Differences in Spontaneous Intracerebral Hemorrhage Cases between Urban and Rural Regions of Taiwan: Big Data Analytics of Government Open Data

Incidence, subtypes, sex differences and trends of stroke in Taiwan

BACKGROUND

Chinese populations have been reported higher incidence of all strokes and intracerebral hemorrhage. However, few large-scale studies have evaluated changes of stroke epidemiology in the 21st century.

METHODS

We explored the rates of incidence of all first-ever strokes, subtypes, and 1-month case fatality by using data from the Taiwan National Health Insurance Research Database since 2004. Also, we investigated sex differences in stroke. Time-trend analysis was performed for incidence and case fatality rates of all strokes and subtypes in both sexes.

RESULTS

The age-adjusted incidence of all strokes per 100,000 person-years decreased by 16%, from 251 (95% confidence interval [CI] 249-253) in 2004 to 210 (95% CI 209-212) in 2011 (p<0.001); it was always higher in Chinese men than in women. Among pathological subtypes, the incidence of intracerebral hemorrhage markedly decreased by 26% over the years (p<0.001), while that of ischemic stroke slightly decreased by 8%. However, when stratified by sex, the incidence of ischemic stroke decreased significantly in only women, not in men (men: p = 0.399, women: p = 0.004). Regarding the incidence of subarachnoid hemorrhage, it remained unchanged. Furthermore, the rate of 1-month case fatality decreased significantly for all strokes in both sexes (p<0.001).

CONCLUSIONS

In Taiwan, the incidence rate of first-ever stroke decreased in both Chinese men and women in the early 21st century. Men had a higher incidence rate than women. Furthermore, a marked decrease was noted in the incidence of intracerebral hemorrhage, while a slight decrease was noted in that of ischemic stroke; however, the decreased incidence of ischemic stroke was significant in only women.

Diseases That Occur Prior to Spontaneous Intracerebral Hemorrhage: Identification of Predisposing and Risk Factors Using Lag Sequential Analysis

Spontaneous intracerebral hemorrhage (sICH) has many predisposing/risk factors. Lag sequential analysis (LSA) is a method of analyzing sequential patterns and their associations within categorical data in different system states. The results of this study will assist in preventing sICH and improving the patient outcome after sICH. The correlations between a first sICH and previous clinic visits were examined using LSA with data obtained from the Taiwan National Health Insurance Research Database (NHIRD). In this study, LSA was employed to examine the data in the Taiwan NHIRD in order to identify predisposing and risk factors related to sICH, and the results increased our knowledge of the temporal relationships between diseases. This study employed LSA to identify predisposing/risk factors prior to the first occurrence of sICH using a healthcare administrative database in Taiwan. The data were managed using the clinical classification software (CCS). All cases of traumatic ICH were excluded. Ten disease groups were identified using CCS. Hypertension and dizziness/vertigo were identified as two important predisposing/risk factors for sICH, and early treatment of hypertension resulted in a greater survival rate. Five disease groups were found to have occurred prior to other diseases and affected mostly the elderly, resulting in subsequent sICH. The results of this study also showed that nutritional status and tooth health were highly associated with the occurrence of sICH owing to a poor state of the digestive system. In conclusion, there are many diseases that influence the risk of a subsequent sICH. This study demonstrated that LSA is a very useful tool for future study of healthcare administrative databases.

Measuring Spatial Accessibility to Hospitals of Acute Myocardial Infarction in Multi Period Scale: A Case Study in Shijingshan District, Beijing, China

The hospital accessibility of Acute Myocardial Infarction (AMI) emergency treatment is of great importance, not only for improving the survival rate of patients but also for protecting the basic human right to health care. Traditional AMI emergency treatment research often does not consider ways to shorten the travel time to hospitals for AMI patients and does not reflect the actual time it takes to travel to hospitals, which is critical to AMI emergency treatment. To avoid these shortcomings, this study proposes a method of accessibility measurement based on Web Mapping API (Application Programming Interface) to obtain travel time to hospitals during different periods, then calculated the AMI hospital accessibility based on these detailed data. This study considered the Shijingshan District, Beijing, China, as an empirical case. The study discovered significant differences in the temporal and spatial characteristics of the AMI hospital accessibility on weekdays and weekends. The analysis revealed that travel time to hospitals and traffic congestion are the two main factors affecting AMI hospital accessibility. The research results shed new light on the accessibility of urban medical facilities and provide a scientific basis with which local governments can optimize the spatial structure of medical facilities.

