Background/Aims: Cardiorespiratory fitness (CRF), as measured by maximal oxygen consumption (VO2max), is an important independent predictive factor of cardiovascular outcomes in patients with heart failure (HF). However, it is unclear whether conventional equations for estimating CRF are applicable to patients with HF with preserved ejection fraction (HFpEF). Methods: This study included 521 patients with HFpEF (EF ≥ 50%) whose CRF was directly measured by cardiopulmonary exercise test using a treadmill. We developed a new equation (Kor-HFpEF) for half of the patients in the HFpEF cohort (group A, n = 253) and validated it for the remaining half (group B, n = 268). The accuracy of the Kor-HFpEF equation was compared to that of the other equations in the validation group. Results: In the total HFpEF cohort, the directly measured VO2max was significantly overestimated by the FRIEND and ACSM equations (p < 0.001) and underestimated by the FRIEND-HF equation (p <0.001) (direct 21.2 ± 5.9 mL/kg/min; FRIEND 29.1 ± 11.8 mL/kg/min; ACSM 32.5 ± 13.4 mL/kg/min; FRIEND-HF 14.1 ± 4.9 mL/kg/min). However, the VO2max estimated by the Kor-HFpEF equation (21.3 ± 4.6 mL/kg/min) was similar to the directly measured VO2max (21.7 ± 5.9 mL/kg/min, p = 0.124), whereas the VO2max estimated by the other three equations was still significantly different from the directly measured VO2max in group B (all p < 0.001). Conclusions Traditional equations used to estimate VO2max were not applicable to patients with HFpEF. We developed and validated a new Kor-HFpEF equation for these patients, which had a high accuracy.

A post-burn scar contracture (PBSC) can cause functional problems including limited range of motion (ROM) and, in turn, poor quality of life. We present a case with an extensive PBSC combined with chronic ulceration. Treatment involved scar tissue excision, rehabilitation, and delayed reconstruction using a free transverse rectus abdominis myocutaneous flap and a split-thickness skin graft. After scar tissue excision, negative pressure was applied to the open wound; this facilitated rapid ambulation and ROM recovery within 2 weeks. Ultimately, over 6 months, the initial flexion contracture of 60º improved to 10º, and the ROM improved from 75º to 125º.

Background and Objectives: The outcome benefits of β-blockers in chronic coronary artery disease (CAD) have not been fully assessed. We evaluated the prognostic impact of β-blockers on patients with chronic CAD after percutaneous coronary intervention (PCI). Methods: A total of 3,075 patients with chronic CAD were included from the Grand DrugEluting Stent registry. We analyzed β-blocker prescriptions, including doses and types, in each patient at 3-month intervals from discharge. After propensity score matching, 1,170 pairs of patients (β-blockers vs. no β-blockers) were derived. Primary outcome was defined as a composite endpoint of all-cause death and myocardial infarction (MI). We further analyzed the outcome benefits of different doses (low-, medium-, and high-dose) and types (conventional or vasodilating) of β-blockers. Results: During a median (interquartile range) follow-up of 3.1 (3.0–3.1) years, 134 (5.7%) patients experienced primary outcome. Overall, β-blockers demonstrated no significant benefit in primary outcome (hazard ratio [HR], 0.88; 95% confidence interval [CI], 0.63–1.24), all-cause death (HR, 0.87; 95% CI, 0.60–1.25), and MI (HR, 1.25; 95% CI, 0.49–3.15). In subgroup analysis, β-blockers were associated with a lower risk of all-cause death in patients with previous MI and/ or revascularization (HR, 0.38; 95% CI, 0.14–0.99) (p for interaction=0.045). No significant associations were found for the clinical outcomes with different doses and types of β-blockers. Conclusions Overall, β-blocker therapy was not associated with better clinical outcomes in patients with chronic CAD undergoing PCI. Limited mortality benefit of β-blockers may exist for patients with previous MI and/or revascularization.

