Health-related quality of life by veterans RAND 12 and healthcare resource utilization in cancer patients with sleep disorders: insights from the Medical Expenditure Panel Survey.

PURPOSE: This study aims to investigate the joint effects of cancer and sleep disorders on the health-related quality of life (HRQoL), healthcare resource utilization, and expenditures among US adults. METHODS: Utilizing the 2018-2019 Medical Expenditure Panel Survey (MEPS) database, a sample of 25,274 participants was categorized into four groups based on cancer and sleep disorder status. HRQoL was assessed using the VR-12 questionnaire. Generalized linear model (GLM) with a log-linear regression model combined gamma distribution was applied for the analysis of healthcare expenditure data. RESULTS: Individuals with both cancer and sleep disorders (C+/S+) exhibited notably lower physical health (PCS) and mental health (MCS) scores-1.45 and 1.87 points lower, respectively. They also showed significantly increased clinic visits (2.12 times), outpatient visits (3.59 times), emergency visits (1.69 times), and total medical expenditures (2.08 times) compared to those without cancer or sleep disorders (C-/S-). In contrast, individuals with sleep disorders alone (C-/S+) had the highest number of prescription drug usage (2.26 times) and home health care days (1.76 times) compared to the reference group (C-/S-). CONCLUSIONS: Regardless of cancer presence, individuals with sleep disorders consistently reported compromised HRQoL. Furthermore, those with cancer and sleep disorders experienced heightened healthcare resource utilization, underscoring the considerable impact of sleep disorders on overall quality of life. IMPLICATIONS FOR CANCER SURVIVORS: The findings of this study address the importance of sleep disorders among cancer patients and their potential implications for cancer care. Healthcare professionals should prioritize screening, education, and tailored interventions to support sleep health in this population.

Healthcare Utilization and Its Correlates in Comorbid Type 2 Diabetes Mellitus and Generalized Anxiety Disorder.

This study investigated the healthcare utilization and medical expenditure of type 2 diabetes mellitus (T2DM) patients with generalized anxiety disorder (GAD) and identified the associated factors. The healthcare utilization and expenditure of T2DM patients with (case group) and without (control group) GAD between 2002 and 2013 were examined using the population-based Taiwan National Health Insurance Research Database. Healthcare utilization included outpatient visits and hospitalization; health expenditure included outpatient, inpatient, and total medical expenditure. Moreover, nonpsychiatric healthcare utilization and medical expenditure were distinguished from total healthcare utilization and medical expenditure. The average healthcare utilization, including outpatient visits and hospitalization, was significantly higher for the case group than for the control group (total and nonpsychiatric). The results regarding differences in average outpatient expenditure (total and nonpsychiatric), inpatient expenditure (total and nonpsychiatric), and total expenditure (total and nonpsychiatric) between the case and control groups are inconsistent. Sex, age, income, comorbidities/complications, and the diabetes mellitus complication severity index were significantly associated with outpatient visits, medical expenditure, and hospitalization in the case group (total and nonpsychiatric). Greater knowledge of factors affecting healthcare utilization and expenditure in comorbid individuals may help healthcare providers intervene to improve patient management and possibly reduce the healthcare burden in the future.

A Taiwan Nationwide Population-Based Study of Socio-Demographic Factors and Comorbid Conditions Associated with Non-Arteritic Anterior Ischaemic Optic Neuropathy.

