Cumulative exposure to metabolic syndrome affects the risk of psoriasis differently according to age group: a nationwide cohort study in South Korea

Late-onset psoriasis is more associated with the cumulative metabolic syndrome burden in the oldest age group, suggesting the particular importance of managing metabolic syndrome in midlife and beyond.

The risk of fracture in age-related macular degeneration according to the presence of visual disability: a nationwide cohort study

PURPOSE

To evaluate the association between age-related macular degeneration (AMD) with or without visual disability (VD) and the risk of fracture using the National Health Insurance data in South Korea.

METHODS

In total, 3,894,702 individuals who had taken part in health-screening programs between January 1, 2009, and December 31, 2009, were included in the cohort and followed until December 31, 2019. The participants with VD, which could be related to the severity of AMD, were defined as those with a loss of vision or visual field defect as certified by the Korean government's Ministry of Health and Welfare. The hazard ratio was calculated for groups (control and AMD with/without VD) using the multivariable-adjusted cox regression analysis.

RESULTS

In total, 466,890 participants (11.99%) were diagnosed with fractures during the study period. An increased risk of fracture was observed in individuals with AMD compared with the control (adjusted hazard ratio (aHR), 1.09, 95% confidence interval (CI), 1.06-1.11). Furthermore, among the AMD individuals, an increased risk of fracture was prominent in individuals with VD (aHR 1.17, 95% CI 1.08-1.27) than those without VD (aHR 1.08, 95% CI 1.06-1.11) compared with the reference group (control).

CONCLUSIONS

AMD was associated with an increased risk of fracture even without VD. Prevention for fracture should be considered in AMD patients, especially when accompanied by VD.

Development of machine learning algorithms for scaling-up antibiotic stewardship

BACKGROUND

Antibiotic stewardship programs (ASP) aim to reduce inappropriate use of antibiotics, but their labor-intensive nature impedes their wide adoption. The present study introduces explainable machine learning (ML) models designed to prioritize inpatients who would benefit most from stewardship interventions.

METHODS

A cohort of inpatients who received systemic antibiotics and were monitored by a multidisciplinary ASP team at a tertiary hospital in the Republic of Korea was assembled. Data encompassing over 130,000 patient-days and comprising more than 160 features from multiple domains, including prescription records, laboratory, microbiology results, and patient conditions was collected.Outcome labels were generated using medication administration history: discontinuation, switching from intravenous to oral medication (IV to PO), and early or late de-escalation. The models were trained using Extreme Gradient Boosting (XGB) and light Gradient Boosting Machine (LGBM), with SHapley Additive exPlanations (SHAP) analysis used to explain the model's predictions.

RESULTS

The models demonstrated strong discrimination when evaluated on a hold-out test set(AUROC - IV to PO: 0.81, Early de-escalation: 0.78, Late de-escalation: 0.72, Discontinue: 0.80). The models identified 41%, 16%, 22%, and 17% more cases requiring discontinuation, IV to PO, early and late de-escalation, respectively, compared to the conventional length of therapy strategy, given that the same number of patients were reviewed by the ASP team. The SHAP results explain how each model makes their predictions, highlighting a unique set of important features that are well-aligned with the clinical intuitions of the ASP team.

CONCLUSIONS

The models are expected to improve the efficiency of ASP activities by prioritizing cases that would benefit from different types of ASP interventions along with detailed explanations.

Supervised machine learning model to predict mortality in patients undergoing venovenous extracorporeal membrane oxygenation from a nationwide multicentre registry

BACKGROUND

Existing models have performed poorly when predicting mortality for patients undergoing venovenous extracorporeal membrane oxygenation (VV-ECMO). This study aimed to develop and validate a machine learning (ML)-based prediction model to predict 90-day mortality in patients undergoing VV-ECMO.

METHODS

This study included 368 patients with acute respiratory failure undergoing VV-ECMO from 16 tertiary hospitals across South Korea between 2012 and 2015. The primary outcome was the 90-day mortality after ECMO initiation. The inputs included all available features (n=51) and those from the electronic health record (EHR) systems without preprocessing (n=40). The discriminatory strengths of ML models were evaluated in both internal and external validation sets. The models were compared with conventional models, such as respiratory ECMO survival prediction (RESP) and predicting death for severe acute respiratory distress syndrome on VV-ECMO (PRESERVE).

RESULTS

Extreme gradient boosting (XGB) (areas under the receiver operating characteristic curve, AUROC 0.82, 95% CI (0.73 to 0.89)) and light gradient boosting (AUROC 0.81 (95% CI 0.71 to 0.88)) models achieved the highest performance using EHR's and all other available features. The developed models had higher AUROCs (95% CI 0.76 to 0.82) than those of RESP (AUROC 0.66 (95% CI 0.56 to 0.76)) and PRESERVE (AUROC 0.71 (95% CI 0.61 to 0.81)). Additionally, we achieved an AUROC (0.75) for 90-day mortality in external validation in the case of the XGB model, which was higher than that of RESP (0.70) and PRESERVE (0.67) in the same validation dataset.

CONCLUSIONS

ML prediction models outperformed previous mortality risk models. This model may be used to identify patients who are unlikely to benefit from VV-ECMO therapy during patient selection.

The effects of special nursing units in nursing homes on healthcare utilization and cost: A case-control study using propensity score matching

BACKGROUND

Most nursing homes in South Korea lack professional nursing services, resulting in transporting residents to hospitals for mild health problems and nursing treatment needs. While the number of nursing homes has increased, the number of registered nurses working in nursing homes has declined. In 2019, the Korean Ministry of Health and Welfare and the National Health Insurance Service launched the Special Nursing Units in Nursing Homes, a pilot nurse-led model, to resolve the lack of health and nursing services in nursing homes by mandating registered nurses' minimum staffing levels and protecting their scope of practice.

OBJECTIVE

This study explored the effects of the Special Nursing Units model in Nursing Homes on healthcare utilization and cost among nursing home residents.

DESIGN

A comparative effectiveness research design using propensity score matching.

SETTING(S)

Eighteen nursing homes were selected based on the region and number of beds.

PARTICIPANTS

There were 323 matched-pairs of residents from the case and control groups.

METHODS

Nursing homes with more than 30 beds were recruited nationwide, with 18 nursing homes being selected based on the region and number of beds. The case group included 323 older adults receiving professional nursing services by registered nurses under the Special Nursing Units model in Nursing Homes for more than six months consecutively in 18 nursing homes between April and December 2019. We matched control participants using propensity score matching with health insurance and long-term care data. We analyzed the differences in healthcare utilization and cost changes between the case and control groups using generalized estimating equations.

RESULTS

The groups were not statistically different in baseline demographic or health-related characteristics. There were 26 (8.1%) and 30 (9.3%) deaths in the case and control groups, respectively, during the six months of the model, which was not statistically different (p = .576). The case group showed statistically significant decreases in healthcare utilization and costs, including hospitalization frequency (p = .008), length of stay (p = .002), and hospitalization costs (p = .003); outpatient visit frequency (p = .003) and costs (p < .001); and home healthcare frequency (p < .001) and cost (p < .001) than the control group.

CONCLUSIONS

Professional nursing services by registered nurses under the Special Nursing Units model in Nursing Homes decreased healthcare utilization and costs. A nurse-led model in nursing homes, which includes mandating the minimum staffing levels of registered nurses and protecting their scope of practice, promises to improve resident health outcomes.

Use of the Smart Excretion Care System Linked to Electronic Medical Records to Alleviate Nursing Burden and Enhance Patient Convenience: Mixed Methods Study

BACKGROUND

The surge in older demographics has inevitably resulted in a heightened demand for health care, and a shortage of nursing staff is impending. Consequently, there is a growing demand for the development of nursing robots to assist patients with urinary and bowel elimination. However, no study has examined nurses' opinions of smart devices that provide integrated nursing for patients' urinary and bowel elimination needs.

OBJECTIVE

This study aimed to evaluate the feasibility of the Smart Excretion Care System tethered to electronic medical records in a tertiary hospital and community care setting and discuss the anticipated reductions in the burden of nursing care.

METHODS

Focus group interviews were conducted using the Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines. The interviews were conducted in March 2021 and involved 67 nurses who had worked at Seoul National University Bundang Hospital for more than 1 year and had experience in assisting patients with excretion care. Data were collected using purposive and snowball sampling methods.

RESULTS

A total of four themes relevant to the Smart Excretion Care System were found: (1) expected reductions in the burden of nursing care, (2) applicable indications (by departments and diseases), (3) preferred features/functions, and (4) expected benefits of using the Smart Excretion Care System in clinical facilities. Nurses from comprehensive nursing care wards had the highest burden when it came to excretion care. It was a common opinion that the Smart Excretion Care System would be very useful in intensive care units and should be applied first to patients with stroke or dementia.

CONCLUSIONS

Excretion care is one of the most burdensome tasks for nurses, increasing their workload. The development of the Smart Excretion Care System as a digital health intervention could help improve nurses' work efficiency, reduce their burden, and extend to caregivers and guardians.

Changes in smoking, alcohol consumption, and the risk of Parkinson's disease

Objective

There have been no studies on the association between changes in smoking and alcohol consumption or combined changes in smoking and alcohol consumption frequencies and PD risk. To assess the influence of changes in smoking and alcohol consumption on the risk of Parkinson's disease (PD).

Methods

National Health Insurance Service (NHIS) database between January 2009 to December 2011 was analyzed. A total of 3,931,741 patients were included. Study participants were followed up for the incidence of PD until December 2017.