Objectives: This study examined the characteristics of patients according to nutritional status assessed by five nutritional screening tools: Patient-Generated Subjective Global Assessment (PG-SGA), NUTRISCORE, Nutritional Risk Index (NRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) and to compare the agreement, sensitivity, and specificity of these tools. Methods: A total of 952 gastric cancer patients who underwent gastrectomy and chemotherapy from January 2009 to December 2012 were included. The patients were categorized into malnutrition and normal status according to five nutritional screening tools one month after surgery. The Spearman partial correlation, Cohen’s Kappa coefficient, the area under the curve (AUC), sensitivity, and specificity of each two screening tools were calculated. Results: Malnutrition was observed in 86.24% of patients based on the PG-SGA and 85.82% based on the NUTRISCORE. When NRI or CONUT were applied, the proportions of malnutrition were < 30%. Patients with malnutrition had lower intakes of energy and protein than normal patients when assessed using the PG-SGA, NUTRISCORE, or NRI. Lower levels of albumin, hemoglobin, total lymphocyte count, and total cholesterol and longer postoperative hospital stays were observed among patients with malnutrition compared to normal patients when NRI, PNI, or CONUT were applied. Relatively high agreement for NUTRISCORE relative to PG-SGA was found; the sensitivity was 90.86%, and the AUC was 0.78. When NRI, PNI, and CONUT were compared, the sensitivities were 23.72% for PNI relative to NRI, 44.53% for CONUT relative to NRI, and 90.91% for CONUT relative to PNI. The AUCs were 0.95 for NRI relative to PNI and 0.91 for CONUT relative to PNI. Conclusions NUTRISCORE had a high sensitivity compared to PG-SGA, and CONUT had a high sensitivity compared to PNI. NRI had a high specificity compared to PNI. This relatively high sensitivity and specificity resulted in 77.00% agreement between PNI and CONUT and 77.94% agreement between NRI and PNI. Further cohort studies will be needed to determine if the nutritional status assessed by PG-SGA, NUTRISCORE, NRI, PNI, and CONUT predicts the gastric cancer prognosis.

Background: There has been no comparison of the determinants of admission route between acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We examined whether factors associated with direct versus transferred-in admission to regional cardiocerebrovascular centers (RCVCs) differed between AIS and AMI. Methods: Using a nationwide RCVC registry, we identified consecutive patients presenting with AMI and AIS between July 2016 and December 2018. We explored factors associated with direct admission to RCVCs in patients with AIS and AMI and examined whether those associations differed between AIS and AMI, including interaction terms between each factor and disease type in multivariable models. To explore the influence of emergency medical service (EMS) paramedics on hospital selection, stratified analyses according to use of EMS were also performed. Results: Among the 17,897 and 8,927 AIS and AMI patients, 66.6% and 48.2% were directly admitted to RCVCs, respectively. Multivariable analysis showed that previous coronary heart disease, prehospital awareness, higher education level, and EMS use increased the odds of direct admission to RCVCs, but the odds ratio (OR) was different between AIS and AMI (for the first 3 factors, AMI > AIS; for EMS use, AMI < AIS). EMS use was the single most important factor for both AIS and AMI (OR, 4.72 vs. 3.90). Hypertension and hyperlipidemia increased, while living alone decreased the odds of direct admission only in AMI;additionally, age (65–74 years), previous stroke, and presentation during non-working hours increased the odds only in AIS. EMS use weakened the associations between direct admission and most factors in both AIS and AMI. Conclusions Various patient factors were differentially associated with direct admission to RCVCs between AIS and AMI. Public education for symptom awareness and use of EMS is essential in optimizing the transportation and hospitalization of patients with AMI and AIS.

Incidental adnexal masses considered indeterminate for malignancy are commonly observed on ultrasonography. Multiparametric MRI is the imaging modality of choice for the evaluation of sonographically indeterminate adnexal masses. Conventional MRI enables a confident pathologic diagnosis of various benign lesions due to accurate tissue characterization of fat, blood, fibrous tissue, and solid components. Additionally, functional imaging sequences, including perfusion- and diffusion-weighted imaging, improve the diagnostic efficacy of conventional MRI in differentiating benign from malignant adnexal masses. The ovarian-adnexal reporting and data system (O-RADS) MRI was recently designed to provide consistent interpretations in assigning risk of malignancy to ovarian and other adnexal masses, and to provide a management recommendation for each risk category. In this review, we describe the clinical application of multiparametric MRI for the evaluation of adnexal masses and introduce the O-RADS MRI risk stratification system.