AIMS: The aim of the study was to investigate the socio-demographic factors and systemic conditions associated with non-arteritic anterior ischaemic optic neuropathy (NAION). METHODS: This was a nationwide population-based retrospective case-controlled study that recruited 9,261 NAION patients selected from the Taiwan National Health Insurance Research Database. The control group consisted of 9,261 age-, sex-, and index date-matched non-NAION patients recruited from the Taiwan Longitudinal Health Insurance Database, 2000. NAION was designated in the database by the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) as "code 377.41: ischaemic optic neuropathy without ICD-9-CM code 446.5: giant cell arteritis." Associated socio-demographic factors and systemic medical conditions were analysed using the McNemar's test, and continuous variables were analysed using the paired t test. The odds ratio (OR) and adjusted OR of developing NAION were compared using univariate logistic regression and multivariable logistic regression analyses, respectively. RESULTS: Patients with systemic conditions such as diabetes mellitus, hypertension, hyperlipidaemia, chronic kidney disease, and hypotension were more likely to develop NAION than controls (adjusted OR = 1.81, 95% confidence interval [CI] = 1.67-1.97, p < 0.0001; adjusted OR = 1.46, 95% CI = 1.36-1.57, p < 0.0001; adjusted OR = 1.44, 95% CI = 1.33-1.57, p < 0.0001; adjusted OR = 3.26, 95% CI = 2.65-4.01, p < 0.0001; adjusted OR = 2.32, 95% CI = 1.31-4.10, p = 0.0039, respectively). CONCLUSIONS: NAION is strongly associated with diabetes mellitus, hypertension, hyperlipidaemia, chronic kidney disease, and hypotension.

Using artificial intelligence to predict adverse outcomes in emergency department patients with hyperglycemic crises in real time.

BACKGROUND: Hyperglycemic crises are associated with high morbidity and mortality. Previous studies have proposed methods to predict adverse outcomes of patients in hyperglycemic crises; however, artificial intelligence (AI) has never been used to predict adverse outcomes. We implemented an AI model integrated with the hospital information system (HIS) to clarify whether AI could predict adverse outcomes. METHODS: We included 2,666 patients with hyperglycemic crises from emergency departments (ED) between 2009 and 2018. The patients were randomized into a 70%/30% split for AI model training and testing. Twenty-two feature variables from the electronic medical records were collected. The performance of the multilayer perceptron (MLP), logistic regression, random forest, Light Gradient Boosting Machine (LightGBM), support vector machine (SVM), and K-nearest neighbor (KNN) algorithms was compared. We selected the best algorithm to construct an AI model to predict sepsis or septic shock, intensive care unit (ICU) admission, and all-cause mortality within 1 month. The outcomes between the non-AI and AI groups were compared after implementing the HIS and predicting the hyperglycemic crisis death (PHD) score. RESULTS: The MLP had the best performance in predicting the three adverse outcomes, compared with the random forest, logistic regression, SVM, KNN, and LightGBM models. The areas under the curves (AUCs) using the MLP model were 0.852 for sepsis or septic shock, 0.743 for ICU admission, and 0.796 for all-cause mortality. Furthermore, we integrated the AI predictive model with the HIS to assist decision making in real time. No significant differences in ICU admission or all-cause mortality were detected between the non-AI and AI groups. The AI model performed better than the PHD score for predicting all-cause mortality (AUC 0.796 vs. 0.693). CONCLUSIONS: A real-time AI predictive model is a promising method for predicting adverse outcomes in ED patients with hyperglycemic crises. Further studies recruiting more patients are warranted.

New diagnosis of cancer in mild and moderate/severe traumatic brain injury patients in a 12-year population-based study.

BACKGROUND: Traumatic brain injury (TBI) has been reported as a risk factor for brain cancer development. However, the magnitude of the impact of TBI on systemic cancer development has not been clarified. METHODS: A retrospective longitudinal cohort study was conducted using the Taiwan Longitudinal Health Insurance Database between January 2000 and December 2011. A total of 35,306 patients were initially enrolled, and 14,795 patients with mild TBI and 14,795 patients with moderate/severe TBI were matched using the National Health Insurance Research Database in Taiwan. The Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of TBI adjusted for potential confounding factors. RESULTS: After matching, the results showed that patients with moderate/severe TBI had a high mortality rate (17.7% vs. 10.4%) and shorter time interval from TBI to death (mean 3.6 years vs. 5.8 years). No differences were observed in cancer incidence (4.1% vs. 4.1%) or risk factors for mortality between mild and moderate/severe TBI patients. However, patients aged between 46 and 55 years, female patients, and patients with pre-existing renal disease had a significant higher cancer incidence risk in moderate/severe TBI compared with mild TBI patients. The top 15 most common cancers showed that mild TBI patients had a higher percentage of head and neck cancer. The overall mortality rate in all TBI patients diagnosed with cancer was about 50%, and the cancer-specific mortality is approximately 85% in death of TBI patients with cancer. CONCLUSIONS: We concluded that the incidence risk of a new cancer diagnosis and mortality risk of TBI patients with cancer between the mild TBI and moderate/severe TBI patients were not significantly different.