Results

Compared to the sustained non-smokers, sustained light smokers (adjusted hazard ratio [aHR] 0.80, 95% confidence interval [CI] 0.75-0.85), sustained moderate smokers (aHR 0.54, 95% CI 0.47-0.61), and sustained heavy smokers (aHR 0.49, 95% CI 0.44-0.55) had a lower risk of PD. Compared to those who sustained non-drinking, sustained light drinkers (aHR 0.85 95% CI 0.89-0.91), sustained moderate drinkers (aHR 0.68, 95% CI 0.60-0.78), and sustained heavy drinkers (aHR 0.77, 95% CI 0.68-0.87) showed decreased risk of PD. Among non-drinkers, those who started drinking to a light level were at decreased risk of PD (aHR 0.84, 95% CI 0.77-0.91). Among non-smoking and non-drinking participants, those who initiated smoking only (aHR 0.78, 95% CI 0.70-0.86), drinking only (aHR 0.77, 95% CI 0.68-0.87), and both smoking and drinking (aHR 0.69, 95% CI 0.58-0.82) showed decreased risk of PD.

Conclusion

Smoking is associated with decreased risk of PD with a dose-response relationship. Alcohol consumption at a light level may also be associated with decreased risk of PD. Further studies are warranted to find the possible mechanisms for the protective effects of smoking and drinking on PD, which may present insights into the etiology of PD.

Nurses' Burden of Elimination Care: Sequential Explanatory Mixed-Methods Design

Background

Inpatients commonly experience problems with elimination due to incontinence, urinary retentions, and complications with indwelling catheters. Although elimination care (EC) is an important nursing area, few studies explore the burden of EC on nurses.

Aim

To identify the burden on EC by analyzing nurses' opinions using sequential explanatory mixed method.

Methods

This research was conducted using a sequential explanatory mixed-methods design. A total of 59 nurses at a tertiary hospital in South Korea participated in the study from January 1 to March 31, 2022. For quantitative analysis, information about number of delays of work due to EC, required time for serving bedpan or diaper changes, percentage of EC per shift, and percentage of patients who need EC was collected through a survey. For qualitative analysis, focus group interviews were conducted to identify factors that put a burden on EC. Important themes were derived by analyzing nurses' opinions on EC.

Results

For nurses in intensive care units, general wards, and integrated nursing care wards, the number of work delays due to EC was 3.6 ± 1.5, 2.3 ± 1.2, and 4.8 ± 2.4 (p<0.01), respectively. The mean percentage of EC work out of total nursing tasks per shift was 36.2 ± 19.0, 29.3 ± 14.4, and 43.8 ± 14.1 (p=0.02), respectively. The mean percentage of patients requiring EC out of patients a nurse cares was 85.4 ± 16.6, 41.3 ± 26.1, and 58.8 ± 21.9 (p<0.01), respectively. Following qualitative analysis, four themes related to nurses' EC burden were derived: physical burden, frequent care needs, delay of other jobs due to EC, and complications. Among them, frequent care needs were found to be the primary factor requiring consideration to reduce nurses' burden.

Conclusion

This research found that EC is one of the most burdensome tasks that nurses want to avoid. To alleviate their burden, effective EC protocol or smart medical devices assisting with EC should be developed.

The Risk of Type 2 Diabetes Mellitus according to Changes in Obesity Status in Late Middle-Aged Adults: A Nationwide Cohort Study of Korea

BACKGRUOUND

Although obesity is a well-known risk factor of type 2 diabetes mellitus (T2DM), there is scant data on discriminating the contribution of previous obesity and recent weight gain on developing T2DM.

METHODS

We analyzed the Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 where Korean residents underwent biennial health checkups. Participants were classified into four groups according to their obesity status (body mass index [BMI] ≥25 kg/m2) before and after turning 50 years old: maintaining normal (MN), becoming obese (BO), becoming normal (BN), and maintaining obese (MO). Cox proportional hazards regression model was used to estimate the risk of T2DM factoring in the covariates age, sex, BMI, presence of impaired fasting glucose or hypertension, family history of diabetes, and smoking status.

RESULTS

A total of 118,438 participants (mean age, 52.5±1.1 years; men, 45.2%) were prospectively evaluated for incident T2DM. A total of 7,339 (6.2%) participants were diagnosed with T2DM during a follow-up period of 4.8±2.6 years. Incidence rates of T2DM per 1,000 person-year were 9.20 in MN, 14.81 in BO, 14.42 in BN, 21.38 in MO. After factoring in covariates, participants in the groups BN (adjusted hazard ratio [aHR], 1.15; 95% confidence interval [CI], 1.04 to 1.27) and MO (aHR, 1.14; 95% CI, 1.06 to 1.24) were at increased risk of developing T2DM compared to MN, whereas BO (hazard ratio, 1.06; 95% CI, 0.96 to 1.17) was not.

CONCLUSION

Having been obese before 50 years old increased the risk of developing T2DM in the future, but becoming obese after 50 did not. Therefore, it is important to maintain normal weight from early adulthood to prevent future metabolic perturbations.

The risk of dementia in multiple sclerosis and neuromyelitis optica spectrum disorder

Introduction

Cognitive impairment is a common feature of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). However, there is a lack of population-based study of dementia risk in these disorders. In the present study, the risk of dementia in MS and NMOSD patients in Republic of Korea was estimated.

Methods

Data analyzed in this study were obtained from the Korean National Health Insurance Service (KNHIS) database between January 2010 and December 2017. The study included 1,347 MS patients and 1,460 NMOSD patients ≥40 years of age who had not been diagnosed with dementia within 1 year prior to the index date. Matched controls were selected based on age, sex, and the presence of hypertension, diabetes mellitus, or dyslipidemia.

Results

In MS and NMOSD patients, the risk of developing any dementia [adjusted hazard ratio (aHR) = 2.34; 95% confidence interval (CI) = 1.84-2.96 and aHR = 2.19; 95% CI = 1.61-3.00, respectively], Alzheimer's disease [AD; aHR = 2.23; 95% confidence interval (CI) = 1.70-2.91 and aHR = 1.99; 95% CI = 1.38-2.88, respectively], and vascular dementia (aHR = 3.75; 95% CI = 1.91-7.35 and aHR = 3.21; 95% CI = 1.47-7.02, respectively) was higher compared with the matched controls. NMOSD patients had a lower risk of any dementia and AD compared with MS patients after adjusting for age, sex, income, hypertension, diabetes, and dyslipidemia (aHR = 0.67 and 0.62).

Conclusion

The risk of dementia increased in MS and NMOSD patients and dementia risk was higher in MS than in NMOSD.

Association of Dexmedetomidine With New-Onset Atrial Fibrillation in Patients With Critical Illness

Importance

Dexmedetomidine is a widely used sedative in the intensive care unit (ICU) and has unique properties that may be associated with reduced occurrence of new-onset atrial fibrillation (NOAF).

Objective

To investigate whether the use of dexmedetomidine is associated with the incidence of NOAF in patients with critical illness.

Design, Setting, and Participants

This propensity score-matched cohort study was conducted using the Medical Information Mart for Intensive Care-IV database, which includes records of patients admitted to the ICU at Beth Israel Deaconess Medical Center in Boston dating 2008 through 2019. Included patients were those aged 18 years or older and hospitalized in the ICU. Data were analyzed from March through May 2022.

Exposure

Patients were divided into 2 groups according to dexmedetomidine exposure: those who received dexmedetomidine within 48 hours after ICU admission (dexmedetomidine group) and those who never received dexmedetomidine (no dexmedetomidine group).

Main Outcomes and Measures

The primary outcome was the occurrence of NOAF within 7 days of ICU admission, as defined by the nurse-recorded rhythm status. Secondary outcomes were ICU length of stay, hospital length of stay, and in-hospital mortality.

Results

This study included 22 237 patients before matching (mean [SD] age, 65.9 [16.7] years; 12 350 male patients [55.5%]). After 1:3 propensity score matching, the cohort included 8015 patients (mean [SD] age, 61.0 [17.1] years; 5240 males [65.4%]), among whom 2106 and 5909 patients were in the dexmedetomidine and no dexmedetomidine groups, respectively. Use of dexmedetomidine was associated with a decreased risk of NOAF (371 patients [17.6%] vs 1323 patients [22.4%]; hazard ratio, 0.80; 95% CI, 0.71-0.90). Although patients in the dexmedetomidine group had longer median (IQR) length of stays in the ICU (4.0 [2.7-6.9] days vs 3.5 [2.5-5.9] days; P < .001) and hospital (10.0 [6.6-16.3] days vs 8.8 [5.9-14.0] days; P < .001), dexmedetomidine was associated with decreased risk of in-hospital mortality (132 deaths [6.3%] vs 758 deaths [12.8%]; hazard ratio, 0.43; 95% CI, 0.36-0.52).

Conclusions and Relevance

This study found that dexmedetomidine was associated with decreased risk of NOAF in patients with critical illness, suggesting that it may be necessary and warranted to evaluate this association in future clinical trials.

Risk of fracture in neuromyelitis optica spectrum disorder and multiple sclerosis: a nationwide cohort study in South Korea

PURPOSE

Interest in fractures in patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) has considerably increased in the last decade. However, few studies have compared the incidence of fractures between patients with MS and NMOSD using a nationwide database. This study aimed to evaluate the differences in the risk of fracture between patients with NMOSD and MS compared to that in healthy controls using cohort data from a Korean nationwide database.

METHODS

In this retrospective cohort study, data from the National Health Insurance Service (NHIS) database from January 2010 to December 2017 were analyzed. A total of 1,217/1,329 patients with MS/NMOSD free of fractures at the index date were included. Matched controls were selected based on age, sex, and the presence of hypertension, diabetes mellitus, and dyslipidemia. The mean follow-up durations after the index date were 4.40/4.08 years for patients with MS/NMOSD and 4.73/4.28 for their matched controls.

