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رحلة إلى الكواكب والنجوم : النظام الشمسي
يتناول كتاب (رحلة إلى الكواكب والنجوم) والذي قام بتأليفه (هاي يونغ لي) في حوالي (36) صفحة من القطع الكبير، النظام الشمسي يشبه عائلة كبيرة تضم العديد من الكواكب والكويكبات والمذنبات ومن المهم جدا نفهم النظام الشمسي كي نستطيع أن نفهم الكون... لهذا سيأخذنا هذا الكتاب في رحلة إلى النجوم في السماء لنتعلم أحجام الكواكب والمسافات في ما بينها في النظام الشمسي.
Book
Artificial intelligence algorithm for predicting mortality of patients with acute heart failure
This study aimed to develop and validate deep-learning-based artificial intelligence algorithm for predicting mortality of AHF (DAHF).
12,654 dataset from 2165 patients with AHF in two hospitals were used as train data for DAHF development, and 4759 dataset from 4759 patients with AHF in 10 hospitals enrolled to the Korean AHF registry were used as performance test data. The endpoints were in-hospital, 12-month, and 36-month mortality. We compared the DAHF performance with the Get with the Guidelines-Heart Failure (GWTG-HF) score, Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score, and other machine-learning models by using the test data. Area under the receiver operating characteristic curve of the DAHF were 0.880 (95% confidence interval, 0.876-0.884) for predicting in-hospital mortality; these results significantly outperformed those of the GWTG-HF (0.728 [0.720-0.737]) and other machine-learning models. For predicting 12- and 36-month endpoints, DAHF (0.782 and 0.813) significantly outperformed MAGGIC score (0.718 and 0.729). During the 36-month follow-up, the high-risk group, defined by the DAHF, had a significantly higher mortality rate than the low-risk group(p<0.001).
DAHF predicted the in-hospital and long-term mortality of patients with AHF more accurately than the existing risk scores and other machine-learning models.
Journal Article
Sex differences in the applicability of Western cardiovascular disease risk prediction equations in the Asian population
Cardiovascular diseases (CVDs) are the most common cause of death, but they can be effectively managed through appropriate prevention and treatment. An important aspect in preventing CVDs is assessing each individual's comprehensive risk profile, for which various risk engines have been developed. The important keys to CVD risk engines are high reliability and accuracy, which show differences in predictability depending on disease status or race. Framingham risk score (FRS) and the atherosclerotic cardiovascular disease risk equations (ASCVD) were applied to the Korean population to assess their suitability.
A retrospective cohort study was conducted using National Health Insurance Corporation sample cohort from 2003 to 2015. The enrolled participants over 30 years of age and without CVD followed-up for 10 years. We compared the prediction performance of FRS and ASCVD and calculated the relative importance of each covariate.
The AUCs of FRS (men: 0.750; women: 0.748) were higher than those of ASCVD (men: 0.718; women: 0.727) for both sexes (Delong test P <0.01). Goodness of fits (GOF) were poor for all models (Chi-square P < 0.001), especially, underestimation of the risk was pronounced in women. When the men's coefficients were applied to women's data, AUC (0.748; Delong test P<0.01) and the GOF (chi-square P = 0.746) were notably improved in FRS. Hypertension was found to be the most influential variable for CVD, and this is one of the reasons why FRS, having the highest relative weight to blood pressure, showed better performance.
When applying existing tools to Korean women, there was a noticeable underestimation. To accurately predict the risk of CVD, it was more appropriate to use FRS with men's coefficient in women. Moreover, hypertension was found to be a main risk factor for CVD.
