Interdisciplinary collaboration and computer-assisted home healthcare referral in the emergency department: a retrospective cohort study.

AIM: Home healthcare (HHC) provides continuous care for disabled patients. However, HHC referral after the emergency department (ED) discharge remains unclear. Thus, this study aimed its clarification. METHODS: A computer-assisted HHC referral by interdisciplinary collaboration among emergency physicians, case managers, nurse practitioners, geriatricians, and HHC nurses was built in a tertiary medical center in Taiwan. Patients who had HHC referrals after ED discharge between February 1, 2020 and September 31, 2020, were recruited into the study. A non-ED HHC cohort who had HHC referrals after hospitalization from the ED was also identified. Comparison for clinical characteristics and uses of medical resources was performed between ED HHC and non-ED HHC cohorts. RESULTS: The model was successfully implemented. In total, 34 patients with ED HHC and 40 patients with non-ED HHC were recruited into the study. The female proportion was 61.8% and 67.5%, and the mean age was 81.5 and 83.7 years in ED HHC and non-ED HHC cohorts, respectively. No significant difference was found in sex, age, underlying comorbidities, and ED diagnoses between the two cohorts. The ED HHC cohort had a lower median total medical expenditure within 3 months (34,030.0 vs. 56,624.0 New Taiwan Dollars, p = 0.021) compared with the non-ED HHC cohort. Compared to the non-ED HHC cohort, the ED HHC cohort had a lower ≤ 1 month ED visit, ≤ 6 months ED visit, and ≤ 3 months hospitalization; however, differences were not significant. CONCLUSION: An innovative ED HHC model was successfully implemented. Further studies with more patients are warranted to investigate the impact.

Computerized tool and interdisciplinary care for older patients with delirium in the emergency department: a novel model in Taiwan.

AIMS: A computerized tool and interdisciplinary care were implemented to develop a novel model for older patients with delirium in the emergency department (ED). METHODS: We developed a computerized tool using a delirium triage screen and brief confusion assessment in the hospital information system, performed education for the healthcare providers, and developed a continuous care protocol. Comparisons for outcomes between pre- and post-intervention periods were performed. RESULTS: Compared with the pre-intervention period, patients in the post-intervention period had shorter hospitalization stay, lower expenditure of hospitalization, more likely to return home, lower ED revisits of ≤ 3 days, re-hospitalization of ≤ 14 days, and mortality of ≤ 1 month. All mentioned differences were not statistically significant. CONCLUSIONS: A novel model was successfully developed for delirium management in older patients in the ED. Outcome differences were not significant; however, the result is promising, which gives us an important reference in the future.

Predicting outcomes in older ED patients with influenza in real time using a big data-driven and machine learning approach to the hospital information system.

BACKGROUND: Predicting outcomes in older patients with influenza in the emergency department (ED) by machine learning (ML) has never been implemented. Therefore, we conducted this study to clarify the clinical utility of implementing ML. METHODS: We recruited 5508 older ED patients (≥65 years old) in three hospitals between 2009 and 2018. Patients were randomized into a 70%/30% split for model training and testing. Using 10 clinical variables from their electronic health records, a prediction model using the synthetic minority oversampling technique preprocessing algorithm was constructed to predict five outcomes. RESULTS: The best areas under the curves of predicting outcomes were: random forest model for hospitalization (0.840), pneumonia (0.765), and sepsis or septic shock (0.857), XGBoost for intensive care unit admission (0.902), and logistic regression for in-hospital mortality (0.889) in the testing data. The predictive model was further applied in the hospital information system to assist physicians' decisions in real time. CONCLUSIONS: ML is a promising way to assist physicians in predicting outcomes in older ED patients with influenza in real time. Evaluations of the effectiveness and impact are needed in the future.

Validation of shock index for predicting mortality in older patients with dengue fever.

BACKGROUND: Older adults have a higher mortality for dengue fever (DF). However, the best method for predicting mortality is still unclear. AIMS: We conducted this study to evaluate the shock index (SI) for this issue. METHODS: A retrospective case-control study was conducted by recruiting older patients (≥ 65 years old) with DF who visited the study hospital in southern Taiwan during the 2015 DF outbreak. Demographic data, vital signs, past histories, decision groups, complications, and mortality were included in the analyses. We evaluated the accuracy of SI ≥ 1 for predicting 30-day mortality in this population. RESULTS: A total of 626 patients with a mean age of 74.1 years and nearly equal sex distribution were recruited. The mean of SI (± standard deviation [SD]) was 0.6 (± 0.2) and patients with a SI ≥ 1 accounted for 3.5% of the total patients. Logistic regression showed that patients with SI ≥ 1 had a higher mortality than those with SI < 1 (odds ratio: 8.49; 95% confidence interval: 1.76-17.92). The area under the receiver-operating characteristic was 0.76, and the Hosmer-Lemeshow goodness of fit test was 0.48. The SI ≥ 1 had a sensitivity, specificity, positive predictive value, and negative predictive value of 14.8%, 97.0%, 18.2%, and 96.2% for predicting mortality. CONCLUSIONS: The SI ≥ 1 is an easy tool that can be potentially used to predict 30-day mortality in older DF patients, especially in DF outbreak. It has a high specificity and negative predictive value for excluding patients with high-risk mortality.

