Information technology-supported integrated health service for older adults in long-term care settings.

BACKGROUND: To examine the effectiveness and safety of a data sharing and comprehensive management platform for institutionalized older patients. METHODS: We applied information technology-supported integrated health service platform to patients who live at long-term care hospitals (LTCHs) and nursing homes (NHs) with cluster randomized controlled study. We enrolled 555 patients aged 65 or older (461 from 7 LTCHs, 94 from 5 NHs). For the intervention group, a tablet-based platform comprising comprehensive geriatric assessment, disease management, potentially inappropriate medication (PIM) management, rehabilitation program, and screening for adverse events and warning alarms were provided for physicians or nurses. The control group was managed with usual care. Co-primary outcomes were (1) control rate of hypertension and diabetes, (2) medication adjustment (PIM prescription rate, proportion of polypharmacy), and (3) combination of potential quality-of-care problems (composite quality indicator) from the interRAI assessment system which assessed after 3-month of intervention. RESULTS: We screened 1119 patients and included 555 patients (control; 289, intervention; 266) for analysis. Patients allocated to the intervention group had better cognitive function and took less medications and PIMs at baseline. The diabetes control rate (OR = 2.61, 95% CI 1.37-4.99, p = 0.0035), discontinuation of PIM (OR = 4.65, 95% CI 2.41-8.97, p < 0.0001), reduction of medication in patients with polypharmacy (OR = 1.98, 95% CI 1.24-3.16, p = 0.0042), and number of PIMs use (ꞵ = - 0.27, p < 0.0001) improved significantly in the intervention group. There was no significant difference in hypertension control rate (OR = 0.54, 95% CI 0.20-1.43, p = 0.2129), proportion of polypharmacy (OR = 1.40, 95% CI 0.75-2.60, p = 0.2863), and improvement of composite quality indicators (ꞵ = 0.03, p = 0.2094). For secondary outcomes, cognitive and motor function, quality of life, and unplanned hospitalization were not different significantly between groups. CONCLUSIONS: The information technology-supported integrated health service effectively reduced PIM use and controlled diabetes among older patients in LTCH or NH without functional decline or increase of healthcare utilization. TRIAL REGISTRATION: Clinical Research Information Service, KCT0004360. Registered on 21 October 2019.

Digital Health Technology Use Among Older Adults: Exploring the Impact of Frailty on Utilization, Purpose, and Satisfaction in Korea.

BACKGROUND: The importance of digital technology is increasing among older adults. In this study, the digital health technology utilization status, purpose, and satisfaction of older adults were investigated according to frailty. METHODS: A face-to-face survey was conducted among adults aged 65 years or older. Frailty was defined using the Korean version of the fatigue, resistance, ambulation, illnesses, and loss of weight scale. RESULTS: A total of 505 participants completed the survey, with 153 (30.3%) identified as pre-frail or frail and 352 (69.7%) as healthy. All respondents used smartphones; 440 (87.1%) were application users, and 290 (57.4%) were healthcare application users. Wearable devices were used by only 36 patients (7.1%). Pre-frail or frail respondents used social media more frequently than healthy respondents (19.4% vs. 7.4%, P < 0.001). Among the respondents, 319 (63.2%) were not able to install or delete the application themselves, and 277 (54.9%) stated that the application was recommended by their children (or partner). Pre-frail and frail respondents used more healthcare applications to obtain health information (P = 0.002) and were less satisfied with wearable devices (P = 0.02). CONCLUSION: The usage rate of digital devices, including mobile phones among older adults in Korea is high, whereas that of wearable devices is low. There was a notable difference in the services used by pre-frail and frail respondents compared to healthy respondents. Therefore, when developing digital devices for pre-frail and frail older adults, it is crucial to incorporate customized services that meet their unique needs, particularly those services that they frequently use.

Characteristics According to Frailty Status Among Older Korean Patients With Hypertension.

