

Risk factors and predictive models for frozen shoulder

This study aims to explore the risk factors associated with frozen shoulder (FS) and develop a predictive model for diagnosing FS, in order to facilitate early detection of the condition. A total of 103 patients diagnosed with FS and admitted to the Department of Joint Surgery at Suining Central Hospital between October 2021 and October 2023 were consecutively included in the study. Additionally, 309 individuals without shoulder joint diseases, matched for age and gender, who visited the department during the same time, were included as the control group.The complete recording of clinical data for all patients was followed by the utilization of statistical tests such as the Mann–Whitney U test, sample t test, and chi-square test to compare different groups. Additionally, multivariate binary logistic regression analysis was employed to identify risk factors associated with the occurrence of FS in patients, leading to the establishment of a prediction model and derivation of a simplified equation. The diagnostic effectiveness of individual indicators and prediction models was assessed through the use of receiver operating characteristic (ROC) curve analysis. In the sample of 103 individuals, 35 were identified as male and 68 as female, with an average age range of 40–70 years (mean age: 54.20 ± 6.82 years). The analysis conducted between different groups revealed that individuals with a low body mass index (BMI), in conjunction with other factors such as diabetes, cervical spondylosis, atherosclerosis, and hyperlipidemia, were more susceptible to developing FS. Logistic regression analysis further indicated that low BMI, diabetes, cervical spondylosis, and hyperlipidemia were significant risk factors for the occurrence of FS. These variables were subsequently incorporated into a predictive model, resulting in the creation of a simplified equation.The ROC curve demonstrated that the combined indicators in the predictive model exhibited superior diagnostic efficacy compared to single indicators, as evidenced by an area under the curve of 0.787, sensitivity of 62.1%, and specificity of 82.2%. Low BMI, diabetes, cervical spondylosis, and hyperlipidemia are significant risk factors associated with the occurrence of FS. Moreover, the utilization of a prediction model has demonstrated superior capability in forecasting the likelihood of FS compared to relying solely on individual indicators. This finding holds potential in offering valuable insights for the early diagnosis of FS.

Italian National Registry of Alopecia Areata: an epidemiological study of 699 Italian patients.

Alopecia areata (AA) is an organ-specific autoimmune disease that affects the hair follicles of the scalp and the rest of the body causing hair loss. Due to the unpredictable course of AA and the different degrees of severity of hair loss, only a few well-designed clinical studies with a low number of patients are available. Also, there is no specific cure, but topical and systemic anti-inflammatory and immune system suppressant drugs are used for treatment. The need to create a global registry of AA, comparable and reproducible in all countries, has recently emerged. An Italian multicentric electronic registry is proposed as a model to facilitate and guide the recording of epidemiological and clinical data and to monitor the introduction of new therapies in patients with AA. The aim of this study was to evaluate the epidemiological data of patients with AA by collecting detailed information on the course of the disease, associated diseases, concomitant and previous events, and the clinical response to traditional treatments. Estimate the impact on the quality of life of patients. The creation of the National Register of AA has proven to be a valid tool for recording, with a standardized approach, epidemiological data, the trend of AA, response to therapies and quality of life. AA is confirmed as a difficult hair disease to manage due to its unpredictable course and, in most cases, its chronic-relapsing course, capable of having a significant impact on the quality of life of patients.

Improving the Detection, Assessment, Management and Prevention of Delirium in Hospices (the DAMPen-D study): Feasibility study of a flexible and scalable implementation strategy to deliver guideline-adherent delirium care

Background: Delirium is a complex condition, stressful for all involved. Although highly prevalent in palliative care settings, it remains underdiagnosed and associated with poor outcomes. Guideline-adherent delirium care may improve its detection, assessment and management. Aim: To inform a future definitive study that tests whether an implementation strategy designed to improve guideline-adherent delirium care in palliative care settings improves patient outcomes (reduced proportion of in-patient days with delirium). Design: With Patient Involvement members, we conducted a feasibility study to assess the acceptability of and engagement with the implementation strategy by hospice staff (intervention), and whether clinical record data collection of process (e.g. guideline-adherent delirium care) and clinical outcomes (evidence of delirium using a validated chart-based instrument;) pre- and 12-weeks post-implementation of the intervention would be possible. Setting/participants: In-patient admissions in three English hospices. Results: Between June 2021 and December 2022, clinical record data were extracted from 300 consecutive admissions. Despite data collection during COVID-19, target clinical record data collection (n = 300) was achieved. Approximately two-thirds of patients had a delirium episode during in-patient stay at both timepoints. A 6% absolute reduction in proportion of delirium days in those with a delirium episode was observed. Post-implementation improvements in guideline-adherent metrics include: clinical delirium diagnosis 15%–28%; delirium risk assessment 0%–16%; screening on admission 7%–35%. Conclusions: Collection of data on delirium outcomes and guideline-adherence from clinical records is feasible. The signal of patient benefit supports formal evaluation in a large-scale study.