Objectives: This study aimed to examine the characteristics of patients according to their nutritional status as assessed by five nutritional screening tools: Patient-Generated Subjective Global Assessment (PG-SGA), NUTRISCORE, Nutritional Risk Index (NRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) and to compare the agreement, sensitivity, and specificity of these tools. Methods: A total of 952 gastric cancer patients who underwent gastrectomy and chemotherapy from January 2009 to December 2012 at the Samsung Medical Center were included. We categorized patients into malnourished and normal according to the five nutritional screening tools 1 month after surgery and compared their characteristics. We also calculated the Spearman partial correlation, Cohen’s Kappa coefficient, the area under the curve (AUC), sensitivity, and specificity of each pair of screening tools. Results: We observed 86.24% malnutrition based on the PG-SGA and 85.82% based on the NUTRISCORE among gastric cancer patients in our study. When we applied NRI or CONUT, however, the malnutrition levels were less than 30%. Patients with malnutrition as assessed by the PG-SGA, NUTRISCORE, or NRI had lower intakes of energy and protein compared to normal patients. When NRI, PNI, or CONUT were used to identify malnutrition, lower levels of albumin, hemoglobin, total lymphocyte count, total cholesterol, and longer postoperative hospital stays were observed among patients with malnutrition compared to those without malnutrition. We found relatively high agreement between PG-SGA and NUTRISCORE; sensitivity was 90.86% and AUC was 0.78. When we compared NRI and PNI, sensitivity was 99.64% and AUC was 0.97. AUC ranged from 0.50 to 0.67 for comparisons between CONUT and each of the other nutritional screening tools. Conclusions Our study suggests that PG-SGA and NRI have a relatively high agreement with the NUTRISCORE and PNI, respectively. Further cohort studies are needed to examine whether the nutritional status assessed by PG-SGA, NUTRISCORE, NRI, PNI, and CONUT predicts the gastric cancer prognosis.

At the end of 2019, the cause of pneumonia outbreaks in Wuhan, China, was identified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In February 2020, the World Health Organization named the disease cause by SARS-CoV-2 as coronavirus disease 2019 (COVID-19). In response to the pandemic, the Korean Cancer Association formed the COVID-19 task force to develop practice guidelines. This special article introduces the clinical practice guidelines for cancer patients which will help oncologists best manage cancer patients during the COVID-19 pandemic.

Objectives: This study aimed to examine the characteristics of patients according to their nutritional status as assessed by five nutritional screening tools: Patient-Generated Subjective Global Assessment (PG-SGA), NUTRISCORE, Nutritional Risk Index (NRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) and to compare the agreement, sensitivity, and specificity of these tools. Methods: A total of 952 gastric cancer patients who underwent gastrectomy and chemotherapy from January 2009 to December 2012 at the Samsung Medical Center were included. We categorized patients into malnourished and normal according to the five nutritional screening tools 1 month after surgery and compared their characteristics. We also calculated the Spearman partial correlation, Cohen’s Kappa coefficient, the area under the curve (AUC), sensitivity, and specificity of each pair of screening tools. Results: We observed 86.24% malnutrition based on the PG-SGA and 85.82% based on the NUTRISCORE among gastric cancer patients in our study. When we applied NRI or CONUT, however, the malnutrition levels were less than 30%. Patients with malnutrition as assessed by the PG-SGA, NUTRISCORE, or NRI had lower intakes of energy and protein compared to normal patients. When NRI, PNI, or CONUT were used to identify malnutrition, lower levels of albumin, hemoglobin, total lymphocyte count, total cholesterol, and longer postoperative hospital stays were observed among patients with malnutrition compared to those without malnutrition. We found relatively high agreement between PG-SGA and NUTRISCORE; sensitivity was 90.86% and AUC was 0.78. When we compared NRI and PNI, sensitivity was 99.64% and AUC was 0.97. AUC ranged from 0.50 to 0.67 for comparisons between CONUT and each of the other nutritional screening tools. Conclusions Our study suggests that PG-SGA and NRI have a relatively high agreement with the NUTRISCORE and PNI, respectively. Further cohort studies are needed to examine whether the nutritional status assessed by PG-SGA, NUTRISCORE, NRI, PNI, and CONUT predicts the gastric cancer prognosis.

no abstract available.