An artificial intelligence approach for predicting cardiotoxicity in breast cancer patients receiving anthracycline.

Although anti-cancer therapy-induced cardiotoxicity is known, until now it lacks a reliable risk predictive model of the subsequent cardiotoxicity in breast cancer patients receiving anthracycline therapy. An artificial intelligence (AI) with a machine learning approach has yet to be applied in cardio-oncology. Herein, we aimed to establish a predictive model for differentiating patients at a high risk of developing cardiotoxicity, including cancer therapy-related cardiac dysfunction (CTRCD) and symptomatic heart failure with reduced ejection fraction. This prospective single-center study enrolled patients with newly diagnosed breast cancer who were preparing for anthracycline therapy from 2014 to 2018. We randomized the patients into a 70%/30% split group for ML model training and testing. We used 15 variables, including clinical, chemotherapy, and echocardiographic parameters, to construct a random forest model to predict CTRCD and heart failure with a reduced ejection fraction (HFrEF) during the 3-year follow-up period (median, 30 months). Comparisons of the predictive accuracies among the random forest, logistic regression, support-vector clustering (SVC), LightGBM, K-nearest neighbor (KNN), and multilayer perceptron (MLP) models were also performed. Notably, predicting CTRCD using the MLP model showed the best accuracy compared with the logistic regression, random forest, SVC, LightGBM, and KNN models. The areas under the curves (AUC) of MLP achieved 0.66 with the sensitivity and specificity as 0.86 and 0.53, respectively. Notably, among the features, the use of trastuzumab, hypertension, and anthracycline dose were the major determinants for the development of CTRCD in the logistic regression. Similarly, MLP, logistic regression, and SVM also showed higher AUCs for predicting the development of HFrEF. We also validated the AI prediction model with an additional set of patients developing HFrEF, and MLP presented an AUC of 0.81. Collectively, an AI prediction model is promising for facilitating physicians to predict CTRCD and HFrEF in breast cancer patients receiving anthracycline therapy. Further studies are warranted to evaluate its impact in clinical practice.

Associations between dietary patterns and stages of chronic kidney disease.

BACKGROUND: Studies have revealed that patients with chronic kidney disease (CKD) have dietary patterns different from those of the general population. However, no studies have compared the dietary patterns of between patients with early-stages (stages 1-3a) and late-stages (stages 3b-5) of CKD. Our objective was to investigate the associations between dietary patterns in early and late-stage CKD. METHODS: We analyzed 4480 participants with CKD at various stages based on the data recorded between 2007 and 2016 from the database of the American National Health and Nutrition Examination Survey. RESULTS: In total, 3683 and 797 participants had early and late-stage CKD, respectively. Through principal components analysis, the dietary intake dimension was reduced from 63 variables to 3 dietary patterns. We adopted logistic regression for analysis. The three dietary patterns are as follows: (1) saturated fatty acids and mono-unsaturated fatty acids (MUFA); (2) vitamins and minerals; and (3) cholesterols and polyunsaturated fatty acids (PUFA). These 3 patterns explained > 50% of dietary nutrient intake. Results indicated that among participants with dietary patterns 2 (vitamins and minerals) and 3 (cholesterols and PUFA), those with low intakes were more likely to have late-stage CKD. The odds ratios for patterns 2 and 3 were 1.74 (95% CI: 1.21-2.50) and 1.66 (95% CI: 1.13-2.43), respectively. CONCLUSIONS: This study revealed that intakes of vitamins and minerals and cholesterols and PUFA were associated with the stages of CKD.

Implementation of a machine learning application in preoperative risk assessment for hip repair surgery.