Rat Hair Metabolomics Analysis Reveals Perturbations of Unsaturated Fatty Acid Biosynthesis, Phenylalanine, and Arachidonic Acid Metabolism Pathways Are Associated with Amyloid-ß-Induced Cognitive Deficits.

Hair is a noninvasive valuable biospecimen for the long-term assessment of endogenous metabolic disturbance. Whether the hair is suitable for identifying biomarkers of the Alzheimer's disease (AD) process remains unknown. We aim to investigate the metabolism changes in hair after ß-amyloid (Aß1-42) exposure in rats using ultra-high-performance liquid chromatography-high-resolution mass spectrometry-based untargeted and targeted methods. Thirty-five days after Aß1-42 induction, rats displayed significant cognitive deficits, and forty metabolites were changed, of which twenty belonged to three perturbed pathways: (1) phenylalanine metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis-L-phenylalanine, phenylpyruvate, ortho-hydroxyphenylacetic acid, and phenyllactic acid are up-regulated; (2) arachidonic acid (ARA) metabolism-leukotriene B4 (LTB4), arachidonyl carnitine, and 5(S)-HPETE are upregulation, but ARA, 14,15-DiHETrE, 5(S)-HETE, and PGB2 are opposite; and (3) unsaturated fatty acid biosynthesis- eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), FA 18:3 + 1O, and FA 18:3 + 2O are downregulated. Linoleic acid metabolism belonging to the biosynthesis of unsaturated fatty acid includes the upregulation of 8-hydroxy-9,10-epoxystearic acid, 13-oxoODE, and FA 18:2 + 4O, and downregulation of 9(S)-HPODE and dihomo-γ-linolenic acid. In addition, cortisone and dehydroepiandrosterone belonging to steroid hormone biosynthesis are upregulated. These three perturbed metabolic pathways also correlate with cognitive impairment after Aß1-42 stimulation. Furthermore, ARA, DHA, EPA, L-phenylalanine, and cortisone have been previously implicated in the cerebrospinal fluid of AD patients and show a similar changing trend in Aß1-42 rats' hair. These data suggest hair can be a useful biospecimen that well reflects the expression of non-polar molecules under Aß1-42 stimulation, and the five metabolites have the potential to serve as novel AD biomarkers.

Association between osteoarthritis and urinary tract infection in older adults: A nationwide population-based cohort study.

Osteoarthritis (OA) may increase urinary tract infection (UTI) in older adults. However, this issue remains unclear. We identified 8599 older patients (≥65 years) with OA, and an equal number of older patients without OA, matched by age, sex, and index date from the Taiwan National Health Insurance Research Database between 2001 and 2005. Past histories, including UTI and underlying comorbidities, were included in the analyses. Comparisons for any UTI, ≥1 hospitalization for UTI, and ≥3 hospitalizations for UTI between the 2 cohorts by following up until 2015 were performed. In both cohorts, the percentages of age subgroups were 65-74 years (65.7%), 75-84 years (30.1%), and ≥85 years (4.2%). The male sex was 42.4%. Patients with OA had an increased risk of any UTI compared with those without OA after adjusting for all past histories (adjusted hazard ratio [AHR]: 1.72; 95% confidence interval [CI]: 1.64-1.80). Compared with patients without OA, patients with OA also had an increased risk of ≥1 hospitalization for UTI and ≥3 hospitalizations for UTI (AHR: 1.13; 95% CI: 1.06-1.19 and AHR: 1.25; 95% CI: 1.13-1.38, respectively). In addition to OA, age 75-84 years, female sex, history of UTI, benign prostatic hyperplasia, indwelling urinary catheter, cerebrovascular disease, dementia, and urolithiasis were independent predictors for any UTI. This study showed that OA was associated with UTI in older adults. We suggest appropriately managing OA and controlling underlying comorbidities to prevent subsequent UTI.

Comparison of Risk for End-Stage Renal Disease Between Physicians and the General Population: A Nationwide Population-Based Cohort Study.

Physicians experience high stress and have much responsibility during a night shift, which contributes to increased sympathetic activity, the risk factor for renal disease. The risk for end-stage renal disease (ESRD) in physicians is still unclear. Therefore, we conducted a nationwide population-based cohort study to clarify this issue. Using Taiwan's National Health Insurance Research Database, we identified 30,268 physicians and 60,536 individuals from the general population matched with a ratio of 1:2 by age and sex. All participants who had ESRD before 2006 and residents were excluded. ESRD risk between physicians and the general population and among physician subgroups was compared by following up their medical histories until 2012. We also compared the treatments between both cohorts with ESRD. Physicians had a lower ESRD risk than the general population (adjusted odds ratio (AOR): 0.5; 95% confidence interval (CI): 0.4-0.7), particularly in the middle-age subgroup (35-64 years) (AOR: 0.4; 95% CI: 0.3-0.7); however, there was no difference in the older age subgroup (≥65 years) (AOR: 1.0; 95% CI: 0.6-1.7). More physicians received peritoneal dialysis (63.0% vs. 11.1%) and renal transplantation (5.6% vs. 1.7%) than the general population after being diagnosed with ESRD. Compared with the general population, physicians had a lower ESRD risk and higher treatment selection for peritoneal dialysis and renal transplantation after being diagnosed with ESRD. Better medical knowledge, a greater awareness of diseases and their risk factors, more rigorous implementation of preventive measures, and easy access to medical care may play a role in this aspect. Further studies are warranted for elucidating the associated mechanisms.