Digital transformation in public health: a software tool for efficient health record management and improved healthcare delivery

Background In today’s world, the abundance of data in many areas of society has increased the need to use efficient technological tools to analyse, accurately and clearly present information. The objective was to develop a virtual platform to increase efficiency in the control of medical records (MR) and reduce errors in the recording of clinical data. To improve the quality of medical care in public health centres. Method The research used a methodology that follows a four-stage process for the development of the medical records management software. It started with planning where the user stories and their priority were defined. In the design phase, the system architecture and code structure were developed. Subsequently, in the coding phase, pair programming with incremental implementation was emphasised. Finally, in the testing phase, automatic and manual integration tests were carried out, documented by means of acceptance tests to ensure the quality of the developed software. Results The web-based platform has led to a significant increase in the number of patients seen, resulting in significant improvements in resource management at the health centres. In addition, the reduction in the incidence of errors highlights the superior accuracy in recording and tracking medical information, promoting a safer and more efficient care environment for patients. Conclusions The main focus of this study is the management of medical records, with the aim of reducing the time spent on registration, ensuring secure access to information, reducing documentation errors and facilitating instant data retrieval through a web-based platform. The results show the effectiveness of this methodology and its positive impact on the management of medical records.

Validation of an Anti-Müllerian Hormone Cutoff for Polycystic Ovarian Morphology in the Diagnosis of Polycystic Ovary Syndrome in the HARMONIA Study: Protocol for a Prospective, Noninterventional Study.

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women and is diagnosed using the Rotterdam criteria, including diagnosis of polycystic ovarian morphology (PCOM) by transvaginal ultrasound (TVUS). Due to high cost, availability, and the impact of the operator and ultrasound equipment on the reliability of the antral follicle count (AFC) by TVUS, an unmet need exists for a diagnostic test to determine PCOM without TVUS. A strong positive correlation between elevated anti-Müllerian hormone (AMH) levels and AFCs has been demonstrated in women with PCOS. In addition, recent updates to the international evidence-based PCOS guidelines state that serum AMH can be used as an alternative to TVUS-determined AFC, in the diagnosis of PCOM. The retrospective APHRODITE study derived and validated an AMH cutoff of 3.2 ng/mL for the Elecsys AMH Plus or Elecsys AMH assays (Roche) to diagnose PCOM in patients with PCOS. This study aims to further validate, in an independent prospective cohort, the AMH cutoff (3.2 ng/mL) for PCOM determination, which was previously derived and validated in the APHRODITE study. This large, prospective, multicenter, population-based, noninterventional study will evaluate the previously established AMH cutoff for the determination of PCOM during the diagnosis of PCOS using the Elecsys AMH Plus immunoassay in an independent population. Participants were women born between July 1985 and December 1987 in Northern Finland; the study partially links to the Northern Finland Birth Cohort 1986. We assessed the enrolled women, determined with the 2023 PCOS Guidelines, for current PCOS status and divided them by phenotype if positive. Each participant had 1 study visit to collect serum samples, record clinical data, and undergo a gynecological examination including TVUS. All data were collected by highly trained midwives or trained gynecologists. Sensitivity, specificity, and agreement measures were used to validate the previously determined cutoff in the whole population and in subpopulations based on phenotype and relevant demographic or clinical factors. The minimum target sample size was approximately 1800 women, including approximately 10% with PCOS. At the time of manuscript submission, participant recruitment had concluded, and 1803 women were enrolled into the study. Data collection is complete and biostatistical analysis is planned for 2023. To limit variability, there were few TVUS operators and only 2 TVUS machines of the same type. Additionally, all women who were taking oral contraceptives were excluded from the primary analysis population. Selection bias was limited as this was a population-based study and participants were not seeking treatment for PCOS symptoms. Validating the AMH cutoff in a large, population-based study will provide further evidence on the utility of the Elecsys AMH Plus or Elecsys AMH assays in PCOM diagnosis as an alternative to TVUS. Measuring AMH for PCOM diagnosis could reduce delayed or missed diagnoses due to operator-dependent TVUS examinations. ClinicalTrials.gov NCT05527353; http://tinyurl.com/2f3ffbdz. DERR1-10.2196/48854.