BACKGROUND: This study aims to develop a machine learning-based application in a real-world medical domain to assist anesthesiologists in assessing the risk of complications in patients after a hip surgery. METHODS: Data from adult patients who underwent hip repair surgery at Chi-Mei Medical Center and its 2 branch hospitals from January 1, 2013, to March 31, 2020, were analyzed. Patients with incomplete data were excluded. A total of 22 features were included in the algorithms, including demographics, comorbidities, and major preoperative laboratory data from the database. The primary outcome was a composite of adverse events (in-hospital mortality, acute myocardial infarction, stroke, respiratory, hepatic and renal failure, and sepsis). Secondary outcomes were intensive care unit (ICU) admission and prolonged length of stay (PLOS). The data obtained were imported into 7 machine learning algorithms to predict the risk of adverse outcomes. Seventy percent of the data were randomly selected for training, leaving 30% for testing. The performances of the models were evaluated by the area under the receiver operating characteristic curve (AUROC). The optimal algorithm with the highest AUROC was used to build a web-based application, then integrated into the hospital information system (HIS) for clinical use. RESULTS: Data from 4,448 patients were analyzed; 102 (2.3%), 160 (3.6%), and 401 (9.0%) patients had primary composite adverse outcomes, ICU admission, and PLOS, respectively. Our optimal model had a superior performance (AUROC by DeLong test) than that of ASA-PS in predicting the primary composite outcomes (0.810 vs. 0.629, p < 0.01), ICU admission (0.835 vs. 0.692, p < 0.01), and PLOS (0.832 vs. 0.618, p < 0.01). CONCLUSIONS: The hospital-specific machine learning model outperformed the ASA-PS in risk assessment. This web-based application gained high satisfaction from anesthesiologists after online use.

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.

Association between chronic kidney disease and the most common corneal ectasia disease (keratoconus): a nationwide cohort study.

BACKGROUND: Both keratoconus (KCN) and chronic kidney disease (CKD) are multifactorial conditions with multiple aetiologies and share several common pathophysiologies. However, the few studies that have described the relationship between KCN and CKD are limited to case reports and small case series. This study aimed to evaluate the association between KCN and CKD. METHODS: The study cohort included 4,609 new-onset keratoconus patients ≥ 12 years identified by the International Classification of Diseases, Ninth Revision, Clinical Modification, code 371.6 and recruited between 2004 and 2011 from the Taiwan National Health Insurance Research Database. The age-, sex-, and comorbidity-matched control group included 27,654 non-KCN patients, selected from the Taiwan Longitudinal Health Insurance Database, 2000. Information for each patient was collected and tracked from the index date until December 2013. The incidence and risk of CKD were compared between the two groups. The adjusted hazard ratios (HRs) for CKD were calculated with Cox proportional hazard regression analysis. Kaplan-Meier analysis was used to calculate the cumulative CKD incidence rate. RESULTS: The incidence rate of CKD was 1.36 times higher in KCN patients than in controls without statistically significant difference (95 % confidence interval [CI] = 0.99-1.86, p = 0.06). In total, 29 male KCN patients and 90 male controls developed CKD during the follow-up period. The incidence rate of CKD was 1.92 times (95 % [CI] = 1.26-2.91; p = 0.002) higher in male KCN patients than in controls. After adjusting for potential confounders, including age, hypertension, hyperlipidaemia, and diabetes mellitus, male KCN patients were 1.75 times (adjusted HR = 1.75, 95 % [CI] = 1.14-2.68, p < 0.05) more likely to develop CKD. CONCLUSIONS: We found that male KCN patients have an increased risk of CKD. Therefore, it is recommended that male KCN patients should be aware of CKD.

Competing risk analysis of the association between dementia and major depressive disorder: a nationwide population-based study in Taiwan.

