This study was performed to determine if women with day 3 serum inhibin-B concentrations <45pg/ml (conversion factor to SI unit, 1.00) demonstrate a pro. response to ovulation induction and assisted reproductive technology outcome to women with inhibin-B > or = 45pg/ml, independant of day 3 FSH, E2 and patient age. From Jan 1996 to Dec 1996, 16 volunteers patients who underwent 25 IVF cycles with luteal phase GnRH agonist suppression and HMG stimulation were allocated to the study group. We evaluated day 3 serum inhibits-B, FSH, E2, peak E2, cancellation rate per initiated cycle (%) and clinical pregnancy rate per initiated cycle (%) according to the above two groups and independent of patient age, day 3 FSH, day 3 E2 and all of above combined. Women with day 3 serum inhibin-B > or =45pg/m1 demonstrated higher average day 3 inhibits-B level, clinical pregnancy rate per initiated cycle (20.3+/-2.5 pg/ml vs 80.9+/- 5.0pg/ml, p<0.05; 24.8% vs 8.5%, p<0.05) and lower day 3 FSH level, cancellation rate per initiated cycle (6.9+/-0.3 mIU/ml vs 8.5+/-0.5 mIU/ml, p<0.05; 1.5% vs 9.0%, p<0.05). Women with day 3 serum inhibin> or =45pg/ml and age<40 year demonstrated higher pregnancy rate per initiated cycle (28.2% vs 7.4%, p<0.05) and lows. day 3 FSH level, cancellation rate per initiated cycle (6.9+/-0.5 mIU/ml vs 8.2+/-0.7 mIU/ml, p<0.05; 1.0% vs 9.0%, p<0.05). Women with day 3 serum inhibin> or =45pg/ml and day 3 FSH<15mIU/inl demonstrated higher pregnancy rate per initiated cycle (33.5% vs 9.5%, p<0.05) and lower day 3 FSH level, cancellation rate per initiated cycle (7.7+/- 0.2 mIU/ml vs 8.5+/-0.5 mIU/ml, p<0.05; 1.5% vs 10.0%, p<0.05). Women with day 3 serum inhibin> or =45pg/ml and day 3 E2<50pq/ml demonstrated higher pregnancy rate per initiated cycle (30.0% vs 9.5%, p<0.05) and lower cancellation rate per initiated cycle (1.5% vs 9.5%, p<0.05). Women with day 3 serum inhibin> or =45pg/ml, age<40 year, day 3 FSH<15mIU/ml and day 3 E2<50pg/m1 demonstrated higher pregnancy rate per initiated cycle (30.0% vs 10.8%, p<0.05) and lower day 3 FSH level, cancellation rate per initiated cycle (6.8+/-0.6 mIU/ml vs 8.4+/-0.9 mIU/ml, p<0.05; 1.5% vs 7.8%, p<0.05). Therefore women with low day 3 serum inhibits-B concentrations demonstrate a poorer response to ovulation induction and are less likely to conceive a clinical pregnancy though ART relative to women with high day 3 inhibits-B and day 3 serum inhibin-B, in addition to a day 3 FSH, E2 and patient age, appears helpful in prediction in IVF-ET outcome.
Female ; Gonadotropin-Releasing Hormone ; Humans ; International System of Units ; Luteal Phase ; Ovulation Induction ; Pregnancy ; Pregnancy Rate ; Reproductive Techniques, Assisted* ; Volunteers