BACKGROUND: As the prevalence of hypertension increases with age and the proportion of the older population is also on the rise, research on the characteristics of older hypertensive patients and the importance of frailty is necessary. This study aimed to identify clinical characteristics of older hypertension in Korea and to investigate these characteristics based on frailty status. METHODS: The HOW to Optimize eLDerly systolic BP (HOWOLD-BP) is a prospective, multicenter, open-label, randomized clinical trial that aims to compare intensive (target systolic blood pressure [SBP] ≤ 130 mmHg) with standard (target SBP ≤ 140 mmHg) treatment to reduce cardiovascular events in older hypertensive Korean patients aged ≥ 65 years. Data were analyzed through a screening assessment of 2,085 patients recruited from 11 university hospitals. Demographic, functional (physical and cognitive), medical history, laboratory data, quality of life, and medication history of antihypertensive drugs were assessed. RESULTS: The mean age was 73.2 years (standard deviation ± 5.60), and 48.0% (n = 1,001) were male. Prevalent conditions included dyslipidemia (66.5%), obesity (body mass index ≥ 25 kg/m², 53.6%), and diabetes (28.9%). Dizziness and orthostatic hypotension were self-reported by 1.6% (n = 33) and 1.2% (n = 24), respectively. The majority of patients were on two antihypertensive drugs (48.4%), while 27.5% (n = 574) and 20.8% (n = 433) were on 1 and 3 antihypertensive medications, respectively. Frail to pre-frail patients were older and also tended to have dependent instrumental activities of daily living, slower gait speed, weaker grip strength, lower quality of life, and lower cognitive function. The frail to pre-frail group reported more dizziness (2.6% vs. 1.2%, P < 0.001) and had concerning clinical factors, including lower glomerular filtration rate, more comorbidities such as diabetes, stroke, and a history of admission. Frail to pre-frail older hypertensive patients used slightly more antihypertensive medications than robust older hypertensive patients (1.95 vs. 2.06, P = 0.003). Pre-frail to frail patients often chose beta-blockers as a third medication over diuretics. CONCLUSION: This study described the general clinical characteristics of older hypertensive patients in Korea. Frail hypertensive patients face challenges in achieving positive clinical outcomes because of multifactorial causes: they are older, have more morbidities, decreased function, lower quality of life and cognitive function, and take more antihypertensive medications. Therefore, it is essential to comprehensively evaluate and monitor disease-related or drug-related adverse events more frequently during regular check-ups, which is necessary for pre-frail to frail older patients with hypertension. TRIAL REGISTRATION: Clinical Research Information Service Identifier: KCT0003787.

Development and validation of a machine learning-based fall-related injury risk prediction model using nationwide claims database in Korean community-dwelling older population.

BACKGROUND: Falls impact over 25% of older adults annually, making fall prevention a critical public health focus. We aimed to develop and validate a machine learning-based prediction model for serious fall-related injuries (FRIs) among community-dwelling older adults, incorporating various medication factors. METHODS: Utilizing annual national patient sample data, we segmented outpatient older adults without FRIs in the preceding three months into development and validation cohorts based on data from 2018 and 2019, respectively. The outcome of interest was serious FRIs, which we defined operationally as incidents necessitating an emergency department visit or hospital admission, identified by the diagnostic codes of injuries that are likely associated with falls. We developed four machine-learning models (light gradient boosting machine, Catboost, eXtreme Gradient Boosting, and Random forest), along with a logistic regression model as a reference. RESULTS: In both cohorts, FRIs leading to hospitalization/emergency department visits occurred in approximately 2% of patients. After selecting features from initial set of 187, we retained 26, with 15 of them being medication-related. Catboost emerged as the top model, with area under the receiver operating characteristic of 0.700, along with sensitivity and specificity rates around 65%. The high-risk group showed more than threefold greater risk of FRIs than the low-risk group, and model interpretations aligned with clinical intuition. CONCLUSION: We developed and validated an explainable machine-learning model for predicting serious FRIs in community-dwelling older adults. With prospective validation, this model could facilitate targeted fall prevention strategies in primary care or community-pharmacy settings.

Development and Validation of a Prognostic Classification Model Predicting Postoperative Adverse Outcomes in Older Surgical Patients Using a Machine Learning Algorithm: Retrospective Observational Network Study.

BACKGROUND: Older adults are at an increased risk of postoperative morbidity. Numerous risk stratification tools exist, but effort and manpower are required. OBJECTIVE: This study aimed to develop a predictive model of postoperative adverse outcomes in older patients following general surgery with an open-source, patient-level prediction from the Observational Health Data Sciences and Informatics for internal and external validation. METHODS: We used the Observational Medical Outcomes Partnership common data model and machine learning algorithms. The primary outcome was a composite of 90-day postoperative all-cause mortality and emergency department visits. Secondary outcomes were postoperative delirium, prolonged postoperative stay (≥75th percentile), and prolonged hospital stay (≥21 days). An 80% versus 20% split of the data from the Seoul National University Bundang Hospital (SNUBH) and Seoul National University Hospital (SNUH) common data model was used for model training and testing versus external validation. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) with a 95% CI. RESULTS: Data from 27,197 (SNUBH) and 32,857 (SNUH) patients were analyzed. Compared to the random forest, Adaboost, and decision tree models, the least absolute shrinkage and selection operator logistic regression model showed good internal discriminative accuracy (internal AUC 0.723, 95% CI 0.701-0.744) and transportability (external AUC 0.703, 95% CI 0.692-0.714) for the primary outcome. The model also possessed good internal and external AUCs for postoperative delirium (internal AUC 0.754, 95% CI 0.713-0.794; external AUC 0.750, 95% CI 0.727-0.772), prolonged postoperative stay (internal AUC 0.813, 95% CI 0.800-0.825; external AUC 0.747, 95% CI 0.741-0.753), and prolonged hospital stay (internal AUC 0.770, 95% CI 0.749-0.792; external AUC 0.707, 95% CI 0.696-0.718). Compared with age or the Charlson comorbidity index, the model showed better prediction performance. CONCLUSIONS: The derived model shall assist clinicians and patients in understanding the individualized risks and benefits of surgery.