Journal Article
Validation of a wearable cuff-less wristwatch-type blood pressure monitoring device
Ambulatory blood pressure (BP) monitoring is recommended to improve the management of hypertension. Here, we investigated the accuracy of BP estimated using a wearable cuff-less device, InBodyWATCH, compared with BP measured using a manual sphygmomanometer. Thirty-five adults were enrolled (age 57.1 ± 17.9 years). The BP was estimated using InBodyWATCH with an individualized estimation based on a neural network model. Three paired sets of BPs from the two devices were compared using correlation analysis and Bland–Altman plots (
n
= 105 paired BP readings). The correlations for both systolic and diastolic BP (SBP and DBP) between the two devices were high (
r
= 0.964 and 0.939, both
P
< 0.001). The mean difference was 2.2 ± 6.1 mmHg for SBP and −0.2 ± 4.2 mmHg for DBP; these were not significant (
P
= 0.472 for SBP and
P
= 0.880 for DBP). The proportions of estimated SBP/DBP obtained from the InBodyWATCH within ± 5 mmHg of manual SBP/DBP were 71.4%/83.8%; within ± 10 mmHg they were 86.7%/98.1%; and within ± 15 mmHg they were 97.1%/99.0%. The estimated BP from this wearable cuff-less device correlated highly with the manual BP and showed good accuracy, suggesting its potential to be used in ambulatory BP monitoring.
Journal Article
The 2022 focused update of the 2018 Korean Hypertension Society Guidelines for the management of hypertension
Hypertension is the leading cause of death in human being, which shows high prevalence and associated complications that increase the mortality and morbidity. Controlling blood pressure (BP) is very important because it is well known that lowering high BP effectively improves patients’ prognosis. This review aims to provide a focused update of the 2018 Korean Hypertension Society Guidelines for the management of hypertension. The importance of ambulatory BP and home BP monitoring was further emphasized not only for the diagnosis but also for treatment target. By adopting corresponding BPs, the updated guideline recommended out-of-office BP targets for both standard and intensive treatment. Based on the consensus on corresponding BPs and Systolic Blood Pressure Intervention Trial (SPRINT) revisit, the updated guidelines recommended target BP in high-risk patients below 130/80 mmHg and it applies to hypertensive patients with three or more additional cardiovascular risk factors, one or more risk factors with diabetes, or hypertensive patients with subclinical organ damages, coronary or vascular diseases, heart failure, chronic kidney disease with proteinuria, and cerebral lacunar infarction. Cerebral infarction and chronic kidney disease are also high-risk factors for cardiovascular disease. However, due to lack of evidence, the target BP was generally determined at < 140/90 mmHg in patients with those conditions as well as in the elderly. Updated contents regarding the management of hypertension in special situations are also discussed.
Journal Article
Cost-effectiveness analysis of intensive blood pressure control in Korea
This study was a cost-effectiveness analysis of intensive blood pressure (BP) control among hypertensive patients in Korea. We constructed a Markov model comparing intensive versus standard BP control treatment and calculated the incremental cost-effectiveness ratio. The study population consisted of hypertensive patients over 50 years old with systolic blood pressures (SBPs) exceeding 140 mmHg and at high risk of cardiovascular disease. Treatment alternatives included lowering the SBP below 120 mmHg (intensive) and 140 mmHg (standard) for target BP. We assumed five scenarios with different medication adherence. The effectiveness variable was quality-adjusted life years (QALYs), and costs included medical costs related to hypertension (HT), complications, and nonmedical costs. In addition, we performed a sensitivity analysis to confirm the robustness of the results of this study. Scenario 5, with 100% medication adherence, showed the lowest incremental cost-effectiveness ratio (ICER) of $1,373 USD, followed by scenario 1 (first 15 years: 62.5%, 16-30 years: 65.2%, after 30 years: 59.5%), scenario 2 (first five years: 62.5% decrease by 5% every five years), and scenario 3 (first 10 years: 62.5% decrease by 10% every 10 years). The ICERs in all scenarios were lower than the willingness to pay (WTP) threshold of $9,492-$32,907 USD in Korea. Tornado analysis showed that the ICERs were changed greatly according to stroke incidence. Intensive treatment of HT prevents cardiovascular disease (CVD); therefore, intensive treatment is more cost-effective than standard treatment despite the consumption of more health resources. ICERs are considerably changed according to medication adherence, confirming the importance of patient adherence to treatment.