A Clinical Decision Support System for Diabetes Patients with Deep Learning: Experience of a Taiwan Medical Center

Background: Diabetes mellitus (DM) is a major public health problem worldwide. It involves dysfunction of blood sugar regulation resulting from insulin resistance, inadequate insulin secretion, or excessive glucagon secretion. Methods: This study collated 971,401 drug usage records of 51,009 DM patients. These data include patient identification code, age, gender, outpatient visiting dates, visiting code, medication features (included items, doses, and frequencies of drugs), HbA1c results, and testing time. We apply a random forest (RF) model for feature selection and implement a regression model with the bidirectional long short-term memory (Bi-LSTM) deep learning architecture. Finally, we use the root mean square error (RMSE) as the evaluation index for the prediction model. Results: After data cleaning, the data included 8,729 male and 9,115 female cases. Metformin was the most important feature suggested by the RF model, followed by glimepiride, acarbose, pioglitazone, glibenclamide, gliclazide, repaglinide, nateglinide, sitagliptin, and vildagliptin. The model performed better with the past two seasons in the training data than with additional seasons. Further, the Bi-LSTM architecture model performed better than support vector machines (SVMs). Discussion & Conclusion: This study found that Bi-LSTM models is a well kernel in a CDSS which help physicians' decision-making, and the increasing the number of seasons will negative impact the performance. In addition, this study found that the most important drug is metformin, which is recommended as first-line treatment OHA in various situations for DM patients.

Distinct Behavior of Traumatic versus Nontraumatic Intracerebral Hematomas: Different Biology or Impact of Age?

BACKGROUND AND STUDY AIMS

 Patients with large intracerebral hematomas (ICH) may demonstrate different demographics and underlying brain and systemic diseases, as well as different radiologic courses and distinct outcomes. It remains unclear whether their different behavior attributes to a different biology of the ICH or to the asymmetric characteristics of the two populations. To analyze and adjust for potential sources of selection and treatment bias, our study compared age-matched patients with traumatic and nontraumatic ICH in a single cohort diagnosed and treated in the same surgical department.

MATERIAL AND METHODS

 We analyzed 135 consecutive patients with traumatic (n = 90) or spontaneous ICH (n = 45) undergoing treatment at a surgical intensive care unit of an urban university hospital. We documented their differences before and after adjustment for age in terms of demographics, the therapies applied, their radiologic (i.e., volume and rate of ICH expansion [HE]) and clinical (patients' outcome at 30 days) course, the length of hospital and ICU stay, as well as the hospital costs.

RESULTS

 Patients with traumatic ICH demonstrated more favorable clinical and radiologic characteristics at admission, that is, higher Glasgow Coma Scale score (p < 0.001), less frequently dilated pupil (p = 0.028), lower Charlson Comorbidity Index (p < 0.001), smaller ICH volume (p < 0.001), noneloquent (p < 0.001) or nonintraventricular (p = 0.003) ICH locations, as well as underwent fewer neurosurgical interventions (p < 0.001) and showed a better outcome (p = 0.041), defined as Glasgow Outcome Scale 4 and 5. After adjustment for age, no different outcomes were observed. Of note, elderly patients on novel oral anticoagulants (NOACs) were more likely to develop an HE compared with those on vitamin K antagonists (VKAs, p = 0.05) after traumatic brain injury (TBI) but not after spontaneous ICH.

CONCLUSION

 Our data reveal a significant heterogeneity within the traumatic series. Whereas younger patients show an excellent outcome, the elderly population of the traumatic cases demonstrates a poor outcome similar to that of the nontraumatic cohort. HE under NOACs rather than under VKAs is more likely in the elderly after TBI. Larger prospective trials are warranted to elucidate the potential individual underlying molecular mechanisms for the development of an ICH and HE in these diseases.