Analysis of blood pressure and blood pressure variability pattern among older patients in long-term care hospitals: an observational study analysing the Health-RESPECT (integrated caRE Systems for elderly PatiEnts using iCT) dataset.

OBJECTIVES: There are limited data regarding blood pressure (BP) variability among older adults living in long-term care hospitals (LTCHs). We aimed to collect data from LTCH and analyse BP characteristics and its variability among these patients using a novel platform. METHODS: The Health-RESPECT (integrated caRE Systems for elderly PatiEnts using iCT) platform was used to construct a daily BP dataset using data of 394 older patients from 6 LTCHs. BP variability was expressed as coefficient of variation (CV = standard deviation/mean of BP × 100). Physical frailty and cognitive function were evaluated using the K-FRAIL questionnaire and the Cognitive Performance Scale of the interRAI Long-Term Care Facilities tool, respectively. RESULTS: From September 2019 to September 2020, 151,092 BP measurements, 346.5 (IQR 290.8-486.3) measurements per patient, were included. The mean BP was 123.4 ± 10.8/71.3 ± 6.5 mmHg. BP was significantly lower in frail patients (122.2 ± 11.3/70.4 ± 6.8 mmHg) than in pre-frail/robust patients (124.4 ± 10.4/72.1 ± 6.1 mmHg, P < 0.05). However, CV of systolic (10.7 ± 2.3% versus 11.3 ± 2.3%, P = 0.005) and diastolic (11.6 ± 2.3% versus 12.4 ± 2.4%, P < 0.001) BP was higher in frail patients. The mean BP was lower, but BP variability was higher in patients with cognitive impairment. The mean BP, but not BP variability, was higher in treated hypertensive patients, as the number of antihypertensive medications increased. CONCLUSION: Older patients with physical or cognitive frailty had lower BP but higher BP variability. Relationship among frailty, increased BP variability and adverse clinical outcomes should be investigated.

Prevalence of potentially inappropriate medications based on the STOPPFrail criteria in frail older patients with limited life expectancy: a cross-sectional study.

BACKGROUND: The recently developed Screening Tool of Older Persons' Prescriptions in Frail adults with a limited life expectancy (STOPPFrail) criteria can be helpful for screening medications (PIMs), but it is yet to be widely used in clinical practice. Herein, we aimed to investigate the prevalence of PIMs based on the STOPPFrail criteria (STOPPFrail-PIM) among frail older adults with limited life expectancy admitted to the geriatric center. METHODS: This was a retrospective cross-sectional study conducted in the geriatric center at an academic tertiary care hospital in Korea. We evaluated frail older adults with limited life expectancy who received comprehensive geriatric assessment (CGA) admitted between 1 January, 2019 and 30 June, 2020. Frail older adults with limited life expectancy were identified by geriatricians with retrospective records and the prevalence of STOPPFrail-PIMs was analysed by trained pharmacists. Descriptive analysis, t-test, and chi-square test were conducted using IBM SPSS software version 25.0. RESULTS: Among 504 older adults who underwent CGA after admission, 171 frail older adults with limited life expectancy were identified by geriatricians and included in the study. An average of 11.3 ± 4.7 medications were administered regularly to each patient before admission. Overall, 97.1% (166/171) had at least one STOPPFrail-PIM, and the mean number of STOPPFrail-PIM was 4.2 ± 2.8. Drugs without clear clinical indication (A2) were the most frequent pre-admission STOPPFrail-PIM, followed by lipid-lowering therapies (B1) and neuroleptic antipsychotics (D1). The number of STOPPFrail-PIM was significantly lower at discharge than that at admission, with the decrease being the highest for A2 at 94.7%. CONCLUSIONS: Most frail older adults with limited life expectancy had at least one STOPPFrail-PIM at admission, and the rate of STOPPFrail-PIM decreased significantly at discharge after the geriatric multidisciplinary team care. Further studies are needed to investigate the association between the use of STOPPFrail-PIM and adverse consequences in frail older adults.