Objectives: To investigate the association between major depressive disorder (MDD) and the competing risk of Alzheimer's dementia (AD) and non-Alzheimer's dementia (NAD) using a nationwide population-based health insurance database.Methods: From Taiwan's National Health Insurance Research Database, we extracted claims data of 13,067 patients with MDD and 52,268 non-MDD controls matched by index date, age, sex, geographical area, monthly income, and selected comorbidities through propensity score matching. Follow-up durations in person-years were calculated for each person until dementia diagnosis, death, or the end of 2013. Competing incident risks of AD and NAD between patients with MDD and non-MDD.Results: In this study, 335 (2.6%) of the 13,067 MDD patients and 313 (0.6%) of the 52,268 non-MDDs developed AD. During the follow-up period, 73 (0.59%) of the 13,067 MDD patients developed NAD and 80 (0.15%) of the 52,268 non-MDD developed NAD. The patients with MDD had 4.73 and 3.69 times higher risks of AD (adjusted subdistribution hazard ratio [SHR] 4.73; 95% confidence interval [CI] 4.05-5.52) and NAD (adjusted SHR 3.69; 95% CI 2.68-5.08), respectively, than the controls.Conclusions: The patients with MDD had significantly higher incidence rates of AD and NAD than the controls, in particular among aged 65 and above. Additional studies are required to clarify the underlying pathophysiology between the MDD-dementia association and investigate whether prompt intervention in MDD can reduce the risk of dementia.

Site-specific mortality in native joint septic arthritis: a national population study.

OBJECTIVE: This national cohort study investigated the incidence, site-specific mortality and prognostic factors of native septic arthritis (SA). METHODS: Tapping Taiwan's National Health Insurance Research Database, we identified inpatients with newly diagnosed SA between 1998 and 2012. They were categorized by site of infection and followed to calculate 30-day, 90-day and 1-year mortality. Predictors of mortality were calculated using Cox models. RESULTS: A total of 31 491 patients were identified as having SA, the most common site of infection being the knee (50.1%), followed by the hip (14.4%), other sites (26.8%), the shoulder (5.5%) and multiple sites (1.2%). Knee joint involvement was the most common site for all subgroups. Incidence increased from 9.8/105 in 1998 to 13.3/105 in 2012. The 30-day, 90-day and 1-year mortality rates were 4.3, 8.6 and 16.4% respectively. Predictors for mortality were hip infection, shoulder infection, multiple-site infection, being male, age ≥65 years old and comorbidities. We derived a mortality scoring model over age/SA site/comorbidity, and age ≥65 years old had the greatest risk contribution to mortality. No matter whether 1-month, 3-month or 1-year mortality was being considered, patients with the higher risk scores had the higher mortality rates (P < 0.0001). CONCLUSION: SA is an emerging infectious disease with a rising incidence, long duration of hospital stay and high mortality rate. The most common affected joint was knee for all subgroups. Patients aged ≥65 years old had a high SA incidence and the greatest risk contribution.

Risk of Dementia in Diabetic Patients with Hyperglycemic Crisis: A Nationwide Taiwanese Population-Based Cohort Study.

BACKGROUND: A hyperglycemic crisis episode (HCE) signifies poor control of diabetes and may increase the risk of dementia via microvascular and macrovascular injuries. OBJECTIVES: We conducted this study to clarify this issue, which remains unclear. METHODS: Using the Taiwan National Health Insurance Database, we identified 9,466 diabetic patients with HCE and the identical number of diabetic patients without HCE who were matched by age and sex for this nationwide population-based cohort study. The risk of dementia was compared between the 2 cohorts by following up until 2014. Investigation of independent predictors of dementia was also done. RESULTS: In the overall analysis, the risk of dementia between the 2 cohorts was not different. However, stratified analyses showed that patients with HCE had a higher risk of subsequent dementia in the age subgroup of 45-54 and 55-64 years (adjusted odds ratio [AOR]: 2.4, 95% confidence interval [CI]: 1.6-3.6, and AOR: 1.2, 95% CI: 1.0-1.5, respectively). In the overall analysis, older age, female sex, ≥3 HCEs, hypertension, hyperlipidemia, depression, cerebrovascular disease, Parkinson's disease, and head injury were independent predictors. CONCLUSIONS: HCE increased the risk of dementia in diabetic patients aged 45-64 years. Dementia was predicted by ≥3 HCEs. Prevention of recurrent HCE, control of comorbidities, and close follow-up of cognitive decline and dementia are suggested in patients with HCE.