BACKGROUND AND OBJECTIVES: This study aimed to confirm the effects of traditional holidays on the incidence and outcomes of out-of-hospital cardiac arrest (OHCA) in South Korea. METHODS: We studied 95,066 OHCAs of cardiac cause from a nationwide, prospective study from the Korea OHCA Registry from January 2012 to December 2016. We compared the incidence of OHCA, in-hospital mortality, and neurologic outcomes between traditional holidays, Seollal (Lunar New Year's Day) and Chuseok (Korean Thanksgiving Day), and other day types (weekday, weekend, and public holiday). RESULTS: OHCA occurred more frequently on traditional holidays than on the other days. The median OHCA incidence were 51.0 (interquartile range [IQR], 44.0–58.0), 53.0 (IQR, 46.0–60.5), 52.5 (IQR, 45.3–59.8), and 60.0 (IQR, 52.0–69.0) cases/day on weekday, weekend, public holiday, and traditional holiday, respectively (p<0.001). The OHCA occurred more often at home rather than in public place, lesser bystander cardiopulmonary resuscitation (CPR) was performed, and the rate of cessation of CPR within 20 minutes without recovery of spontaneous circulation was higher on traditional holiday. After multivariable adjustment, traditional holiday was associated with higher in-hospital mortality (adjusted hazard ratio [HR], 1.339; 95% confidence interval [CI], 1.058–1.704; p=0.016) but better neurologic outcomes (adjusted HR, 0.503; 95% CI, 0.281–0.894; p=0.020) than weekdays. CONCLUSIONS: The incidence of OHCAs was associated with day types in a year. It occurred more frequently on traditional holidays than on other day types. It was associated with higher in-hospital mortality and favorable neurologic outcomes than weekday.
Cardiopulmonary Resuscitation ; Epidemiology ; Heart Arrest ; Holidays ; Hospital Mortality ; Incidence ; Korea ; Mortality ; Out-of-Hospital Cardiac Arrest ; Prospective Studies

BACKGROUND AND OBJECTIVES: Screening and early diagnosis for heart failure (HF) are critical. However, conventional screening diagnostic methods have limitations, and electrocardiography (ECG)-based HF identification may be helpful. This study aimed to develop and validate a deep-learning algorithm for ECG-based HF identification (DEHF). METHODS: The study involved 2 hospitals and 55,163 ECGs of 22,765 patients who performed echocardiography within 4 weeks were study subjects. ECGs were divided into derivation and validation data. Demographic and ECG features were used as predictive variables. The primary endpoint was detection of HF with reduced ejection fraction (HFrEF; ejection fraction [EF]≤40%), and the secondary endpoint was HF with mid-range to reduced EF (≤50%). We developed the DEHF using derivation data and the algorithm representing the risk of HF between 0 and 1. We confirmed accuracy and compared logistic regression (LR) and random forest (RF) analyses using validation data. RESULTS: The area under the receiver operating characteristic curves (AUROCs) of DEHF for identification of HFrEF were 0.843 (95% confidence interval, 0.840–0.845) and 0.889 (0.887–0.891) for internal and external validation, respectively, and these results significantly outperformed those of LR (0.800 [0.797–0.803], 0.847 [0.844–0.850]) and RF (0.807 [0.804–0.810], 0.853 [0.850–0.855]) analyses. The AUROCs of deep learning for identification of the secondary endpoint was 0.821 (0.819–0.823) and 0.850 (0.848–0.852) for internal and external validation, respectively, and these results significantly outperformed those of LR and RF. CONCLUSIONS: The deep-learning algorithm accurately identified HF using ECG features and outperformed other machine-learning methods.
Artificial Intelligence ; Early Diagnosis ; Echocardiography ; Electrocardiography ; Forests ; Heart Failure ; Heart ; Humans ; Learning ; Logistic Models ; Machine Learning ; Mass Screening ; ROC Curve

BACKGROUND AND OBJECTIVES: Screening and early diagnosis for heart failure (HF) are critical. However, conventional screening diagnostic methods have limitations, and electrocardiography (ECG)-based HF identification may be helpful. This study aimed to develop and validate a deep-learning algorithm for ECG-based HF identification (DEHF). METHODS: The study involved 2 hospitals and 55,163 ECGs of 22,765 patients who performed echocardiography within 4 weeks were study subjects. ECGs were divided into derivation and validation data. Demographic and ECG features were used as predictive variables. The primary endpoint was detection of HF with reduced ejection fraction (HFrEF; ejection fraction [EF]≤40%), and the secondary endpoint was HF with mid-range to reduced EF (≤50%). We developed the DEHF using derivation data and the algorithm representing the risk of HF between 0 and 1. We confirmed accuracy and compared logistic regression (LR) and random forest (RF) analyses using validation data. RESULTS: The area under the receiver operating characteristic curves (AUROCs) of DEHF for identification of HFrEF were 0.843 (95% confidence interval, 0.840–0.845) and 0.889 (0.887–0.891) for internal and external validation, respectively, and these results significantly outperformed those of LR (0.800 [0.797–0.803], 0.847 [0.844–0.850]) and RF (0.807 [0.804–0.810], 0.853 [0.850–0.855]) analyses. The AUROCs of deep learning for identification of the secondary endpoint was 0.821 (0.819–0.823) and 0.850 (0.848–0.852) for internal and external validation, respectively, and these results significantly outperformed those of LR and RF. CONCLUSIONS The deep-learning algorithm accurately identified HF using ECG features and outperformed other machine-learning methods.