A Quasi-Intelligent Maritime Route Extraction from AIS Data.

The rapid development and adoption of automatic identification systems as surveillance tools have resulted in the widespread application of data analysis technology in maritime surveillance and route planning. Traditional, manual, experience-based route planning has been widely used owing to its simplicity. However, the method is heavily dependent on officer experience and is time-consuming. This study aims to extract shipping routes using unsupervised machine-learning algorithms. The proposed three-step approach: maneuvering point detection, waypoint discovery, and traffic network construction was used to construct a maritime traffic network from historical AIS data, which quantitatively reflects ship characteristics by ship length and ship type, and can be used for route planning. When the constructed maritime traffic network was compared to the macroscopic ship traffic flow, the Symmetrized Segment-Path Distance (SSPD) metric returned lower values, indicating that the constructed traffic network closely resembles the routes ships transit. The result indicates that the proposed approach is effective in extracting a route from the maritime traffic network.

Differential virulence of infectious hematopoietic necrosis virus (IHNV) isolated from salmonid fish in Gangwon Province, Korea.

The present study investigated the virulence and expression of innate immunity genes in isolates of infectious hematopoietic necrosis virus (IHNV) in Gangwon province, South Korea, by challenging rainbow trout, Atlantic salmon, and coho salmon. Eight IHNV isolates were used to infect RTG-2 cells for viral replication using plaque assays. Three isolates with the highest replication rates, the RtPc0314g and RtPc0314c isolates of the JRt-Shizuoka type and the RtPc0816g isolate of the JRt-Nagano type, were experimentally infected into the fish. In rainbow trout, both RtPc0314c and RtPc0314g isolates showed 100% cumulative mortality while the RtPc0816g isolate showed 60% cumulative mortality for 14 days. In contrast, all three isolates showed <60% cumulative mortality in Atlantic salmon and coho salmon. The expression of G genes in the kidney was higher than that in the spleen-infected fish, with the highest expression observed in the kidneys of rainbow trout. The relative expression levels of innate immunity genes were higher in rainbow trout than in Atlantic salmon and coho salmon. The expression level of immunoglobulin M increased until day 7, and the expression of type I interferon was higher in the spleen than in other tissues. The expression of Mx-1 was higher in the kidney and liver than other tissues. These results indicate that IHNV isolates from Gangwon province show host-specific virulence in rainbow trout and that their virulence and replication were higher in JRt-Shizuoka type than in JRt-Nagano type isolates.

How does the multidimensional frailty score compare with grip strength for predicting outcomes after hip fracture surgery in older patients? A retrospective cohort study.

BACKGROUND: Frailty and low handgrip strength (HGS) are associated with adverse outcomes after hip fracture (HF) surgery. We aimed to compare the predictive role of frailty and HGS for adverse outcome in HF patients. METHODS: We included older patients (age ≥ 65 years) who underwent HF surgery to compare the predictive role of HGS and hip-multidimensional frailty score (Hip-MFS) for postoperative complications and mortality. The Hip-MFS was calculated based on comprehensive geriatric assessment (CGA), and HGS was measured with a hand dynamometer. The primary outcome was a composite of postoperative complications (e.g., pneumonia, urinary tract infection, delirium, acute pulmonary thromboembolism, and unplanned intensive care unit admission). The secondary outcomes were 6-month mortality and mortality at the end of follow-up. RESULTS: The median observation time was 620.5 days (interquartile range: 367.0-784.8 days). Among the 242 patients (mean age: 81.5 ± 6.7 years, 73.1% women), 106 (43.8%) experienced postoperative complications. The 6-month mortality and mortality at the end of follow-up were 7.4% (n = 18) and 20.7% (n = 50), respectively. The Hip-MFS (odds ratio [OR], 1.250; 95% confidence interval [CI], 1.092-1.432) and HGS (OR, 1.147; 95% CI, 1.082-1.215) could predict postoperative complications. The Hip-MFS could predict both 6-month mortality (hazard ratio [HR], 1.403; 95% CI, 1.027-1.917) and mortality at the end of follow-up (HR, 1.493; 95% CI, 1.249-1.769) after adjustment, while HGS was only associated with mortality at the end of follow-up (HR, 1.080; 95% CI, 1.024-1.139). For mortality at the end of follow-up, predictive models with the Hip-MFS were superior to those with HGS in the time-dependent receiver-operating curve analysis after adjustment (p = 0.017). Furthermore, the addition of Hip-MFS or HGS to the American Society of Anesthesiologists (ASA) classification improved its prognostic ability. CONCLUSIONS: Both the Hip-MFS and HGS could predict postoperative complications and improve prognostic utility when combined with the ASA classification. The Hip-MFS was a stronger predictor of mortality than HGS after HF surgery. HGS could be a useful pre-screening tool to identify patients at a high risk of postoperative complications and those who may benefit from further CGA.