Journal Article
Age-differential association between serum uric acid and incident hypertension
Increasing evidence suggests a positive association between the serum uric acid (SUA) level and incident hypertension. However, the association has been inconsistent based on age, sex, body mass index, and lipid profiles. Thus, we investigated whether there is an interaction between SUA and other risk factors on incident hypertension in the Korean general population. In this study, 808 participants aged 40-79 years were included. They were free of hypertension and major cardiovascular disease at baseline. Incident hypertension was defined as systolic blood pressure (SBP) ≥ 140 mmHg, diastolic blood pressure (DBP) ≥ 90 mmHg, or use of antihypertensive medication. To investigate whether the association between SUA and incident hypertension is modified by other risk factors for hypertension, a generalized linear model and Z test were used. During the mean follow-up of 3.3 years, 11.5% of men and 10.7% of women developed hypertension. The association between SUA and incident hypertension was inconsistent according to participant age (p for interaction = 0.009). The association between SUA level and incident hypertension was positively significant among people aged < 55 years (relative risk 1.74 per 1.0 mg/dL of SUA; p = 0.002), but there was no significant association among people aged ≥ 55 years (p = 0.894). In a secondary analysis, the SUA level was not associated with an increase in SBP, but positively associated with DBP. We observed an age-differential association between SUA level and incident hypertension among Koreans. An increased SUA level can be a trigger for hypertension through early vascular changes in the middle-aged population.
Journal Article
Deep learning of ECG waveforms for diagnosis of heart failure with a reduced left ventricular ejection fraction
The performance and clinical implications of the deep learning aided algorithm using electrocardiogram of heart failure (HF) with reduced ejection fraction (DeepECG-HFrEF) were evaluated in patients with acute HF. The DeepECG-HFrEF algorithm was trained to identify left ventricular systolic dysfunction (LVSD), defined by an ejection fraction (EF) < 40%. Symptomatic HF patients admitted at Seoul National University Hospital between 2011 and 2014 were included. The performance of DeepECG-HFrEF was determined using the area under the receiver operating characteristic curve (AUC) values. The 5-year mortality according to DeepECG-HFrEF results was analyzed using the Kaplan–Meier method. A total of 690 patients contributing 18,449 ECGs were included with final 1291 ECGs eligible for the study (mean age 67.8 ± 14.4 years; men, 56%). HFrEF (+) identified an EF < 40% and HFrEF (−) identified EF ≥ 40%. The AUC value was 0.844 for identifying HFrEF among patients with acute symptomatic HF. Those classified as HFrEF (+) showed lower survival rates than HFrEF (−) (log-rank
p
< 0.001). The DeepECG-HFrEF algorithm can discriminate HFrEF in a real-world HF cohort with acceptable performance. HFrEF (+) was associated with higher mortality rates. The DeepECG-HFrEF algorithm may help in identification of LVSD and of patients at risk of worse survival in resource-limited settings.
Journal Article
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
Older adults are at an increased risk of postoperative morbidity. Numerous risk stratification tools exist, but effort and manpower are required. 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. 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. 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. The derived model shall assist clinicians and patients in understanding the individualized risks and benefits of surgery.
Journal Article
Blood Pressure Control and Cardiovascular Outcomes: Real-world Implications of the 2017 ACC/AHA Hypertension Guideline
The 2017 American College of Cardiology/American Heart Association (ACC/AHA) hypertension guideline lowered the threshold defining hypertension and treatment target from 140/90 mmHg to 130/80 mmHg. We compared the 2017 ACC/AHA guideline and the Eighth Joint National Committee (JNC8) report with regard to the current status of hypertension using the Korean National Health and Nutrition Examination Survey. The association between blood pressure (BP) control and long-term major cardiovascular outcomes (MACEs) was analyzed using the Korea National Health Insurance Service cohort. In the cross-sectional study with 15,784 adults, the prevalence of hypertension was expected to be 49.2 ± 0.6% based on the definition suggested by the 2017 ACC/AHA guideline versus 30.4 ± 0.6% based on the JNC8 report. In a longitudinal analysis with 373,800 hypertensive adults for the median follow-up periods of 11.0 years, the adults meeting the target goal BP goal of 2017 ACC/AHA guideline were associated with 21% reduced risk of MACEs compared with adults, not meeting 2017 ACC/AHA BP goal but meeting JNC8 target goal. In conclusion, substantial increase of prevalence of hypertension is expected by the 2017 ACC/AHA guideline. This study also suggests endorsing the aggressive approach would lead to an improvement in cardiovascular care.
Journal Article