RESULTS

The adjusted hazard ratios (aHRs) with 95% confidence intervals of any, hip, and vertebral fractures were 1.81 (1.43-2.28), 3.36 (1.81-6.24), and 2.01 (1.42-2.99) times higher for patients with MS than for controls, respectively, and they were 1.85 (1.47-2.34), 3.82 (2.05-7.11), and 2.84 (1.92-4.21) times higher for patients with NMOSD than for controls, respectively. No significant differences were observed in the incidence of fractures between the MS and NMOSD groups. Patients with MS/NMOSD had a 1.8-fold higher risk of fracture than matched controls, and the risk of hip fracture was especially high (3- to 4-fold higher).

CONCLUSIONS

Clinicians need to regularly assess patients with MS/NMOSD for the risk of fractures and take preventative measures to reduce it.

Impact of Sleep Duration on Decline in Kidney Function in Adult Patients with Hypertension: A Community-Based Prospective Cohort Study

Background

Sleep duration is associated with various health conditions, including chronic kidney disease. However, the association between sleep duration and decline in kidney function in the South Korean population remains unclear. We aimed to investigate the impact of sleep duration on kidney function decline in adult patients with hypertension.

Methods

This cohort study was performed using data obtained from the Korean Genome and Epidemiology Study; 2,837 patients with hypertension who initially had normal kidney function were included. Glomerular filtration rates (GFRs) were estimated at baseline and throughout the 16 years of follow-up. A person was considered to have a decline in kidney function if they had a GFR <60 mL/min/1.73 m². Sleep duration data were obtained through interviewer-assisted questionnaires. Sleep durations were classified as short (<6 hours), normal (≥6 hours but <9 hours), and long (≥9 hours). The Cox proportional hazards model was applied, with adjustments for covariates.

Results

After adjusting for covariates, sleep duration was not associated with a decline in kidney function. However, among men with poorly controlled hypertension at baseline, compared to men with normal sleep durations, men with sleep durations <6 hours had a significantly higher risk of kidney function decline (hazard ratio, 1.56; 95% confidence interval, 1.02–2.36).

Conclusion

Short sleep duration did not seem to be associated with an increased risk of decline in kidney function; however, it may be a risk factor for the decline in kidney function in men with poorly controlled hypertension.

Examining the adoption and implementation of behavioral electronic health records by healthcare professionals based on the clinical adoption framework

Background

While various quantitative studies based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and Technology Acceptance Models (TAM) exist in the general medical sectors, just a few have been conducted in the behavioral sector; they have all been qualitative interview-based studies.

Objective

The purpose of this study is to assess the adoption dimensions of a behavioral electronic health record (EHR) system for behavioral clinical professionals using a modified clinical adoption (CA) research model that incorporates a variety of micro, meso, and macro level factors.

Methods

A questionnaire survey with quantitative analysis approach was used via purposive sampling method. We modified the existing CA framework to be suitable for evaluating the adoption of an EHR system by behavioral clinical professionals. We designed and verified questionnaires that fit into the dimensions of the CA framework. The survey was performed in five US behavioral hospitals, and the adoption factors were analyzed using a structural equation analysis.

Results

We derived a total of seven dimensions, omitting those determined to be unsuitable for behavioral clinical specialists to respond to. We polled 409 behavioral clinical experts from five hospitals. As a result, the ease of use and organizational support had a substantial impact on the use of the behavioral EHR system. Although the findings were not statistically significant, information and service quality did appear to have an effect on the system's ease of use. The primary reported benefit of behavioral EHR system adoption was the capacity to swiftly locate information, work efficiently, and access patient information via a mobile app, which resulted in more time for better care. The primary downside, on the other hand, was an unhealthy reliance on the EHR system.

Conclusions

We demonstrated in this study that the CA framework can be a useful tool for evaluating organizational and social elements in addition to the EHR system's system features. Not only the EHR system's simplicity of use, but also organizational support, should be considered for the effective implementation of the behavioral EHR system.

Trial Registration: The study was approved by the Institutional Review Board of Seoul National University Bundang Hospital (IRB No.: B-1904-534-301).

Risk of Parkinson's disease in multiple sclerosis and neuromyelitis optica spectrum disorder: a nationwide cohort study in South Korea

BACKGROUND

Neurodegeneration is associated with pathogenesis of both multiple sclerosis (MS) and neuromyelitis optica (NMOSD). Parkinson's disease (PD) is a representative neurodegenerative disease, however, whether MS or NMOSD is associated with risk of PD is not known.

METHODS

MS and NMOSD cohorts were collected from the Korean National Health Insurance Service between 1 January 2010 and 31 December 2017, using International Classification of Diseases 10th revision diagnosis codes and information in the Rare Intractable Disease management programme. The PD incidence rate that occurred after a 1-year lag period was calculated and compared with that of a control cohort matched for age, sex, hypertension, diabetes and dyslipidaemia in a 1:5 ratio.

RESULTS

The incidence rates of PD in patients with MS and NMOSD were 3.38 and 1.27 per 1000 person-years, respectively, and were higher than that of their matched control groups. The adjusted HR of PD was 7.73 (95% CI, 3.87 to 15.47) in patients with MS and 2.61 (95% CI, 1.13 to 6.02) in patients with NMOSD compared with matched controls. In both patients with MS and NMOSD, there were no significant differences in relative risk when stratified by sex, age, diabetes, hypertension and dyslipidaemia.

CONCLUSION

The PD risk was higher in patients with MS and NMOSD compared with healthy controls and was particularly high in patients with MS. Further investigations should be performed to determine the pathophysiology and occurrence of PD in patients with MS and NMOSD.

Changes in Diagnostic Performance of Thyroid Cancer Screening before and after the Korean Thyroid Imaging Reporting and Data System Revision

Background: Since the era of “thyroid cancer epidemic,” many Korean academic societies discouraged the use of ultrasonography in healthy individuals and revised the Korean Thyroid Imaging Reporting and Data System to address the overscreening and overdiagnosis issues. This study aimed to evaluate the change in the diagnostic effectiveness of thyroid cancer screening over the last decade.Methods: This single-center, retrospective observational study analyzed the data of 125,962 thyroid nodules obtained during cancer screening at the health promotion center of Seoul National University Bundang Hospital from 2010 to 2019. Only 327 thyroid cancer cases pathologically confirmed by fine-needle aspiration (FNA) were included in the study. The strength of the association between the number of FNA and (1) the number of thyroid cancer diagnoses, (2) the positive predictive values (PPVs), and (3) the difference in PPV from the previous year were evaluated using Pearson’s correlation analysis.Results: The number of thyroid FNA biopsies as well as the thyroid cancer diagnoses decreased from 2010 to 2019 (166 to 48 [-71.1%] vs. 43 to 22 [-48.8%]). The PPV of FNA biopsies increased from 25.9% to 45.8% (+76.8%) and was negatively correlated with the number of FNA biopsies performed (R=-0.87, P<0.001). The difference in PPV from the previous year increased similarly but without statistical significance (R=-0.59, P=0.09).Conclusion: The diagnostic efficiency of thyroid cancer screening has increased over the last decade, as evidencedby the increasing PPV of FNA biopsies.

Recent trends of healthcare information and communication technologies in pediatrics: a systematic review

As information communication technology (ICT) has advanced, the healthcare industry has embraced it to reduce medical costs, improve health outcomes, and increase patient satisfaction. Healthcare ICT revolutionizes pediatric healthcare. This study aimed to categorize and synthesize findings from the literature regarding the application of ICT in pediatric patients. This systematic review is based on a comprehensive search of Embase, MEDLINE, and Google Scholar. Study selection and coding were performed independently by 2 researchers, followed by narrative categorization. To reflect current trends in ICT for pediatrics, we adopted the Hype cycle technology classification developed by the advisory and information technology firm, Gartner, and the classification of digital health interventions by the World Health Organization. This study included a total of 135 studies. The analysis revealed 7 main types of ICT for pediatrics: (1) telehealth (39 papers), (2) precision medicine (2 papers), (3) automated decision support systems (17 papers), (4) electronic health records (7 papers), (5) patient portals (7 papers), (6) artificial intelligence (AI) (39 papers), and (7) mobile and wearable technologies (20 papers). In particular, we consistently found references to ICT for pediatrics as well as changing and improving healthcare for children. Further studies are required to determine how we can improve ICT productivity for pediatrics, particularly through AI. This study's results will help healthcare delivery organizations and technology companies consider the future direction of pediatric healthcare.

Neuropsychological adverse drug reactions of Remdesivir: analysis using VigiBase, the WHO global database of individual case safety reports

OBJECTIVE

Although remdesivir (GS-5734) has recently demonstrated clinical benefits against the pandemic outbreak of coronavirus disease 2019 (COVID-19), neuropsychological adverse reactions (ADRs) remain to be examined in real-world settings. Therefore, we aimed to identify and characterize the neuropsychological ADRs associated with remdesivir use.

MATERIALS AND METHODS

We obtained data for this international pharmacovigilance cohort study from individual case safety reports (ICSRs) in a World Health Organization database (VigiBase) from the first report on remdesivir on February 17, 2020, until August 30, 2020 (n=1,403,532). ADRs reported to be relevant to remdesivir were compared with the full database by using a Bayesian neural network method to calculate the information component (IC).

RESULTS

A total of 2,107 reported cases of neuropsychological ADRs suspected to be associated with remdesivir were identified from among all ICSRs in the database during the observation period. Although 108 neuropsychological ADRs (64 neurologic events and 44 psychologic events) were reported in association with the medication, no statistically significant pharmacovigilance signal could be detected; the IC025 value was negative for all of the neuropsychological dysfunctions (anxiety [n=13, 0.62%], seizures [n=12, 0.57%], lethargy [n=6, 0.28%], agitation [n=5, 0.25%], cerebral infarction [n=3, 0.14%], ischemic stroke [n=3, 0.14%], and hemiparesis [n=3, 0.14%]).

CONCLUSIONS

Our study demonstrates that remdesivir, a novel drug applied to the treatment of COVID-19, does not have a significant association with adverse neurologic or psychiatric reactions in the real-world setting.