Accuracy and Diversity of Wearable Device-Based Gait Speed Measurement Among Older Men: Observational Study.

BACKGROUND: Gait speed measurements are widely used in clinical practice, as slow gait is a major predictor of frailty and a diagnostic criterion for sarcopenia. With the development of wearable devices, it is possible to estimate the gait speed in daily life by simply wearing the device. OBJECTIVE: This study aims to accurately determine the characteristics of daily life gait speed and analyze their association with sarcopenia. METHODS: We invited community-dwelling men aged >50 years who had visited the outpatient clinic at a tertiary university hospital to participate in the study. Daily life gait speed was assessed using a wearable smart belt (WELT) for a period of 4 weeks. Data from participants who wore the smart belt for at least 10 days during this period were included. After 4 weeks, data from a survey about medical and social history, usual gait speed measurements, handgrip strength measurements, and dual-energy x-ray absorptiometry were analyzed. RESULTS: A total of 217,578 daily life gait speed measurements from 106 participants (mean age 71.1, SD 7.6 years) were analyzed. The mean daily life gait speed was 1.23 (SD 0.26) m/s. The daily life gait speed of the participants varied according to the time of the day and day of the week. Daily life gait speed significantly slowed down with age (P<.001). Participants with sarcopenia had significantly lower mean daily life gait speed (mean 1.12, SD 0.11 m/s) than participants without sarcopenia (mean 1.23, SD 0.08 m/s; P<.001). Analysis of factors related to mean daily life gait speed showed that age and skeletal muscle mass of the lower limbs were significantly associated characteristics. CONCLUSIONS: More diverse and accurate information about gait speed can be obtained by measuring daily life gait speed using a wearable device over an appropriate period, compared with one-time measurements performed in a laboratory setting. Importantly, in addition to age, daily life gait speed is significantly associated with skeletal muscle mass of the lower limbs.

A Smart Diaper System Using Bluetooth and Smartphones to Automatically Detect Urination and Volume of Voiding: Prospective Observational Pilot Study in an Acute Care Hospital.

BACKGROUND: Caregivers of patients who wear conventional diapers are required to check for voiding every hour because prolonged wearing of wet diapers causes health problems including diaper dermatitis and urinary tract infections. However, frequent checking is labor intensive and disturbs patients' and caregivers' sleep. Furthermore, assessing patients' urine output with diapers in an acute care setting is difficult. Recently, a smart diaper system with wetness detection technology was developed to solve these issues. OBJECTIVE: We aimed to evaluate the applicability of the smart diaper system for urinary detection, its accuracy in measuring voiding volume, and its effect on incontinence-associated dermatitis (IAD) occurrence in an acute care hospital. METHODS: This prospective, observational, single-arm pilot study was conducted at a single tertiary hospital. We recruited 35 participants aged ≥50 years who were wearing diapers due to incontinence between August and November 2020. When the smart diaper becomes wet, the smart diaper system notifies the caregiver to change the diaper and measures voiding volume automatically. Caregivers were instructed to record the weight of wet diapers on frequency volume charts (FVCs). We determined the voiding detection rate of the smart diaper system and compared the urine volume as automatically calculated by the smart diaper system with the volume recorded on FVCs. Agreement between the two measurements was estimated using a Bland-Altman plot. We also checked for the occurrence or aggravation of IAD and bed sores. RESULTS: A total of 30 participants completed the protocol and 390 episodes of urination were recorded. There were 108 records (27.7%) on both the FVCs and the smart diaper system, 258 (66.2%) on the FVCs alone, 18 (4.6%) on the smart diaper system alone, and 6 (1.5%) on the FVCs with sensing device lost. The detection rate of the smart diaper system was 32.8% (126/384). When analyzing records concurrently listed in both the FVCs and the smart diaper system, linear regression showed a strong correlation between the two measurements (R2=0.88, P<.001). The Bland-Altman assessment showed good agreement between the two measurements, with a mean difference of -4.2 mL and 95% limits of agreement of -96.7 mL and 88.3 mL. New occurrence and aggravation of IAD and bed sores were not observed. Bed sores improved in one participant. CONCLUSIONS: The smart diaper system showed acceptable accuracy for measuring urine volume and it could replace conventional FVCs in acute setting hospitals. Furthermore, the smart diaper system has the potential advantage of preventing IAD development and bed sore worsening. However, the detection rate of the smart diaper system was lower than expected. Detection rate polarization among participants was observed, and improvements in the user interface and convenience are needed for older individuals who are unfamiliar with the smart diaper system.