Chronic Pain Increases the Risk for Major Adverse Cardiac and Cerebrovascular Events: A Nationwide Population-Based Study in Asia.

OBJECTIVE: Chronic pain (CP) may increase the risk for major adverse cardiac and cerebrovascular events (MACCEs); however, this issue is still unclear in the Asian population. We conducted this study to delineate it. DESIGN: From the Taiwan National Health Insurance Research Database, we identified 17,614 participants (<65 years) with CP and matched them by age and sex at a 1:2 ratio to participants without CP, who made up the comparison cohort. Several causes of CP and its underlying comorbidities were also analyzed. OUTCOME MEASURE: A comparison of MACCE occurring in the two cohorts was performed via follow-up until 2015. RESULTS: The mean age (SD) was 50.2 (11.5) years and 50.4 (11.7) years in participants with and without CP, respectively. In both cohorts, the percentage of female participants was 55.5%. Common causes of CP were spinal disorders (23.9%), osteoarthritis (12.4%), headaches (11.0%), gout (10.2%), malignancy (6.2%), and osteoporosis (4.5%). After adjusting for hypertension, diabetes, chronic obstructive pulmonary disease, renal diseases, hyperlipidemia, liver diseases, dementia, and depression, participants with CP had a higher risk for MACCE than those without CP (adjusted hazard ratio [AHR] = 1.3, 95% confidence interval [CI] = 1.3 - 1.4). After conducting subgroup analyses, an increased risk was also found for all-cause mortality (AHR = 1.4, 95% CI = 1.1 - 1.8), acute myocardial infarction (AHR = 1.2, 95% CI = 1.0 - 1.4), and stroke (AHR = 1.3, 95% CI = 1.3 - 1.4). CONCLUSIONS: CP is associated with increased occurrence of MACCE. Early detection and interventions for CP are suggested.

Association between exercise and health-related quality of life and medical resource use in elderly people with diabetes: a cross-sectional population-based study.

BACKGROUND: Exercise improves glycemic control and functional capacity in elderly people with diabetes; however, its effect on health-related quality of life (HRQoL) and medical resource use remains unclear. This study aims to clarify the effect of exercise. METHODS: Using the data from National Health and Nutrition Examination Survey between 2007 and 2016, we identified 1572 elderly people with diabetes for this cross-sectional population-based study. Demographic characteristics, health conditions, comorbidities, HRQoL, and medical resource were compared among four groups (no exercise, low-intensity exercise, moderate-intensity exercise, and high-intensity exercise). RESULTS: The mean age of all participants was between 71.5 and 73.3 years. Male participants with higher education performed more exercise than their counterparts. The moderate- and high-intensity groups reported better general health condition than the no exercise group. Depression and worse health were more common in the no exercise group. Participants in the moderate-intensity exercise group had lower risk for depression than those in the no exercise group (adjusted odds ratio: 0.13, 95% confidence interval: 0.02-0.92) after adjusting for demographic characteristics, health conditions, and comorbidities, whereas participants in the low- and high-intensity exercise did not have a lower risk. The no exercise group had the highest proportions of emergency, hospitalization, and total healthcare visits. CONCLUSIONS: Exercise is associated with better HRQoL, and lack of exercise is associated with higher medical resource use in elderly people with diabetes. Encouraging exercise is recommended in this population.

Comparison of the risk for dementia between physicians and the general population: a nationwide population-based cohort study.