Lactobacillus intestinalis YT2 restores the gut microbiota and improves menopausal symptoms in ovariectomized rats

There are many studies focusing on the alleviation of menopausal symptoms; however, little is known about the role of gut microorganisms in menopausal symptoms. Ovariectomized (OVX) rats were administered a novel strain (YT2) of Lactobacillus intestinalis (a species with significantly reduced abundance in OVX rats) and the potential probiotic effect on the improvement of menopausal symptoms was evaluated. Of note, the gut microbial composition completely shifted after ovariectomy in rats. Treatment with L. intestinalis YT2 significantly alleviated menopausal symptoms, such as increased fat mass, decreased bone mineral density, increased pain sensitivity, depression-like behaviour, and cognitive impairment. Additionally, the administration of L. intestinalis YT2 restored the intestinal microbial composition, including an increased Firmicutes/Bacteroides ratio. L. intestinalis YT2 also promoted gut barrier integrity by increasing the mRNA levels of tight junction-related markers. In conclusion, L. intestinalis YT2 treatment alleviated menopausal symptoms via the modulation of the gut microbiota. Importantly, these results suggest that L. intestinalis YT2 should be considered as a therapeutic probiotic agent for menopausal women.

Mechanism Design of Health Care Blockchain System Token Economy: Development Study Based on Simulated Real-World Scenarios

Background

Despite the fact that the adoption rate of electronic health records has increased dramatically among high-income nations, it is still difficult to properly disseminate personal health records. Token economy, through blockchain smart contracts, can better distribute personal health records by providing incentives to patients. However, there have been very few studies regarding the particular factors that should be considered when designing incentive mechanisms in blockchain.

Objective

The aim of this paper is to provide 2 new mathematical models of token economy in real-world scenarios on health care blockchain platforms.

Methods

First, roles were set for the health care blockchain platform and its token flow. Second, 2 scenarios were introduced: collecting life-log data for an incentive program at a life insurance company to motivate customers to exercise more and recruiting participants for clinical trials of anticancer drugs. In our 2 scenarios, we assumed that there were 3 stakeholders: participants, data recipients (companies), and data providers (health care organizations). We also assumed that the incentives are initially paid out to participants by data recipients, who are focused on minimizing economic and time costs by adapting mechanism design. This concept can be seen as a part of game theory, since the willingness-to-pay of data recipients is important in maintaining the blockchain token economy. In both scenarios, the recruiting company can change the expected recruitment time and number of participants. Suppose a company considers the recruitment time to be more important than the number of participants and rewards. In that case, the company can increase the time weight and adjust cost. When the reward parameter is fixed, the corresponding expected recruitment time can be obtained. Among the reward and time pairs, the pair that minimizes the company’s cost was chosen. Finally, the optimized results were compared with the simulations and analyzed accordingly.

Results

To minimize the company’s costs, reward–time pairs were first collected. It was observed that the expected recruitment time decreased as rewards grew, while the rewards decreased as time cost grew. Therefore, the cost was represented by a convex curve, which made it possible to obtain a minimum—an optimal point—for both scenarios. Through sensitivity analysis, we observed that, as the time weight increased, the optimized reward increased, while the optimized time decreased. Moreover, as the number of participants increased, the optimization reward and time also increased.

Conclusions

In this study, we were able to model the incentive mechanism of blockchain based on a mechanism design that recruits participants through a health care blockchain platform. This study presents a basic approach to incentive modeling in personal health records, demonstrating how health care organizations and funding companies can motivate one another to join the platform.

Fruit Intake and Changes of Cardio-Metabolic Risk Factors in People with Obesity

BACKGROUND

This study aimed to explore the relationship between fruit intake, changes in fruit intake, and changes in cardiometabolic factors in people with obesity.

METHODS

A total of 21,270 subjects (8,718 men, 12,552 women) aged 40 years and over, from the Korean-based Genome and Epidemiology Study, were followed up for an average of 4.4 years. Fruit intake was assessed using a food frequency questionnaire at baseline and the second follow-up. The beta coefficient and confidence intervals for changes in cardiometabolic risk factors according to fruit consumption were calculated using a linear regression model.

RESULTS

In men, the abdominal circumference decreased with changes in fruit intake (P=0.029). Fruit intake and increased fruit intake in men were associated with a lower systolic blood pressure (P=0.012 and P=0.02, respectively) and lower triglyceride levels (P=0.002 and P<0.001, respectively). In women, abdominal circumference decreased with both fruit intake and increased fruit intake (P<0.001 and P=0.013, respectively). Systolic blood pressure and triglycerides tended to decrease only with fruit intake (P=0.048 and P<0.001, respectively). Unlike in men, fasting blood glucose tended to decrease in women with both fruit intake and increased fruit intake (P=0.011 and P=0.005, respectively).

CONCLUSION

Fruit intake and increased fruit intake may have beneficial effects on cardiometabolic risk factors among individuals who are obese.

Patient-Level Cancer Prediction Models From a Nationwide Patient Cohort: Model Development and Validation

Background

Nationwide population-based cohorts provide a new opportunity to build automated risk prediction models at the patient level, and claim data are one of the more useful resources to this end. To avoid unnecessary diagnostic intervention after cancer screening tests, patient-level prediction models should be developed.

Objective

We aimed to develop cancer prediction models using nationwide claim databases with machine learning algorithms, which are explainable and easily applicable in real-world environments.

Methods

As source data, we used the Korean National Insurance System Database. Every Korean in ≥40 years old undergoes a national health checkup every 2 years. We gathered all variables from the database including demographic information, basic laboratory values, anthropometric values, and previous medical history. We applied conventional logistic regression methods, light gradient boosting methods, neural networks, survival analysis, and one-class embedding classifier methods to effectively analyze high dimension data based on deep learning–based anomaly detection. Performance was measured with area under the curve and area under precision recall curve. We validated our models externally with a health checkup database from a tertiary hospital.

Results

The one-class embedding classifier model received the highest area under the curve scores with values of 0.868, 0.849, 0.798, 0.746, 0.800, 0.749, and 0.790 for liver, lung, colorectal, pancreatic, gastric, breast, and cervical cancers, respectively. For area under precision recall curve, the light gradient boosting models had the highest score with values of 0.383, 0.401, 0.387, 0.300, 0.385, 0.357, and 0.296 for liver, lung, colorectal, pancreatic, gastric, breast, and cervical cancers, respectively.

Conclusions

Our results show that it is possible to easily develop applicable cancer prediction models with nationwide claim data using machine learning. The 7 models showed acceptable performances and explainability, and thus can be distributed easily in real-world environments.

User Perspectives on Barriers and Facilitators to the Implementation of Electronic Health Records in Behavioral Hospitals: Qualitative Study

BACKGROUND

Despite the rapid adoption of electronic health records (EHRs) resulting from the reimbursement program of the US government, EHR adoption in behavioral hospitals is still slow, and there remains a lack of evidence regarding barriers and facilitators to the implementation of mental health care EHRs.

OBJECTIVE

The aim of this study is to analyze the experience of mental health professionals to explore the perceived barriers, facilitators, and critical ideas influencing the implementation and usability of a mental health care EHR.

METHODS

In this phenomenological qualitative study, we interviewed physicians, nurses, pharmacists, mental health clinicians, and administrative professionals separately at 4 behavioral hospitals in the United States. We conducted semistructured interviews (N=43) from behavioral hospitals involved in the adoption of the mental health care EHR. Purposeful sampling was used to maximize the diversity. Transcripts were coded and analyzed for emergent domains. An exploratory data analysis was conducted.

RESULTS

Content analyses revealed 7 barriers and 4 facilitators. The most important barriers to implementing the mental health care EHR were the low levels of computer proficiency among nurses, complexity of the system, alert fatigue, and resistance because of legacy systems. This led to poor usability, low acceptability, and distrust toward the system. The major facilitators to implementing the mental health care EHR were well-executed training programs, improved productivity, better quality of care, and the good usability of the mental health care EHR.

CONCLUSIONS

Health care professionals expected to enhance their work productivity and interprofessional collaboration by introducing the mental health care EHR. Routine education for end users is an essential starting point for the successful implementation of mental health care EHR electronic decision support. When adopting the mental health care EHR, managers need to focus on common practices in behavioral hospitals, such as documenting structured data in their organizations and adopting a seamless workflow of mental health care into the system.

A standardized glucose-insulin-potassium infusion protocol in surgical patients: Use of real clinical data from a clinical data warehouse

AIMS

We evaluated the clinical usefulness of a new unified glucose-insulin-potassium (GIK) regimen in a general surgical department.

METHODS

Surgical patients treated under the previous diverse GIK regimens (September 2016 to August 2017) and the new unified GIK regimen (September 2017 to August 2018) were identified in records of the Clinical Data Warehouse of Seoul National University Bundang Hospital. Serial and area under the curve (AUC) glucose levels, and percentages of time within the target glucose levels were compared in propensity score matched patients in the diverse GIK regimen and in the unified GIK regimen (n = 227 in each group).

RESULTS

The AUC of glucose at 6 h and 12 h was lower under the unified GIK regimen than the diverse GIK regimen. The percentage of target glucose levels was higher in the unified GIK regimen compared to the diverse GIK regimen (81.5% vs. 75.0%, P = 0.026), but the occurrence of hypoglycaemia did not differ significantly between groups.

CONCLUSIONS

The unified GIK regimen was more effective than the diverse GIK regimen for glycaemic control and did not increase the number of patients developing hypoglycaemia. This validated written GIK regimen can be safely used in a general surgical department.