Optimal Staffing for Vessel Traffic Service Operators: A Case Study of Yeosu VTS.

Vessel traffic volume and vessel traffic service (VTS) operator workloads are increasing with the expansion of global maritime trade, contributing to marine accidents by causing difficulties in providing timely services. Therefore, it is essential to have sufficient VTS operators considering the vessel traffic volume and near-miss cases. However, no quantitative method for determining the optimal number of workstations, which is necessary for calculating the VTS operator staffing level, has yet been proposed. This paper proposes a new, microscopic approach for calculating the number of workstations from vessel trajectories and voice recording communication data between VTS operators and navigators. The vessel trajectory data are preprocessed to interpolate different intervals. The proposed method consists of three modules: Information services, navigational assistance services, and traffic organization service. The developed model was applied to the Yeosu VTS in Korea. Another workstation should be added to the current workstation based on the proposed method. The results showed that even without annual statistical data, a reasonable VTS operator staffing level could be calculated. The proposed approach helps prevent vessel accidents by providing timely services even if the vessel traffic is congested if VTS operators are deployed to a sufficient number of workstations.

Immunostimulatory Potential of Extracellular Vesicles Isolated from an Edible Plant, Petasites japonicus, via the Induction of Murine Dendritic Cell Maturation.

Extracellular vesicles (EVs) have recently been isolated from different plants. Plant-derived EVs have been proposed as potent therapeutics and drug-delivery nanoplatforms for delivering biomolecules, including proteins, RNAs, DNAs, and lipids. Herein, Petasites japonicus-derived EVs (PJ-EVs) were isolated through a series of centrifugation steps and characterized using dynamic light scattering and transmission electron microscopy. Immunomodulatory effects of PJ-EVs were assessed using dendritic cells (DCs). PJ-EVs exhibited a spherical morphology with an average size of 122.6 nm. They induced the maturation of DCs via an increase in the expression of surface molecules (CD80, CD86, MHC-I, and MHC-II), production of Th1-polarizing cytokines (TNF-α and IL-12p70), and antigen-presenting ability; however, they reduced the antigen-uptake ability. Furthermore, maturation of DCs induced by PJ-EVs was dependent on the activation and phosphorylation of MAPK and NF-κB signal pathways. Notably, PJ-EV-treated DCs strongly induced the proliferation and differentiation of naïve T cells toward Th1-type T cells and cytotoxic CD8+ T cells along with robust secretion of IFN-γ and IL-2. In conclusion, our study indicates that PJ-EVs can be potent immunostimulatory candidates with an ability of strongly inducing the maturation of DCs.

Polypharmacy, Inappropriate Medication Use, and Drug Interactions in Older Korean Patients with Cancer Receiving First-Line Palliative Chemotherapy.

BACKGROUND: Polypharmacy is an important issue in the care of older patients with cancer, as it increases the risk of unfavorable outcomes. We estimated the prevalence of polypharmacy, potentially inappropriate medication (PIM) use, and drug-drug interactions (DDIs) in older patients with cancer in Korea and their associations with clinical outcomes. SUBJECTS, MATERIALS, AND METHODS: This was a secondary analysis of a prospective observational study of geriatric patients with cancer undergoing first-line palliative chemotherapy. Eligible patients were older adults (≥70 years) with histologically diagnosed solid cancer who were candidates for first-line palliative chemotherapy. All patients enrolled in this study received a geriatric assessment (GA) at baseline. We reviewed the daily medications taken by patients at the time of GA before starting chemotherapy. PIMs were assessed according to the 2015 Beers criteria, and DDIs were assessed by a clinical pharmacist using Lexi-comp Drug Interactions. We evaluated the association between polypharmacy and clinical outcomes including treatment-related toxicity, and hospitalization using logistic regression and Cox regression analyses. RESULTS: In total, 301 patients (median age 75 years; range, 70-93) were enrolled; the most common cancer types were colorectal cancer (28.9%) and lung cancer (24.6%). Mean number of daily medications was 4.7 (±3.1; range, 0-14). The prevalence of polypharmacy (≥5 medications) was 45.2% and that of excessive polypharmacy (≥10 medications) was 8.6%. PIM use was detected in 137 (45.5%) patients. Clinically significant DDIs were detected in 92 (30.6%) patients. Polypharmacy was significantly associated with hospitalization or emergency room (ER) visits (odds ratio: 1.73 [1.18-2.55], p < .01). Neither polypharmacy nor PIM use showed association with treatment-related toxicity. CONCLUSION: Polypharmacy, PIM use, and potential major DDIs were prevalent in Korean geriatric patients with cancer. Polypharmacy was associated with a higher risk of hospitalization or ER visits during the chemotherapy period. IMPLICATIONS FOR PRACTICE: This study, which included 301 older Korean patients with cancer, highlights the increased prevalence of polypharmacy in this population planning to receive palliative chemotherapy. The prevalence of polypharmacy and excessive polypharmacy was 45.2% and 8.6%, respectively. The prescription of potentially inappropriate medications (PIMs) was detected in 45.5% and clinically significant drug-drug interaction in 30.6% of patients. Given the association of polypharmacy with increased hospitalization or emergency room visits, this study points to the need for increased awareness and intervention to minimize polypharmacy in the geriatric cancer population undergoing chemotherapy. Moreover, specific criteria for establishing PIMs should be adopted for the treatment of older adults with cancer.