BACKGROUND AND OBJECTIVES: This study aimed to confirm the effects of traditional holidays on the incidence and outcomes of out-of-hospital cardiac arrest (OHCA) in South Korea. METHODS: We studied 95,066 OHCAs of cardiac cause from a nationwide, prospective study from the Korea OHCA Registry from January 2012 to December 2016. We compared the incidence of OHCA, in-hospital mortality, and neurologic outcomes between traditional holidays, Seollal (Lunar New Year's Day) and Chuseok (Korean Thanksgiving Day), and other day types (weekday, weekend, and public holiday). RESULTS: OHCA occurred more frequently on traditional holidays than on the other days. The median OHCA incidence were 51.0 (interquartile range [IQR], 44.0–58.0), 53.0 (IQR, 46.0–60.5), 52.5 (IQR, 45.3–59.8), and 60.0 (IQR, 52.0–69.0) cases/day on weekday, weekend, public holiday, and traditional holiday, respectively (p<0.001). The OHCA occurred more often at home rather than in public place, lesser bystander cardiopulmonary resuscitation (CPR) was performed, and the rate of cessation of CPR within 20 minutes without recovery of spontaneous circulation was higher on traditional holiday. After multivariable adjustment, traditional holiday was associated with higher in-hospital mortality (adjusted hazard ratio [HR], 1.339; 95% confidence interval [CI], 1.058–1.704; p=0.016) but better neurologic outcomes (adjusted HR, 0.503; 95% CI, 0.281–0.894; p=0.020) than weekdays. CONCLUSIONS The incidence of OHCAs was associated with day types in a year. It occurred more frequently on traditional holidays than on other day types. It was associated with higher in-hospital mortality and favorable neurologic outcomes than weekday.

Background and Objectives: This study aimed to investigate the association between cardiovascular events and 2 different levels of elevated on-treatment diastolic blood pressures (DBP) in the presence of achieved systolic blood pressure targets (SBP). Methods: A nation-wide population-based cohort study comprised 237,592 patients with hypertension treated. The primary endpoint was a composite of cardiovascular death, myocardial infarction, and stroke. Elevated DBP was defined according to the Seventh Report of Joint National Committee (JNC7; SBP <140 mmHg, DBP ≥90 mmHg) or to the 2017 American College of Cardiology/American Heart Association (ACC/AHA) definitions (SBP <130 mmHg, DBP ≥80 mmHg). Results: During a median follow-up of 9 years, elevated on-treatment DBP by the JNC7 definition was associated with an increased risk of the occurrence of primary endpoint compared with achieved both SBP and DBP (adjusted hazard ratio [aHR], 1.14; 95% confidence interval [CI], 1.05–1.24) but not in those by the 2017 ACC/AHA definition. Elevated ontreatment DBP by the JNC7 definition was associated with a higher risk of cardiovascular mortality (aHR, 1.42; 95% CI, 1.18–1.70) and stroke (aHR, 1.19; 95% CI, 1.08–1.30). Elevated on-treatment DBP by the 2017 ACC/AHA definition was only associated with stroke (aHR, 1.10;95% CI, 1.04–1.16). Similar results were seen in the propensity-score-matched cohort. Conclusion Elevated on-treatment DBP by the JNC7 definition was associated a high risk of major cardiovascular events, while elevated DBP by the 2017 ACC/AHA definition was only associated with a higher risk of stroke. The result of study can provide evidence of DBP targets in subjects who achieved SBP targets.