Epidemiological characteristics of 561 cases of intracerebral hemorrhage in Chengdu, China

ABSTRACT

To explore the epidemiology of patients with spontaneous intracerebral hemorrhage (sICH) in Chengdu, China, we retrieved the data of patients with spontaneous cerebral hemorrhage admitted to the First Affiliated Hospital of Chengdu Medical College from January 2017 to December 2019. We performed a comprehensive analysis of the location of hemorrhage, demographics, factors of hemorrhage, condition of body, severity of disturbance of consciousness, treatment, length of stay (days), inpatient costs, prognosis, and mortality rate in patients with sICH. In total, data of 561 in patients with sICH were included. The hemorrhage site was primarily located in the basal ganglia and thalamus (64.71%). The mean patient age was 63.2 ± 12.4 years (64.17% men, 35.83% women). Male patients (mean age 62.3 ± 12.5 year) were younger than female patients (mean age 64.9 ± 12.1 year). The age of sICH onset in our sample was between 40 and 79 years; this occurred in 87.70% of the included cases. There were more males than females, which may be related to more daily smoking, longer drinking years, and overweight in males than in females. Cases occurred most frequently during the winter and spring months, and the relationship between sICH visits and hospitalizations appeared as a U-shape. The median time from illness onset to hospital admission was 3.0 hours. According to the Glasgow Coma Scale (GCS) score at admission, 20.50% of sICH cases were of mild intensity, 39.93% were moderate, and 39.57% were severe. Moderate disorder is the most common sICH severity. Factors influencing the disturbance of consciousness were blood glucose level at the time of admission as well as the number of years with hypertension. The lower the degree of disturbance of consciousness and the more they smoked per day indicated they had a higher likelihood of receiving surgical treatment while in hospital. The median hospital stay was 13.0 days, while the median inpatient cost was USD 3609. The 30-day mortality rate was 18.36%. sICH is an important public health problem in Chengdu, China. A governmental initiative is urgently needed to establish a sICH monitoring system that covers the Chengdu region to develop more effective and targeted measures for sICH prevention, treatment, and rehabilitation.

Exploration of Medical Trajectories of Stroke Patients Based on Group-Based Trajectory Modeling

A high mortality rate is an issue with acute cerebrovascular disease (ACVD), as it often leads to a high medical expenditure, and in particular to high costs of treatment for emergency medical conditions and critical care. In this study, we used group-based trajectory modeling (GBTM) to study the characteristics of various groups of patients hospitalized with ACVD. In this research, the patient data were derived from the 1 million sampled cases in the National Health Insurance Research Database (NHIRD) in Taiwan. Cases who had been admitted to hospitals fewer than four times or more than eight times were excluded. Characteristics of the ACVD patients were collected, including age, mortality rate, medical expenditure, and length of hospital stay for each admission. We then performed GBTM to examine hospitalization patterns in patients who had been hospitalized more than four times and fewer than or equal to eight times. The patients were divided into three groups according to medical expenditure: high, medium, and low groups, split at the 33rd and 66th percentiles. After exclusion of unqualified patients, a total of 27,264 cases (male/female = 15,972/11,392) were included. Analysis of the characteristics of the ACVD patients showed that there were significant differences between the two gender groups in terms of age, mortality rate, medical expenditure, and total length of hospital stay. In addition, the data were compared between two admissions, which included interval, outpatient department (OPD) visit after discharge, OPD visit after hospital discharge, and OPD cost. Finally, the differences in medical expenditure between genders and between patients with different types of stroke-ischemic stroke, spontaneous intracerebral hemorrhage (sICH), and subarachnoid hemorrhage (SAH)-were examined using GBTM. Overall, this study employed GBTM to examine the trends in medical expenditure for different groups of stroke patients at different admissions, and some important results were obtained. Our results demonstrated that the time interval between subsequent hospitalizations decreased in the ACVD patients, and there were significant differences between genders and between patients with different types of stroke. It is often difficult to decide when the time has been reached at which further treatment will not improve the condition of ACVD patients, and the findings of our study may be used as a reference for assessing outcomes and quality of care for stroke patients. Because of the characteristics of NHIRD, this study had some limitations; for example, the number of cases for some diseases was not sufficient for effective statistical analysis.