Impact of a delirium prevention project among older hospitalized patients who underwent orthopedic surgery: a retrospective cohort study.

BACKGROUND: Postoperative delirium (POD) is a common clinical syndrome with significant negative outcomes. Thus, we aimed to evaluate the feasibility and effectiveness of a delirium screening tool and multidisciplinary delirium prevention project. METHODS: A retrospective cohort study was conducted at a single teaching center in Korea. A cohort of patients who underwent a delirium prevention program using a simple delirium screening tool from December 2018 to February 2019 (intervention group, N = 275) was compared with the cohort from the year before implementation of the delirium prevention program (December 2017 to February 2018) (control group, N = 274). Patients aged ≥65 years who were admitted to orthopedic wards and underwent surgery were included. The incidence rates of delirium before and after implementation of the delirium prevention program, effectiveness of the delirium screening tool, change in the knowledge score of nurses, and length of hospital stay were assessed. RESULTS: The sensitivity and specificity of the screening tool for the incidence of POD were 94.1 and 72.7%, respectively. The incidence rates of POD were 10.2% (control group) and 6.2% (intervention group). The odds ratio for the risk reduction effect of the project related to the incidence of POD was 0.316 (95% confidence interval: 0.125-0.800, p = 0.015) after adjustment for possible confounders. The delirium knowledge test score increased from 40.52 to 43.24 out of 49 total points (p < 0.001). The median length of hospital stay in the intervention and control groups was 6.0 (interquartile range, 4-9) and 7.0 (interquartile range, 4-10) days, respectively (p = 0.062). CONCLUSION: The screening tool successfully identified patients at a high risk of POD at admission. The POD prevention project was feasible to implement, effective in preventing delirium, and improved knowledge regarding delirium among the medical staff. TRIAL REGISTRATION: None.

Adaptive Information Visualization for Maritime Traffic Stream Sensor Data with Parallel Context Acquisition and Machine Learning.

Excessive information significantly increases the mental burden on operators of critical monitoring services such as maritime and air traffic control. In these fields, vessels and aircraft have sensors that transmit data to a control center. Because of the large volume of collected data, it is infeasible for monitoring stations to display all of the information on monitoring screens that have limited sizes. This paper proposes a method for automatically selecting maritime traffic stream data for display from a large number of candidates in a context-aware manner. Safety is the most important concern in maritime traffic control, and special care must be taken to avoid collisions between vessels at sea. It presents an architecture for an adaptive information visualization system for a maritime traffic control service. The proposed system adaptively determines the information to be displayed based on the safety evaluation scores and expertise of vessel traffic service operators. It also introduces a method for safety context acquisition to assess the risk of collisions between vessels, using parallel and distributed processing of maritime stream data transmitted by sensors on the vessels at sea. It provides an information-filtering, knowledge extraction method based on the work logs of traffic service operators, using a machine learning technique to generate a decision tree. We applied the proposed system architecture to a large dataset collected at a port. Our results indicate that the proposed system can adaptively select traffic information according to port conditions and to ensure safety and efficiency.

Predicting cumulative incidence of adverse events in older patients with cancer undergoing first-line palliative chemotherapy: Korean Cancer Study Group (KCSG) multicentre prospective study.