Tipping the immunostimulatory and inhibitory DAMP balance to harness immunogenic cell death

Induction of tumor cell death is the therapeutic goal for most anticancer drugs. Yet, a mode of drug-induced cell death, known as immunogenic cell death (ICD), can propagate antitumoral immunity to augment therapeutic efficacy. Currently, the molecular hallmark of ICD features the release of damage-associated molecular patterns (DAMPs) by dying cancer cells. Here, we show that gemcitabine, a standard chemotherapy for various solid tumors, triggers hallmark immunostimualtory DAMP release (e.g., calreticulin, HSP70, and HMGB1); however, is unable to induce ICD. Mechanistic studies reveal gemcitabine concurrently triggers prostaglandin E2 release as an inhibitory DAMP to counterpoise the adjuvanticity of immunostimulatory DAMPs. Pharmacological blockade of prostaglandin E2 biosythesis favors CD103+ dendritic cell activation that primes a Tc1-polarized CD8+ T cell response to bolster tumor rejection. Herein, we postulate that an intricate balance between immunostimulatory and inhibitory DAMPs could determine the outcome of drug-induced ICD and pose COX-2/prostaglandin E2 blockade as a strategy to harness ICD.

Perspectives of Patients, Health Care Professionals, and Developers Toward Blockchain-Based Health Information Exchange: Qualitative Study

Background

Although the electronic health record system adoption rate has reached 96% in the United States, implementation and usage of health information exchange (HIE) is still lagging behind. Blockchain has come into the spotlight as a technology to solve this problem. However, there have been no studies assessing the perspectives of different stakeholders regarding blockchain-based patient-centered HIE.

Objective

The objective of this study was to analyze the awareness among patients, health care professionals, and information technology developers toward blockchain-based HIE, and compare their different perspectives related to the platform using a qualitative research methodology.

Methods

In this qualitative study, we applied grounded theory and the Promoting Action on Research Implementation in the Health Service (PARiHS) framework. We interviewed 7 patients, 7 physicians, and 7 developers, for a total of 21 interviewees.

Results

Regarding the leakage of health information, the patient group did not have concerns in contrast to the physician and developer groups. Physicians were particularly concerned about the fact that errors in the data cannot be easily fixed due to the nature of blockchain technology. Patients were not against the idea of providing information for clinical trials or research institutions. They wished to be provided with the results of clinical research rather than being compensated for providing data. The developers emphasized that blockchain must be technically mature before it can be applied to the health care scene, and standards of medical information to be exchanged must first be established.

Conclusions

The three groups’ perceptions of blockchain were generally positive about the idea of patients having the control of sharing their own health information. However, they were skeptical about the cooperation among various institutions and implementation for data standardization in the establishment process, in addition to how the service will be employed in practice. Taking these factors into consideration during planning, development, and operation of a platform will contribute to establishing practical treatment plans and tracking in a more convenient manner for both patients and physicians. Furthermore, it will help expand the related research and health management industry based on blockchain.

Barriers and facilitators to implementation of nationwide electronic health records in the Russian Far East: A qualitative analysis

BACKGROUND

Electronic health records (EHRs) are transforming and revolutionizing the healthcare industry. However, whereas developed countries have a high EHR penetration rate, adoption of EHRs in developing countries is lagging behind. Recently, the Korean and Russian governments have been pursuing economic cooperation in the Russian Far East. Thus, since 2009, Russia's EHR market and healthcare system have been maturing in tandem.

OBJECTIVE

To qualitatively investigate and analyze the current status of EHRs in the Russian Far East and derive implementation plans for nationwide EHRs.

METHODS

A qualitative analysis based on semi-structured interviews with healthcare professionals and administrative officers in the Russian Far East was conducted to illuminate the current status of EHRs and to collect various perspectives on barriers and facilitators to implementation.

RESULTS

The analysis revealed six major barriers and five major facilitators for implementation of nationwide EHRs in the Russian Far East. The barriers include lack of communications, an insufficient system development environment, poor adoption of standard terminology, poor infrastructure, resistance to a new system, and poor functionality. Facilitators include strategic government planning, centrally managed systems, health information exchange, willingness to use new functions, and well-established work processes.

CONCLUSIONS

This study's results, along with the experiences of developed countries that have already successfully introduced EHRs, will help support successful introduction of EHRs in the Russian Far East.

Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation

BACKGROUND

The COVID-19 pandemic has caused major disruptions worldwide since March 2020. The experience of the 1918 influenza pandemic demonstrated that decreases in the infection rates of COVID-19 do not guarantee continuity of the trend.

OBJECTIVE

The aim of this study was to develop a precise spread model of COVID-19 with time-dependent parameters via deep learning to respond promptly to the dynamic situation of the outbreak and proactively minimize damage.

METHODS

In this study, we investigated a mathematical model with time-dependent parameters via deep learning based on forward-inverse problems. We used data from the Korea Centers for Disease Control and Prevention (KCDC) and the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University for Korea and the other countries, respectively. Because the data consist of confirmed, recovered, and deceased cases, we selected the susceptible-infected-recovered (SIR) model and found approximated solutions as well as model parameters. Specifically, we applied fully connected neural networks to the solutions and parameters and designed suitable loss functions.

RESULTS

We developed an entirely new SIR model with time-dependent parameters via deep learning methods. Furthermore, we validated the model with the conventional Runge-Kutta fourth order model to confirm its convergent nature. In addition, we evaluated our model based on the real-world situation reported from the KCDC, the Korean government, and news media. We also crossvalidated our model using data from the CSSE for Italy, Sweden, and the United States.

CONCLUSIONS

The methodology and new model of this study could be employed for short-term prediction of COVID-19, which could help the government prepare for a new outbreak. In addition, from the perspective of measuring medical resources, our model has powerful strength because it assumes all the parameters as time-dependent, which reflects the exact status of viral spread.

A Predictive Model Based on Machine Learning for the Early Detection of Late-Onset Neonatal Sepsis: Development and Observational Study

BACKGROUND

Neonatal sepsis is associated with most cases of mortalities and morbidities in the neonatal intensive care unit (NICU). Many studies have developed prediction models for the early diagnosis of bloodstream infections in newborns, but there are limitations to data collection and management because these models are based on high-resolution waveform data.

OBJECTIVE

The aim of this study was to examine the feasibility of a prediction model by using noninvasive vital sign data and machine learning technology.

METHODS

We used electronic medical record data in intensive care units published in the Medical Information Mart for Intensive Care III clinical database. The late-onset neonatal sepsis (LONS) prediction algorithm using our proposed forward feature selection technique was based on NICU inpatient data and was designed to detect clinical sepsis 48 hours before occurrence. The performance of this prediction model was evaluated using various feature selection algorithms and machine learning models.

RESULTS

The performance of the LONS prediction model was found to be comparable to that of the prediction models that use invasive data such as high-resolution vital sign data, blood gas estimations, blood cell counts, and pH levels. The area under the receiver operating characteristic curve of the 48-hour prediction model was 0.861 and that of the onset detection model was 0.868. The main features that could be vital candidate markers for clinical neonatal sepsis were blood pressure, oxygen saturation, and body temperature. Feature generation using kurtosis and skewness of the features showed the highest performance.

CONCLUSIONS

The findings of our study confirmed that the LONS prediction model based on machine learning can be developed using vital sign data that are regularly measured in clinical settings. Future studies should conduct external validation by using different types of data sets and actual clinical verification of the developed model.

Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis

Background

Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts.

Objective

In order to improve MDSS functionality, we must understand what factors users consider essential for the successful implementation of an MDSS into their clinical setting. This study followed the implementation process for an MDSS within a comprehensive EHR system and analyzed the relevant barriers and facilitators.

Methods

A mixed research methodology was adopted. Data from a structured survey and 15 in-depth interviews were integrated. Structural equation modeling was conducted for quantitative analysis of factors related to user adoption of MDSS. Qualitative analysis based on semistructured interviews with physicians was conducted to collect various opinions on MDSS implementation.

Results

Quantitative analysis revealed that physicians’ expectations regarding ease of use and performance improvement are crucial. Qualitative analysis identified four significant barriers to MDSS implementation: alert fatigue, lack of accuracy, poor user interface design, and lack of customizability.

Conclusions

This study revealed barriers and facilitators to the implementation of MDSS. The findings can be applied to upgrade MDSS in the future.

Risk Factors of Cardiovascular Disease according to Alcohol Behavioral Change after Cancer Diagnosis

Background

Problem drinking increases the incidence of all-cause mortality and specific cancers, and persistent drinking is associated with cardiovascular disease in certain cancer survivors. This study analyzed the cardiovascular risk factors before and after diagnosis in Korean cancer survivors.

Methods

Data for the period between 2002 and 2013 were collected from the National Health Insurance Service Health-Examinee Cohort Database. Among the 27,835 patients included, those with moderate alcohol consumption before and after cancer diagnosis were excluded. Problem drinking was defined as males under 65 years consuming over 14 glasses a week, and males over 65 years or females consuming over seven glasses a week. A t-test, chi-square test, and linear regression analysis were performed for differences in cardiovascular risk factors and differences according to cancer types.

Results

There was a difference in the body mass index, systolic and diastolic blood pressure, and total cholesterol among patients who became moderate drinkers after diagnosis, but fasting blood glucose did not show any significant changes. Risk factors for cardiovascular disease were analyzed in patients with liver, stomach, rectal, and breast cancer with improved drinking behavior, and there were significant differences in body mass index, systolic and diastolic blood pressure, fasting blood glucose, and total cholesterol in stomach cancer patients.

Conclusion

Moderate drinking can lower cardiovascular risk in cancer survivors, and among the many drinking-related cancers, stomach cancer patients demonstrated significantly reduced cardiovascular risk factors.

Development of Comprehensive Personal Health Records Integrating Patient-Generated Health Data Directly From Samsung S-Health and Apple Health Apps: Retrospective Cross-Sectional Observational Study

BACKGROUND

Patient-generated health data (PGHD), especially lifelog data, are important for managing chronic diseases. Additionally, personal health records (PHRs) have been considered an effective tool to engage patients more actively in the management of their chronic diseases. However, no PHRs currently integrate PGHD directly from Samsung S-Health and Apple Health apps.