BACKGROUND: Physicians have better medical knowledge, which may decrease the risk of dementia; however, this issue remains unclear. This study was performed to clarify it. METHODS: We conducted a nationwide population-based study that recruited 29,388 physicians, 50,000 participants from the general population, and 30,446 other healthcare professionals (HCPs; excluding physicians) for this study. The prevalence of dementia was compared among the three groups and physician subgroups by tracing their medical histories from 2006 to 2012. RESULTS: Physicians had a lower prevalence of dementia than the general population after adjusting for age, sex, head trauma, hypothyroidism, hypertension, diabetes mellitus, stroke, vascular disease, atrial fibrillation, hypercholesterolemia, depression, and alcoholism [adjusted odds ratio (AOR) 0.56; 95% confidence interval (CI) 0.47-0.67]. Other HCPs also had a lower prevalence for dementia than the general population (AOR 0.46; 95% CI 0.36-0.60). Compared with other HCPs, physicians had no difference in the prevalence for dementia (AOR 0.98 95% CI 0.71-1.36). Physicians who were older, specialized in pediatrics and worked at local hospitals and clinics had a higher prevalence for dementia than their counterparts did. CONCLUSIONS: Physicians had a lower prevalence for dementia than the general population. The prevalence for dementia in specific subgroups of physicians was higher, which needs to be clarified by further studies.

Prophylactic diphenhydramine attenuates postoperative catheter-related bladder discomfort in patients undergoing gynecologic laparoscopic surgery: a randomized double-blind clinical study.

BACKGROUND: To evaluate the effectiveness of diphenhydramine, an antihistamine with anti-muscarinic properties, for prevention of postoperative catheter-related bladder discomfort (CRBD). METHODS: Ninety-six ASA physical status I and II adult female patients (20-60 years) scheduled for elective gynecologic laparoscopic surgery were included. Patients were randomized into two groups of 48 patients each. All patients received a detailed preoperative explanation of the possible consequences of CRBD. The control group received normal saline 2 ml, whereas the diphenhydramine group received diphenhydramine 30 mg intravenously after induction of general anesthesia. Then, all patients were catheterized with a 14F Foley catheter and the balloon was inflated with 10 ml of distilled water. All patients who complained of CRBD in the postoperative room were appeased with nursing. Ketorolac 30 mg was used as the rescue drug on patients' request or when the patient was evaluated as having moderate or severe CRBD. Bladder discomfort and its severity were assessed at 1, 2 and 6 h postoperatively. The severity of CRBD was graded as none, mild, moderate and severe. Adverse effects of diphenhydramine such as sedation, dry mouth or GI upset were recorded. RESULTS: The incidence of CRBD was lower in the diphenhydramine group compared with the control group at 2 h (34.8 vs. 58.7%, p = 0.02) and 6 h (23.9 vs. 56.5%, p < 0.01) postoperatively. Diphenhydramine treatment also reduced the severity of CRBD at 6 h postoperatively (p = 0.01). Moreover, the request for rescue for CRBD was lower in diphenhydramine group at 2 h (8.7 vs. 26.1%, p = 0.03). There were no significant differences in side effects, such as sedation, dry mouth or gastrointestinal upset between the two groups (p > 0.05). CONCLUSION: Prophylactic diphenhydramine 30 mg at induction of general anesthesia reduced the incidence and severity of postoperative bladder discomfort without significant side effects in patients receiving gynecologic laparoscopic surgery.

Phentolamine Reverses Epinephrine-Enhanced Skin Antinociception of Dibucaine in Rats.