BACKGROUND: Older patients have increased risk of toxicity from chemotherapy. Current prediction tools do not provide information on cumulative risk. METHODS: Patients aged ≥ 70 years with solid cancer were prospectively enrolled. A prediction model was developed for adverse events (AEs) ≥ Grade 3 (G3), based on geriatric assessment (GA), laboratory, and clinical variables. RESULTS: 301 patients were enrolled (median age, 75 years). Median number of chemotherapy cycles was 4. During first-line chemotherapy, 53.8% of patients experienced AEs ≥ G3. Serum protein < 6.7 g/dL, initial full-dose chemotherapy, psychological stress or acute disease in the past 3 months, water consumption < 3 cups/day, unable to obey a simple command, and self-perception of poor health were significantly related with AEs ≥ G3. A predicting model with these six variables ranging 0-8 points was selected with the highest discriminatory ability (c-statistic= 0.646), which could classify patients into four risk groups. Predicted cumulative incidence of AEs ≥ G3 was discriminated according to risk groups. CONCLUSIONS: This prediction tool could identify the risk of AEs ≥ G3 after chemotherapy and provide information on the cumulative incidence of AEs in each cycle. CLINICAL TRIAL ID: WHO ICTRP number, KCT0001071.

Terminal Deoxynucleotidyl Transferase and T7 Exonuclease-Aided Amplification Strategy for Ultrasensitive Detection of Uracil-DNA Glycosylase.

As one of the key initiators of the base excision repair process, uracil-DNA glycosylase (UDG) plays an important role in maintaining genomic integrity. It has been found that aberrant expression of UDG is associated with a variety of diseases. Thus, accurate and sensitive detection of UDG activity is of critical significance for biomedical research and early clinical diagnosis. Here, we developed a novel fluorescent sensing platform for UDG activity detection based on a terminal deoxynucleotidyl transferase (TdT) and T7 exonuclease (T7 Exo)-aided recycling amplification strategy. In this strategy, only two DNA oligonucleotides (DNA substrate containing one uracil base and Poly dT probe labeled with a fluorophore/quencher pair) are used. UDG catalyzes the removal of uracil base from the enclosed dumbbell-shape DNA substrate to give an apyrimidinic site, at which the substrate oligonucleotide is cleaved by endonuclease IV. The released 3'-end can be elongated by TdT to form a long deoxyadenine-rich (Poly dA) tail, which may be used as a recyclable template to initiate T7 Exo-mediated hybridization-digestion cycles of the Poly dT probe, giving a significantly enhanced fluorescence output. The proposed UDG-sensing strategy showed excellent selectivity and high sensitivity with a detection limit of 1.5 × 10-4 U/mL. The sensing platform was also demonstrated to work well for UDG inhibitor screening and inhibitory activity evaluation, thus holding great potential in UDG-related disease diagnosis and drug discovery. The proposed strategy can be easily used for the detection of other DNA repair-related enzymes by simply changing the recognition site in DNA substrate and might also be extended to the analysis of some DNA/RNA-processing enzymes, including restriction endonuclease, DNA methyltransferase, polynucleotide kinase, and so on.

Deep Learning-Based Caution Area Traffic Prediction with Automatic Identification System Sensor Data.

In a crowded harbor water area, it is a major concern to control ship traffic for assuring safety and maximizing the efficiency of port operations. Vessel Traffic Service (VTS) operators pay much attention to caution areas like ship route intersections or traffic congestion area in which there are some risks of ship collision. They want to control the traffic of the caution area at a proper level to lessen risk. Inertial ship movement makes swift changes in direction and speed difficult. It is hence important to predict future traffic of the caution area earlier on so as to get enough time for control actions on ship movements. In the harbor area, VTS stations collect a large volume of Automatic Identification Service (AIS) sensor data, which contain information about ship movement and ship attributes. This paper proposes a new deep neural network model called Ship Traffic Extraction Network (STENet) to predict the medium-term traffic and long-term traffic of the caution area. The STENet model is trained with AIS sensor data. The STENet model is organized into a hierarchical architecture in which the outputs of the movement and contextual feature extraction modules are concatenated and fed into a prediction module. The movement module extracts the features of overall ship movements with a convolutional neural network. The contextual modules consist of five separated fully-connected neural networks, each of which receives an associated attribute. The separation of feature extraction modules at the front phase helps extract the effective features by preventing unrelated attributes from crosstalking. To evaluate the performance of the proposed model, the developed model is applied to a real AIS sensor dataset, which has been collected over two years at a Korean port called Yeosu. In the experiments, four methods have been compared including two new methods: STENet and VGGNet-based models. For the real AIS sensor dataset, the proposed model has shown 50.65% relative performance improvement on average for the medium-term predictions and 57.65% improvement on average for the long-term predictions over the benchmark method, i.e., the SVR-based method.