Association between continuity of care and attendance of post-discharge follow-up after psychiatric emergency presentation

The number of accident and emergency (A&E) hospital attendances by young people aged 18 or under with a recorded diagnosis of a psychiatric condition more than tripled between 2010 and 2022. After discharge from the hospital, attendance at follow-up appointments in the community is critical to ensure the safety of young people and optimise the use of clinical resources. A retrospective cohort study was conducted to evaluate the association between follow-up attendance and the continuity of clinicians and clinical teams, using electronic clinical record data from East London NHS Foundation Trust (ELFT), between April 2019 and March 2022. Multi-level mixed effects logistic regression was performed to model the follow-up attendance odds based on whether the same or different clinician and clinical team offered the initial A&E and the community follow-up appointment or whether a crisis team was involved. 3134 A&E presentations by 2368 young people were identified within the study period. Following these presentations, 2091 follow-up appointments in the community were offered. The attendance rate increased by more than three times if the follow-up appointment was offered by the same clinician who saw the young person in A&E (odds ratio (OR) = 3.66; 95% CI 1.65–8.13). Whether the same clinical team provided the community follow-up appointment, or whether a crisis team was involved before discharge made no difference to the likelihood of follow-up attendance. The findings support the importance of the continuity of clinicians in the care of young people in crisis.

Physician-Centered EHR Data Utilization: A Pilot Study.

The utilization of vast amounts of EHR data is crucial to the studies in medical informatics. Physicians are medical participants who directly record clinical data into EHR with their personal expertise, making their roles essential in follow-up data utilization, which current studies have yet to recognize. This paper proposes a physician-centered perspective for EHR data utilization and emphasizes the feasibility and potentiality of digging into physicians' latent decision patterns in EHR. To support our proposal, we design a physician-centered CDS approach named PhyC and test it on a real-world EHR dataset. Experiments show that PhyC performs significantly better in the auxiliary diagnosis of multiple diseases than globally learned models. Discussions on experimental results suggest that physician-centered data utilization can help to derive more objective CDS models, while more means for utilization need further exploration.

Further evidence regarding the convergent and discriminant validity of Minnesota Multiphasic Personality Inventory-3 (MMPI-3) scores in the preoperative psychological evaluation of patients seeking metabolic and bariatric surgery

BackgroundPsychological testing is used in some preoperative psychological evaluations of patients seeking metabolic and bariatric surgery. The Minnesota Multiphasic Personality Inventory-3 (MMPI-3) contains new norms, updated item content, and new scales such as Eating Concerns and Impulsivity, which are relevant to the assessment of patients seeking metabolic and bariatric surgery. ObjectiveThe goal of this investigation was to establish convergent and discriminant properties of the MMPI-3 scales with relevant clinical interview and medical record data from electronic medical records. SettingAcademic medical center in the Midwest. MethodsA sample of 790 consecutive patients who completed a preoperative psychological evaluation and took the MMPI-3 were included. Data from medical records and the assessment report were coded by a trained research assistant. ResultsMMPI-3 scale scores demonstrated good convergent and discriminant validity. For instance, the Emotional/Internalizing Dysfunction scales correlated with depression and anxiety disorder, suicide history, sexual abuse history, psychotropic medication use, and eating behaviors. Behavioral/Externalizing Dysfunction scales correlated with alcohol, nicotine, and substance use and eating behaviors such as loss-of-control overeating. The Eating Concerns scale demonstrated the highest correlational patterns with various eating behaviors such as loss-of-control overeating, binge eating, and stress eating. ConclusionsMMPI-3 scale scores perform as well as their Minnesota Multiphasic Personality Inventory-2 Restructured Form counterparts. Newer scales, such as Eating Concerns and Impulsivity, perform particularly well in the assessment of various eating behaviors.

Research on the Aided Diagnosis Method of Diseases Based on Domain Semantic Knowledge Bases