BACKGROUND: The objective of the experiment was to assess the antinociceptive effect of dibucaine, bupivacaine, and epinephrine. To assess the mechanism of action of the interaction between dibucaine and epinephrine, phentolamine, a nonselective α-adrenergic antagonist, was added to the mixture. METHODS: We assessed sensory blockade with these drugs by injecting 0.6 mL of drug-in-saline in the dorsal thoracolumbar area of rats; pinprick of the "wheal" formed by the injectate was the area targeted for stimulation to elicit a cutaneous trunci muscle reflex. The sensory block of dibucaine was compared with that of bupivacaine or epinephrine. Drug-drug interactions were analyzed by isobologram. Phentolamine was added to investigate the antinociceptive effect of dibucaine coinjected with epinephrine. RESULTS: We demonstrated that dibucaine, epinephrine, and bupivacaine produced dose-dependent skin antinociception. On the median effective dose (ED50) basis, the potency was higher for epinephrine (mean, 0.011 [95% confidence interval {CI}, 0.007-0.015] µmol) than for dibucaine (mean, 0.493 [95% CI, 0.435-0.560] µmol) (P < .01), while there were no significant differences between dibucaine and bupivacaine (mean, 0.450 [95% CI, 0.400-0.505] µmol). On the equipotent basis (75% effective dose, median effective dose, and 25% effective dose), sensory block duration provoked by epinephrine was greater (P < .01) than that provoked by dibucaine or bupivacaine. Coadministration of dibucaine with epinephrine produced a synergistic nociceptive block, whereas phentolamine blocked that synergistic block. CONCLUSIONS: The preclinical data indicated that there is no statistically significant difference between the potency and duration of dibucaine and bupivacaine in this model. Epinephrine synergistically enhances the effects of dibucaine, while phentolamine partially blocked those effects. α-Adrenergic receptors play an important role in controlling synergistic analgesic effect of dibucaine combined with epinephrine.

Risk of diabetes mellitus in physicians: a nationwide study in Taiwan.

BACKGROUND: The heavy workload of physicians in Taiwan may contribute to poor lifestyles and increased risk for diabetes mellitus (DM). We conducted this study to determine the risk for DM among physicians in Taiwan. METHODS: We used the Taiwan National Health Insurance Research Database to identify 28,440 physicians and 56,880 comparisons (general population) matched at a ratio of 1:2 by age and sex. Participants who had been diagnosed with DM before 2007 were excluded. We compared the risk for DM between physicians and comparisons by following up since 2007 to 2013. Comparisons among physician subgroups were also performed. RESULTS: After adjustment for hypertension, hyperlipidemia, hyperuricemia, coronary artery disease, congestive heart failure, hyperthyroidism, hypothyroidism, and polycystic ovary syndrome, physicians had a lower risk for DM than the comparisons (adjusted odds ratio [AOR]: 0.75; 95% confidence interval [CI]: 0.68-0.82). In comparisons among physicians, emergency physicians (AOR: 2.21; 95% CI: 1.44-3.40) and surgeons (AOR: 1.26; 95% CI: 1.05-1.52) had a higher risk for DM than other specialists. CONCLUSIONS: This study found that physicians have a lower risk for DM than the general population and emergency physicians and surgeons have a higher risk for DM than other specialists. Thus, more attention should be paid to the occupational health of these doctors.

Risk for cervical herniated intervertebral disc in dentists: a nationwide population-based study.

BACKGROUND: Prolonged static postures (PSPs) may predispose dentists to develop cervical herniated intervertebral disc (C-HIVD); however, there is limited evidence supporting this in the literature thus far. We conducted this study to fit the data gap. METHODS: We conducted a retrospective nationwide population-based study using the Taiwan National Health Insurance Research Database to identify 10,930 dentists, an identical number of age- and sex-matched participants from the general population, and 73,718 other health care providers (HCPs, non-dentists). Comparisons for the risk of developing C-HIVD between dentists and the general population, and between dentists and other HCPs were performed by tracing their medical histories between 2007 and 2011. RESULTS: Dentists had a cumulative incidence rate of 1.1% for C-HIVD during the 5-year follow-up period. Overall, there was no difference of the risk for C-HIVD between dentists and the general population after adjusting for hypertension, hyperlipidemia, liver disease, mental disorders, diabetes mellitus, coronary artery disease, chronic obstructive pulmonary disease, malignancy, stroke, and renal disease (adjusted odds ratio [AOR]: 1.2, 95% confidence interval [CI]: 0.9-1.6). However, stratified analysis showed that younger dentists (≤ 34 years) had a trend of higher risk for C-HIVD than members of the younger general population (AOR: 1.9, 95% CI: 0.9-4.1). There was no difference found between dentists and other HCPs (AOR: 0.9, 95% CI: 0.8-1.1). CONCLUSION: Younger dentists had a trend of higher risk of developing C-HIVD than members of the general population.