OBJECTIVE

The purposes of this study were (1) to demonstrate the development of an electronic medical record (EMR)-tethered PHR system (Health4U) that integrates lifelog data from Samsung S-Health and Apple Health apps and (2) to explore the factors associated with the use rate of the functions.

METHODS

To upgrade conventional EMR-tethered PHRs, a task-force team (TFT) defined the functions necessary for users. After implementing a new system, we enrolled adults aged 19 years and older with prior experience of accessing Health4U in the 7-month period after November 2017, when the service was upgraded.

RESULTS

Of the 17,624 users, 215 (1.22%) integrated daily steps data, 175 (0.99%) integrated weight data, 51 (0.29%) integrated blood sugar data, and 90 (0.51%) integrated blood pressure data. Overall, 61.95% (10,919/17,624) had one or more chronic diseases. For integration of daily steps data, 48.3% (104/215) of patients used the Apple Health app, 43.3% (93/215) used the S-Health app, and 8.4% (18/215) entered data manually. To retrieve medical documentation, 324 (1.84%) users downloaded PDF files and 31 (0.18%) users integrated their medical records into the Samsung S-Health app via the Consolidated-Clinical Document Architecture download function. We found a consistent increase in the odds ratios for PDF downloads among patients with a higher number of chronic diseases. The age groups of ≥60 years and ≥80 years tended to use the download function less frequently than the others.

CONCLUSIONS

This is the first study to examine the factors related to integration of lifelog data from Samsung S-Health and Apple Health apps into EMR-tethered PHRs and factors related to the retrieval of medical documents from PHRs. Our findings on the lifelog data integration can be used to design PHRs as a platform to integrate lifelog data in the future.

Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data

Background

Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening tools, such as Health Risk Appraisal, are restricted in their achievement this goal due to their limitations, such as static characteristics, accessibility, and generalizability. Hypertension is one of the most important chronic diseases requiring management via the nationwide health maintenance program, and health care providers should inform patients about their risks of a complication caused by hypertension.

Objective

Our goal was to develop and compare machine learning models predicting high-risk vascular diseases for hypertensive patients so that they can manage their blood pressure based on their risk level.

Methods

We used a 12-year longitudinal dataset of the nationwide sample cohort, which contains the data of 514,866 patients and allows tracking of patients’ medical history across all health care providers in Korea (N=51,920). To ensure the generalizability of our models, we conducted an external validation using another national sample cohort dataset, comprising one million different patients, published by the National Health Insurance Service. From each dataset, we obtained the data of 74,535 and 59,738 patients with essential hypertension and developed machine learning models for predicting cardiovascular and cerebrovascular events. Six machine learning models were developed and compared for evaluating performances based on validation metrics.

Results

Machine learning algorithms enabled us to detect high-risk patients based on their medical history. The long short-term memory-based algorithm outperformed in the within test (F1-score=.772, external test F1-score=.613), and the random forest-based algorithm of risk prediction showed better performance over other machine learning algorithms concerning generalization (within test F1-score=.757, external test F1-score=.705). Concerning the number of features, in the within test, the long short-term memory-based algorithms outperformed regardless of the number of features. However, in the external test, the random forest-based algorithm was the best, irrespective of the number of features it encountered.

Conclusions

We developed and compared machine learning models predicting high-risk vascular diseases in hypertensive patients so that they may manage their blood pressure based on their risk level. By relying on the prediction model, a government can predict high-risk patients at the nationwide level and establish health care policies in advance.

Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-Arm Randomized Controlled Trial

Background

Although using the technologies for a variety of chronic health conditions such as personal health record (PHR) is reported to be acceptable and useful, there is a lack of evidence on the associations between the use of the technologies and the change of health outcome and patients’ response to a digital health app.

Objective

This study aimed to examine the impact of the use of PHR and wearables on health outcome improvement and sustained use of the health app that can be associated with patient engagement.

Methods

We developed an Android-based mobile phone app and used a wristband-type activity tracker (Samsung Charm) to collect data on health-related daily activities from individual patients. Dietary record, daily step counts, sleep log, subjective stress amount, blood pressure, and weight values were recorded. We conducted a prospective randomized clinical trial across 4 weeks on those diagnosed with obstructive sleep apnea (OSA) who had visited the outpatient clinic of Seoul National University Bundang Hospital. The trial randomly assigned 60 patients to 3 subgroups including 2 intervention groups: (1) mobile app and wearable device users (n=20), (2) mobile app–only users (n=20), and (3) controls (n=20). The primary outcome measure was weight change. Body weights before and after the trial were recorded and analyzed during clinic visits. Changes in OSA–related respiratory parameters such as respiratory disturbance, apnea-hypopnea, and oxygenation desaturation indexes and snoring comprised the secondary outcome and were analyzed for each participant.

Results

We collected the individual data for each group during the trial, specifically anthropometric measurement and laboratory test results for health outcomes, and the app usage logs for patient response were collected and analyzed. The body weight showed a significant reduction in the 2 intervention groups after intervention, and the mobile app–only group showed more weight loss compared with the controls (P=.01). There were no significant changes in sleep-related health outcomes. From a patient response point of view, the average daily step counts (8165 steps) from the app plus wearable group were significantly higher than those (6034 steps) from the app-only group because they collected step count data from different devices (P=.02). The average rate of data collection was not different in physical activity (P=.99), food intake (P=.98), sleep (P=.95), stress (P=.70), and weight (P=.90) in the app plus wearable and app-only groups, respectively.

Conclusions

We tried to integrate PHR data that allow clinicians and patients to share lifelog data with the clinical workflow to support lifestyle interventions. Our results suggest that a PHR–based intervention may be successful in losing body weight and improvement in lifestyle behavior.

Trial Registration

ClinicalTrials.gov NCT03200223; https://clinicaltrials.gov/ct2/show/NCT03200223 (Archived by WebCite at http://www.webcitation.org/74baZmnCX).

Comparison of the Marginal Utility and Disease Burden of Hearing Loss and Other Chronic Diseases

Background

Compared with other chronic diseases, hearing loss is generally overlooked from the perspective of disease burden. However, hearing loss is emerging as an important issue in the current society. The objective of this study was to investigate disease burdens and marginal utilities associated with hearing loss and other chronic diseases.

Methods

This study analyzed the cross-sectional data of 32,986 participants aged 19 years and older who completed the Korea National Health and Nutrition Examination Surveys between 2009 and 2013. Additionally, this study used the pure tone audiometric test, European Quality of Life-Five Dimensions Questionnaire, and chronic disease status. The data were analyzed using a multiple linear regression method.

Results

The data of 23,297 people who underwent a pure tone audiogram and completed the European Quality of Life-Five Dimensions Questionnaire were used in this analysis. The marginal utility of hearing loss ranked fifth among nine chronic diseases. The estimated loss of quality-adjusted life years associated with hearing loss was -93.69 years per 100,000 people, which is similar to other chronic diseases.

Conclusion

This study assessed the marginal utilities and public burdens of hearing loss and eight chronic diseases in a South Korean population. Although the values may vary depending on country and race, this study may provide an indispensable foundation for more detailed studies on hearing loss.

Clinical implications of controlled attenuation parameter in a health check-up cohort

BACKGROUND & AIMS

Evaluation of the controlled attenuation parameter (CAP) is a promising noninvasive method for assessing hepatic steatosis. Despite the increasing reliability of the CAP for assessing steatosis in subjects with chronic liver disease, few studies have evaluated the CAP in asymptomatic subjects without overt liver disease. Therefore, we aimed to evaluate the usefulness of the CAP for a health check-up population.

METHODS

We enrolled subjects who underwent abdominal ultrasonography (US), FibroScan (Echosens, France) and blood sampling during medical health check-ups. The CAP was measured using FibroScan, and increased CAP was defined as CAP ≥ 222 dB/m.

RESULTS

A total of 1133 subjects were included; 589 subjects (52.0%) had fatty liver based on US, and 604 subjects (53.3%) had increased CAP. Increased CAP was significantly associated with metabolic abnormalities, including higher body mass index (BMI)[odds ratio (OR) = 1.33;95% confidence interval (CI),1.24-1.43; P < .001], higher alanine aminotransferase (ALT) (OR = 1.02; 95% CI, 1.01-1.04; P = .003), higher insulin (OR = 1.04; 95% CI, 1.00-1.08; P = .037), higher triglyceride (OR = 1.00; 95% CI, 1.00-1.01; P = 0.042) and older age (OR = 1.02; 95% CI, 1.00-1.03; P = .05). Furthermore, a comparison of clinical parameters among three groups (normal vs no fatty liver by US but increased CAP vs fatty liver based on US) revealed that metabolic parameters, including blood pressure, BMI, waist circumference, aspartate aminotransferase (AST), ALT, triglycerides, fasting glucose, uric acid, insulin, homeostasis model assessment-estimated insulin resistance and liver stiffness measurements, gradually increased across the three groups (all P < .001).

CONCLUSIONS

In conclusion, increased CAP could be an early indicator of fatty liver disease with metabolic abnormalities that manifests even before a sonographic fatty change appears.

Impact of an Electronic Health Record-Integrated Personal Health Record on Patient Participation in Health Care: Development and Randomized Controlled Trial of MyHealthKeeper

Background

Personal health record (PHR)–based health care management systems can improve patient engagement and data-driven medical diagnosis in a clinical setting.

Objective

The purpose of this study was (1) to demonstrate the development of an electronic health record (EHR)–tethered PHR app named MyHealthKeeper, which can retrieve data from a wearable device and deliver these data to a hospital EHR system, and (2) to study the effectiveness of a PHR data-driven clinical intervention with clinical trial results.