The health care domain is a knowledge-intensive domain. The quality of clinical diagnosis relies mainly on the medical knowledge and experience held by doctors. However, the ability of a single doctor is very limited, so the quality of clinical diagnosis is currently not high. In this paper, an aided diagnosis method based on domain semantic knowledge bases is proposed. Firstly, a domain semantic knowledge base is established by extracting and refining the knowledge of the medicine subject matter domain from the Freebase RDF dumps. Then, based on the semantic knowledge base, the algorithms for calculating the weights of the symptoms in the knowledge base, the relative weights of the diseases related to the input symptom set from a patient, and the related symptom set related to the input symptom set from the patient are proposed. Finally, the clinical medical record data of several common diseases are selected to make an evaluation on the proposed method. For each medical record, the symptom information is extracted from the chief complaint as the patient’s input symptom set. Based on the input symptom set, the method of this paper is used to obtain the list of related diseases and the ranking of disease relative weights. From the disease relevance rankings, the Top 1 (first diagnosis) and Top-3 (first 3 diagnoses) are compared with the doctor’s diagnoses in the medical records. Among them, ovarian cyst has the highest Top-1 and Top-3 hit rates of 67.3% and 89.1%, respectively. Followed by acute upper respiratory tract infection, Top-1 and Top-3 hit rates are 56.6% and 85.2%, respectively. The average Top-1 and Top-3 hit rates are 47.9% and 79.7%, respectively. Compared with the relevant methods, the method of this paper is better. The evaluation results show that based on the domain semantic knowledge base and the aided diagnosis method of diseases constructed in this paper, it is possible to provide aided diagnosis services of a large number of common diseases for general practitioners (especially inexperienced doctors) at the grass-roots level as well as self-diagnosis services of diseases for patients.

The contribution of granger causality analysis to our understanding of cardiovascular homeostasis: from cardiovascular and respiratory interactions to central autonomic network control.

Homeostatic regulation plays a fundamental role in maintenance of multicellular life. At different scales and in different biological systems, this principle allows a better understanding of biological organization. Consequently, a growing interest in studying cause-effect relations between physiological systems has emerged, such as in the fields of cardiovascular and cardiorespiratory regulations. For this, mathematical approaches such as Granger causality (GC) were applied to the field of cardiovascular physiology in the last 20years, overcoming the limitations of previous approaches and offering new perspectives in understanding cardiac, vascular and respiratory homeostatic interactions. In clinical practice, continuous recording of clinical data of hospitalized patients or by telemetry has opened new applicability for these approaches with potential early diagnostic and prognostic information. In this review, we describe a theoretical background of approaches based on linear GC in time and frequency domains applied to detect couplings between time series of RR intervals, blood pressure and respiration. Interestingly, these tools help in understanding the contribution of homeostatic negative feedback and the anticipatory feedforward mechanisms in homeostatic cardiovascular and cardiorespiratory controls. We also describe experimental and clinical results based on these mathematical tools, consolidating previous experimental and clinical evidence on the coupling in cardiovascular and cardiorespiratory studies. Finally, we propose perspectives allowing to complete the understanding of these interactions between cardiovascular and cardiorespiratory systems, as well as the interplay between brain and cardiac, and vascular and respiratory systems, offering a high integrative view of cardiovascular and cardiorespiratory homeostatic regulation.

THE ADULT DAY CENTER: UNTAPPED TERRITORY FOR AGING RESEARCH

Abstract Adult day service centers (ADCs) in the United States are a vital, but overlooked source of community-based long-term care for diverse older adults with multiple chronic conditions, including dementia. The National Institute on Aging has called for more research on ADCs. In this interdisciplinary symposium, we present challenges and opportunities in conducting research in these congregate settings. First, we look at the operating status of ADCs nationally in the aftermath of the COVID-19 pandemic and disparities in access to care using longitudinal data from the National Post-acute and Long-term Care Study. Then we examine the lack of electronic health record utilization and clinical data capture in 4,035 ADCs nationally and discuss strategies to modernize technology in these settings to facilitate data collection. We subsequently present a new database, developed vis a vis an academic/community partnership between the National Adult Day Services Association and researchers, that centralizes and makes data collection feasible in ADCs with limited resources. We will also explore factors supporting intervention research that are unique to ADCs. Finally, we present a protocol adapted for the ADC setting, to test a mobile application that facilitates data collection and enables communication between ADCs, caregivers, and healthcare providers. Our findings show that, while research in ADCs has been limited historically, academic, government, and community partners are working together to spur pragmatic innovations that modernize these settings and better resource them to elevate standards of care.

Abstract C124: Racial and ethnic disparities in follow-up of abnormal cervical cancer screening results

Abstract Background: Despite well-defined practice guidelines for management of abnormal cervical cancer (CC) screening results, the incidence of CC is disproportionately higher in Black and Hispanic women compared to White women. Black women experience the highest overall CC mortality rates, irrespective of subtype or stage. Disparities in CC prevention may be related to differential follow-up of abnormal CC screening and delays in CC diagnosis. In a cohort of primarily Black and Hispanic patients, we investigated racial and ethnic disparities in factors associated with colposcopy attendance following abnormal CC screening. Methods: In a large urban OB/GYN clinic in Connecticut, clinical and demographic medical record data was collected for patients with abnormal CC screening results from 2/2021 to 1/2022. Factors related to colposcopy completion were examined for colposcopy indicated patients. In univariate and multivariate analysis (SAS 9.4), we analyzed the relationship between clinical and demographic characteristics and key junctures in the colposcopy referral and completion cascade. Colposcopy scheduling outcomes were compared by race/ethnicity using the Mann-Whitney U test. Analyses of race/ethnicity were stratified by primary language spoken (non-Hispanic Black, Hispanic English-speaking, Hispanic Spanish-speaking, and White/Other). Results: Of the 248 patients indicated for colposcopy, 44% identified as Black, 39% identified as Hispanic, and 18% identified as White/Other. Among Hispanic patients, 62% spoke English and 38% spoke Spanish as their primary language. The majority of colposcopy indicated patients were publicly insured by Medicare or Medicaid. Colposcopy appointments were attended by 86.7% (215) of indicated patients, with 63.3% (157) attending within the guideline recommended interval of 8 weeks from CC screening for high-grade cytology and 90 days for low-grade cytology. In univariate analysis, colposcopy attendance was significantly lower in Black vs. White/Other patients (p&amp;lt;0.05). Multivariate analysis also showed that Black patients experienced the greatest disparity in colposcopy attendance, followed by Hispanic English-speaking patients (p&amp;lt;0.01). Although rates of guideline-concordant colposcopy attendance were lowest in Black and Hispanic English-speaking patients, these differences were not significant as guideline-concordant completion rates decreased across all groups. No significant relationships were found between race/ethnicity and the number of cancellations, no shows, or reschedules of colposcopy appointments. Conclusions: Although we identified significant differences in colposcopy attendance across race/ethnicity, there were no significant differences in guideline-concordant colposcopy attendance or appointment scheduling outcomes related to delays in colposcopy (i.e. cancellation, no show, or reschedule). Future studies on colposcopy delays will focus on multi-level factors that may disproportionately burden racial/ethnic minority groups and lead to disparities in follow-up of abnormal CC screening results. Citation Format: Anisha V. Patel, Guangyu Tong, Beth A. Jones, Raul U. Hernandez-Ramirez, Wanyi Tang, Sarah Megiel, Abigail Girgis, Jamie Foster, Donna Spiegelman, Sangini S. Sheth. Racial and ethnic disparities in follow-up of abnormal cervical cancer screening results [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C124.

Abstract 17673: Sudden Cardiac Death as the First Manifestation of Heart Disease

Background: Clinical risk stratification is most challenging in the subgroup of individuals who present with sudden cardiac death (SCD) as the first manifestation of heart disease (SCD-FM) and there is a lack of current era population-based data. Hypothesis: Occurrence of SCD-FM SCD differs by ethnicity and access to health care. Methods: Consecutive out-of-hospital cases of SCD attended by emergency medical services were ascertained prospectively from a large ongoing population-based study in the Southwest US (population ~ 850K, 2015-2022) using an established multi-source ascertainment and adjudication process. A detailed review was conducted of the lifetime clinical record and available autopsy data, for each individual. SCD-FM cases were defined as SCD with no prior heart disease diagnosis. We calculated annual age-standardized incidence of overall SCD and SCD-FM per 100,000 residents using US census data. Ethnicity-stratified incidence of SCD-FM was calculated. Occurrence of all health care visits prior to SCD was evaluated. Results: From a total of 2681 SCD cases (age 71 ± 16, female 35%) age adjusted incidence of SCD was 40[38-41] per 100,000 out of which SCD-FM was 15[14-16] per 100,000 (n=1019 (38%), age 67±18, female 33%). There was no difference in SCD-FM incidence between Hispanic and non-Hispanic residents (15 [13-17] vs 15 [14-17], p=0.84). Individuals younger than 65 yr were more likely to have SCD-FM compared to those older than 65 yr (50% vs 33%, p &lt;0.001). We observed that 91% of SCD-FM had visited healthcare providers and 3% had cardiac evaluations performed. Conclusion: A significantly higher proportion of SCD-FM were age &lt;65 but the proportion of SCD-FM did not differ by ethnicity. The vast majority of SCD-FM (91%) underwent health care visits prior to SCD but cardiac evaluations were rare (3%). These findings highlight the need to discover and develop user-friendly, cost-effective pre-screening methods to reduce SCD-FM in the general population.