Methods

To improve the conventional EHR-tethered PHR, we ascertained clinicians’ unmet needs regarding PHR functionality and the data frequently used in the field through a cocreation workshop. We incorporated the requirements into the system design and architecture of the MyHealthKeeper PHR module. We constructed the app and validated the effectiveness of the PHR module by conducting a 4-week clinical trial. We used a commercially available activity tracker (Misfit) to collect individual physical activity data, and developed the MyHealthKeeper mobile phone app to record participants’ patterns of daily food intake and activity logs. We randomly assigned 80 participants to either the PHR-based intervention group (n=51) or the control group (n=29). All of the study participants completed a paper-based survey, a laboratory test, a physical examination, and an opinion interview. During the 4-week study period, we collected health-related mobile data, and study participants visited the outpatient clinic twice and received PHR-based clinical diagnosis and recommendations.

Results

A total of 68 participants (44 in the intervention group and 24 in the control group) completed the study. The PHR intervention group showed significantly higher weight loss than the control group (mean 1.4 kg, 95% CI 0.9-1.9; P<.001) at the final week (week 4). In addition, triglyceride levels were significantly lower by the end of the study period (mean 2.59 mmol/L, 95% CI 17.6-75.8; P=.002).

Conclusions

We developed an innovative EHR-tethered PHR system that allowed clinicians and patients to share lifelog data. This study shows the effectiveness of a patient-managed and clinician-guided health tracker system and its potential to improve patient clinical profiles.

Trial Registration

ClinicalTrials.gov NCT03200119; https://clinicaltrials.gov/ct2/show/NCT03200119 (Archived by WebCite at http://www.webcitation.org/6v01HaCdd)

Osteoarthritis Affects Health-Related Quality of Life in Korean Adults with Chronic Diseases: The Korea National Health and Nutritional Examination Surveys 2009-2013

Background

Osteoarthritis (OA) is a chronic disease that commonly afflicts the elderly. This disease reduces the health-related quality of life (HRQoL) and causes a significant social burden. Whether the effect of coexisting chronic conditions on HRQoL varies according to the presence of OA remains unclear. Therefore, this study aimed to investigate this notion.

Methods

A total of 13,395 participants were identified from the 2009–2013 Korean National Health and Nutrition Examination Survey for analysis. HRQoL was assessed using the European quality of life-5 dimensions (EQ-5D) index. Patients with OA were defined as those diagnosed by a physician or those who displayed both, symptoms and radiological findings consistent with OA at the time of the survey. Associations between OA and 8 chronic conditions were tested using regression analysis.

Results

The EQ-5D index was lower in patients with OA than in those without (mean difference, −0.145; 95% confidence interval [CI], −0.138 to −0.151; P<0.001). Most patients with OA and chronic conditions showed a lower score than those without. EQ-5D was particularly lower in OA patients with hypertension, dyslipidemia, stroke, and renal failure. The estimated β coefficient for the interaction term was significant in renal failure (−0.034; 95% CI, −0.055 to −0.012), after adjusting for demographic and socio-economic variables.

Conclusion

OA significantly affects HRQoL of Korean elderly individuals alone or when combined with other conditions. OA combined with renal failure is particularly detrimental. These results indicate the importance of managing OA, which is an underestimated disease in public health surveys.

Association Between the Awareness of Dyslipidemia and Health Behavior for Control of Lipid Levels Among Korean Adults with Dyslipidemia

Background

Dyslipidemia is a major risk factor contributing to cardiovascular disease and its prevalence is steadily rising. Although screening tests are readily accessible, dyslipidemia remains undertreated. Evaluating health behavior patterns after diagnosis may help improve lifestyle interventions for the management of dyslipidemia.

Methods

Data from the fifth Korean National Health and Nutrition Examination Survey 2010–2012 were used. A total of 6,624 dyslipidemia patients over 20 years old were included according to National Cholesterol Education Program-Adult Treatment Panel III guidelines. Logistic regression analysis was completed using a weighted method to determine whether awareness of dyslipidemia was associated with health behavior. Health behavior was divided into two categories: behavioral factors (smoking, alcohol consumption, exercise) and nutritional factors (adequate intake of fiber, carbohydrate, fat, protein).

Results

There were no significant differences in health behavior among dyslipidemia patients according to awareness after adjustment for covariates, diabetes and hypertension. Awareness in women was associated with decreased smoking (odds ratio [OR], 0.55; 95% confidence interval [CI], 0.32 to 0.94), but when adjusted for diabetes and hypertension the result was not significant (OR, 0.61; 95% CI, 0.35 to 1.06). The same pattern applied to intake of carbohydrate in men (OR, 1.28; 95% CI, 0.99 to 1.67) and protein in women (OR, 1.22; 95% CI, 0.98 to 1.50). In subgroup analysis, awareness of dyslipidemia in men without hypertension or diabetes was associated with adequate intake of carbohydrate (OR, 1.70; 95% CI, 1.06 to 2.72).

Conclusion

Increasing awareness alone may not be enough to improve healthy behavior in patients with dyslipidemia. Efforts including patient education and counseling through a multi-team approach may be required.

Support for Sustainable Use of Personal Health Records: Understanding the Needs of Users as a First Step Towards Patient-Driven Mobile Health

Background

The tethering of a personal health record (PHR) to an electronic medical record (EMR) may serve as a catalyst in accelerating the distribution of integrated PHRs. Creating shared health records for patients and their health care professionals using self-administered functions of EMR-tethered PHRs is crucial to support sustainable use of the system.

Objective

This study assesses the factors related to active use of a self-administered function (Health Notes) in an EMR-tethered PHR (Health4U) in a tertiary academic hospital.

Methods

This research is a cross-sectional study conducted in a tertiary academic hospital in South Korea. The enrollees included adults aged 19 years and older with experience accessing Health4U in the 13-month period after June 2013. The primary outcome was the adoption of Health Notes in accordance with the number of chronic diseases. Socio-demographic variables were included as confounding factors.

Results

Subjects 71 years of age and older were less likely to become active users of Health Notes than those 30 years and younger. Moreover, compared with men, women had 44% and 40% lower tendencies to become Health Notes users and active users, respectively. Those who accessed the desktop page and/or mobile page had higher tendencies to become users of Health Notes. We found a consistent increase in the odds ratio as the number of chronic diseases increased in the active users. When considering specific diseases, patients who had cancer or chronic kidney disease had higher tendencies to become users of Health Notes.

Conclusions

Patients with a greater number of chronic diseases tended to use PHR more actively, and used the self-administered function. Women and the elderly may have lower tendencies to actively use PHR. Therefore, items specific to the health of each demographic—women, the elderly, and those with chronic diseases—should be carefully considered to support sustainable use of PHRs.

Abstract PD2-04: FOXA1 induces a pro-metastatic secretome through ER-dependent and independent transcriptional reprogramming in endocrine-resistant breast cancer

Background: Metastasis in ER-positive (+) breast cancer (BC) occurring years to decades after initial diagnosis presents a daunting challenge for clinical care and preclinical research due to limited known key players and experimental models. FOXA1 is a pioneer factor for ER-chromatin binding and function, and is highly expressed in ER+ BC metastases, yet the underlying mechanism is unclear. Tumor-secreted proteins play a crucial role in the reciprocal interplay between cancer cells and host microenvironmental factors at both primary and secondary sites. We hypothesized that high FOXA1 provokes an ER-dependent transcriptional program that includes a unique pro-tumorigenic secretome essential for promoting ER+ BC metastasis. Methods: A lentiviral doxycycline (Dox)-inducible FOXA1 overexpression vector and a dual luciferase/GFP (LG) tracking vector were integrated to construct a stable MCF7-LG/FOXA1 cell model. Ovariectomized nude mice bearing MCF7-LG/FOXA1 xenografts in the presence of exogenous estrogen (E2) were randomized to ± Dox, each with continued E2, E2 deprivation (ED), or tamoxifen (Tam). Survival surgery removing the therapy-naïve (E2 arm) and relapsed (ED/Tam arms) tumors was performed when tumors reached ∼1000 mm3. All mice then received ED/Tam 'adjuvant' therapy, with longitudinal luminescence imaging to monitor local/distant recurrences. Mice were or will be euthanized at the ethical end-point. Integrative bioinformatics was performed using RNA-seq and FOXA1/ER ChIP-seq data from our preclinical models to identify secretome targets for functional intervention. Times to tumor regression (TTR) and progression (TTP) were defined by when the tumor reached half or twice the volume at randomization. Results: Median (m) TTR was achieved in ED (31/34 days, -/+Dox, P = 0.184) but not in Tam groups — Tam delayed tumor growth but failed to prevent progression in all mice with mTTP of 94/93 days (-/+Dox, P = 0.517). Despite no difference in mTTP at Tam-/+Dox, a quarter of +Dox tumors (3/12) had volume doubled by day 11. No metastases were observed by imaging in any of the mice before surgery ('neoadjuvant' setting). Local relapse and lymph-node/lung metastases were detected after surgery ('adjuvant' setting). At day 90 in the adjuvant Tam group with previously relapsed tumors, +Dox mice succumbed to metastasis more often than -Dox mice (7/8 vs. 3/10, P = 0.023). Compared to the adjuvant Tam+Dox mice with previous therapy-naïve tumors, the Tam+Dox with previously relapsed tumors showed higher distant metastasis rate (7/8 vs. 5/14, P = 0.026). Analysis of the ED setting is pending due to late recurrence. Data integration and functional study revealed a set of cytokines, growth factors, and extracellular matrix components (including IL-8, CTGF, and LOX), regulated by FOXA1 often in conjunction with ER, that are highly involved in FOXA1-induced metastasis. Global secretome profiling by mass spectrometry and target validation are ongoing. Conclusions: FOXA1 overexpression increases metastatic potential in ER+ BC. We established a pertinent metastatic xenograft mouse model to characterize a pro-metastatic secretome with diagnostic and therapeutic potential for treating metastatic ER+ BC.

Citation Format: Fu X, Pereira R, Zhao D, Jung SY, Jeselsohn R, Creighton CJ, Shea M, Nardone A, Angelis CD, Tsimelzon A, Wang T, Gutierrez C, Huang S, Edwards DP, Rimawi MF, Hilsenbeck SG, Brown M, Chen K, Osborne CK, Schiff R. FOXA1 induces a pro-metastatic secretome through ER-dependent and independent transcriptional reprogramming in endocrine-resistant breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD2-04.

Efficacy of Carboxymethylcellulose and Hyaluronate in Dry Eye Disease: A Systematic Review and Meta-Analysis

Background

The efficacy of two artificial tears, carboxymethylcellulose (CMC) and hyaluronate (HA), was compared in the treatment of patients with dry eye disease.

Methods

We conducted a systematic review and meta-analysis on randomized controlled trials in the PubMed, Embase, Cochrane Library, and ClinicalTrials.gov databases. The efficacy was compared in terms of the mean change from baseline in tear break-up time. The meta-analysis was conducted using both random and fixed effect models. The quality of the selected studies was assessed for risk of bias.

Results

Five studies were included involving 251 participants. Random effect model meta-analysis showed no significant difference between CMC and HA in treating dry eye disease (pooled standardized mean difference [SMD]=-0.452; 95% confidence interval [CI], -0.911 to 0.007; P=0.053). In contrast, fixed effect model meta-analysis revealed significant improvements in the CMC group when compared to the HA group (pooled SMD=-0.334; 95% CI, -0.588 to -0.081; P=0.010).

Conclusion

The efficacy of CMC appeared to be better than that of HA in treating dry eye disease, although meta-analysis results were not statistically significant. Further research is needed to better elucidate the difference in efficacy between CMC and HA in treating dry eye disease.

A novel concept for integrating and delivering health information using a comprehensive digital dashboard: An analysis of healthcare professionals' intention to adopt a new system and the trend of its real usage

OBJECTIVE

To introduce a new concept of medical dashboard system called BESTBoard. Such a system was implemented in all wards in a tertiary academic hospital to explore the development process, core designs, functions, usability and feasibility.

METHODS

The task-force team made user interface designs for 6 months based on a need analysis. Hardware configuration and software development was carried out for 3 months. We conducted a survey of 383 physicians and nurses to determine the usability and feasibility of the system.

RESULTS

In March 2012, the system was installed in all wards, including the intensive care units, emergency rooms, operation rooms, and even delivery rooms. Healthcare professionals had access to all information of EHRs optimized for a large 55-inch touchscreen. The satisfaction rate of BESTBoard users was high, with a mean of 3.3 points. Voluntary users tended to consider BESTBoard as a good system that is useful for team round visits, interdisciplinary team approach, and collecting the status of the hospital rooms. Elderly users didn't tend to think of BESTBoard as a useful tool for interdisciplinary team approach and collecting the status of the hospital rooms. Greater expectations regarding work performance affected the users' attitudes positively. A positive attitude toward using the system resulted in consistent real usage and health care professionals' satisfaction with the new dashboard system.

CONCLUSIONS

A new concept of hospital dashboard system proved to be feasible and useful in delivering health information to healthcare professionals. A positive attitude and an expectation regarding work performance were important factors for intention to use the system. This finding can serve for developing new systems to present health information effectively. Further studies will be needed to evaluate the extent to which BESTBoard can have a positive impact on clinical care outcomes and work performance.

Impaired development and dysfunction of endothelial progenitor cells in type 2 diabetic mice

AIM

Dysfunction of circulating endothelial progenitor cells (EPCs) has been shown to affect the development of microvascular diseases in diabetes patients. The aim of this study was to elucidate the development and mechanical dysfunction of EPCs in type 2 diabetes (T2D).

METHODS

The colony-forming capacity of EPCs and differentiation potential of bone marrow (BM) c-Kit(+)/Sca-I(+) lineage-negative mononuclear cells (KSL) were examined in T2D mice, db/db mice and KKA^y mice, using EPC colony-forming assay (EPC-CFA).

RESULTS

T2D mice had fewer BM stem/progenitor cells, and proliferation of KSL was lowest in the BM of db/db mice. In T2D mice, the frequency of large colony-forming units (CFUs) derived from BM-KSL was highly reduced, indicating dysfunction of differentiation into mature EPCs. Only a small number of BM-derived progenitors [CD34(+) KSL cells], which contribute to the supply of EPCs for postnatal neovascularization, was also found. Furthermore, in terms of their plasticity to transdifferentiate into various cell types, BM-KSL exhibited a greater potential to differentiate into granulocyte macrophages (GMs) than into other cell types.

CONCLUSION

T2D affected EPC colony formation and differentiation of stem cells to mature EPCs or haematopoietic cells. These data suggest opposing regulatory mechanisms for differentiation into mature EPCs and GMs in T2D mice.

Development of a Weight Loss Mobile App Linked With an Accelerometer for Use in the Clinic: Usability, Acceptability, and Early Testing of its Impact on the Patient-Doctor Relationship

Background

Although complications of obesity are well acknowledged and managed by clinicians, management of obesity itself is often difficult, which leads to its underdiagnosis and undertreatment in hospital settings. However, tools that could improve the management of obesity, including self-monitoring, engagement with a social network, and open channels of communication between the patient and doctor, are limited in a clinic-based setting.

Objective

The objective of our study was to evaluate the usability and acceptability of a newly developed mobile app linked with an accelerometer and its early effects on patient-doctor relationships.

Methods

From September 2013 to February 2014, we developed a mobile app linked with an accelerometer as a supportive tool for a clinic-based weight loss program. The app used information from electronic health records and delivered tailored educational material. Personal goal setting, as well as monitoring of weight changes and physical activity combined with feedback, are key features of the app. We also incorporated an interactive message board for patients and doctors. During the period of March 2014 to May 2014, we tested our mobile app for 1 month in participants in a hospital clinic setting. We assessed the app’s usability and acceptability, as well as the patient-doctor relationship, via questionnaires and analysis of app usage data.

Results

We recruited 30 individuals (18 male and 12 female) for the study. The median number of log-ins per day was 1.21, with the most frequently requested item being setting goals, followed by track physical activities and view personal health status. Scales of the depth of the patient-doctor relationship decreased from 27.6 (SD 4.8) to 25.1 (SD 4.5) by a Wilcoxon signed rank test (P=.02).

Conclusions

A mobile phone app linked with an accelerometer for a clinic-based weight loss program is useful and acceptable for weight management but exhibited less favorable early effects on patient-doctor relationships.

Comparison of steroid administration methods in patients with idiopathic sudden sensorineural hearing loss: a retrospective observational study

OBJECTIVES

To compare the recovery rates of patients with idiopathic sudden sensorineural hearing loss (ISSHL) treated with oral systemic steroids (PO) or intratympanic steroid injection (IT) or both.

DESIGN

A retrospective observational study.

SETTING

Tertiary referral centre.

PARTICIPANTS

Eight hundred and forty-four patients diagnosed with ISSHL within 14 days of the onset of symptoms. The patients were divided into three groups by treatment modality.

MAIN OUTCOME MEASURES

Threshold of pure-tone tests, age, accompanying symptoms and underlying diseases were compared. The level of final hearing recovery was evaluated by the application of the results of the pure-tone test that was performed at least 3 months after the completion of each treatment.

RESULTS

Final hearing recovery rate differed significantly by the type of treatment (P = 0.031). Recovery rates in the PO and combined groups were significantly higher in patients with mild (85.1% and 88.6%, respectively) than with profound (52.8% and 69.0%, respectively) hearing loss (P < 0.05). In contrast, severity and recovery rate were not significantly correlated in the IT group (P > 0.05). Combined treatment yielded significantly higher recovery rates than other treatment modalities in patients without hypertension (HTN) and diabetes mellitus (DM) (P = 0.021).

CONCLUSION

In the group treated with combined therapy, better hearing improvement was obtained than in the groups treated with systemic steroid only or with intratympanic steroid injection only without complications. These findings suggest that the combination of systemic administration and intratympanic injection may improve patient prognosis.

Identifying the potential long-term survivors among breast cancer patients with distant metastasis

BACKGROUND

We aimed to develop a prediction model to identify long-term survivors after developing distant metastasis from breast cancer.

PATIENTS AND METHODS

From the institution's database, we collected data of 547 patients who developed distant metastasis during their follow-ups. We developed a model that predicts the post-metastasis overall survival (PMOS) based on the clinicopathologic factors of the primary tumors and the characteristics of the distant metastasis. For validation, the survival data of 254 patients from four independent institutions were used.

RESULTS

The median duration of the PMOS was 31.0 months. The characteristics of the initial primary tumor, such as tumor stage, hormone receptor status, and Ki-67 expression level, and the characteristics of the distant metastasis presentation including the duration of disease-free interval, the site of metastasis, and the presence of metastasis-related symptoms were independent prognostic factors determining the PMOS. The association between tumor stage and the PMOS was only seen in tumors with early relapses. The PMOS score, which was developed based on the above six factors, successfully identified patients with superior survival after metastasis. The median PMOS for patients with a PMOS score of <2 and for patients with a PMOS score of >5 were 71.0 and 12 months, respectively. The clinical significance of the PMOS score was further validated using independent multicenter datasets.

CONCLUSIONS

We have developed a novel prediction model that can classify breast cancer patients with distant metastasis according to their survival after metastasis. Our model can be a valuable tool to identify long-term survivors who can be potential candidates for more intensive multidisciplinary approaches. Furthermore, our model can provide a more reliable survival information for both physicians and patients during their informed decision-making process.