Purpose: This study aimed to understand the experiences of dialysis and their meaning among patients with chronic kidney disease through a meta-synthesis of the existing literature. Since 2010, the prevalence of end-stage renal disease has doubled in South Korea, which has the sixth-highest incidence worldwide. Although most kidney disease patients undergo dialysis to attenuate disease-related symptoms and prolong their lives, the implications of dialysis on their lives, together with the role played by patients’ significant others, remain underexplored. Similarly, existing research has not considered both patients with hemodialysis and peritoneal dialysis. Methods: In this meta-synthesis, seven electronic databases (PubMed, CINAHL, EMBASE, PsycINFO, DBpia, KISS, and RISS) were searched for the terms “dialysis” and “qualitative.” Thirty qualitative studies were selected for examination. Results: The overriding theme observed in the studies was “I do not have much time left.”–navigating the dual realities of one’s limited existence, while other key themes were: (1) the inevitable experience of the troubles of dialysis, (2) life is extended, but deteriorating in every aspect, (3) accepting dialysis with a positive outlook for life, and (4) essential support experienced in an exhausting life. Conclusion These findings are important for the design and delivery of practical and tailored nursing interventions to help patients overcome the various challenges related to dialysis treatment, and improve their quality of life.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Purpose: This study aimed to understand the experiences of dialysis and their meaning among patients with chronic kidney disease through a meta-synthesis of the existing literature. Since 2010, the prevalence of end-stage renal disease has doubled in South Korea, which has the sixth-highest incidence worldwide. Although most kidney disease patients undergo dialysis to attenuate disease-related symptoms and prolong their lives, the implications of dialysis on their lives, together with the role played by patients’ significant others, remain underexplored. Similarly, existing research has not considered both patients with hemodialysis and peritoneal dialysis. Methods: In this meta-synthesis, seven electronic databases (PubMed, CINAHL, EMBASE, PsycINFO, DBpia, KISS, and RISS) were searched for the terms “dialysis” and “qualitative.” Thirty qualitative studies were selected for examination. Results: The overriding theme observed in the studies was “I do not have much time left.”–navigating the dual realities of one’s limited existence, while other key themes were: (1) the inevitable experience of the troubles of dialysis, (2) life is extended, but deteriorating in every aspect, (3) accepting dialysis with a positive outlook for life, and (4) essential support experienced in an exhausting life. Conclusion These findings are important for the design and delivery of practical and tailored nursing interventions to help patients overcome the various challenges related to dialysis treatment, and improve their quality of life.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Purpose: This study aimed to understand the experiences of dialysis and their meaning among patients with chronic kidney disease through a meta-synthesis of the existing literature. Since 2010, the prevalence of end-stage renal disease has doubled in South Korea, which has the sixth-highest incidence worldwide. Although most kidney disease patients undergo dialysis to attenuate disease-related symptoms and prolong their lives, the implications of dialysis on their lives, together with the role played by patients’ significant others, remain underexplored. Similarly, existing research has not considered both patients with hemodialysis and peritoneal dialysis. Methods: In this meta-synthesis, seven electronic databases (PubMed, CINAHL, EMBASE, PsycINFO, DBpia, KISS, and RISS) were searched for the terms “dialysis” and “qualitative.” Thirty qualitative studies were selected for examination. Results: The overriding theme observed in the studies was “I do not have much time left.”–navigating the dual realities of one’s limited existence, while other key themes were: (1) the inevitable experience of the troubles of dialysis, (2) life is extended, but deteriorating in every aspect, (3) accepting dialysis with a positive outlook for life, and (4) essential support experienced in an exhausting life. Conclusion These findings are important for the design and delivery of practical and tailored nursing interventions to help patients overcome the various challenges related to dialysis treatment, and improve their quality of life.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Purpose: This study aimed to understand the experiences of dialysis and their meaning among patients with chronic kidney disease through a meta-synthesis of the existing literature. Since 2010, the prevalence of end-stage renal disease has doubled in South Korea, which has the sixth-highest incidence worldwide. Although most kidney disease patients undergo dialysis to attenuate disease-related symptoms and prolong their lives, the implications of dialysis on their lives, together with the role played by patients’ significant others, remain underexplored. Similarly, existing research has not considered both patients with hemodialysis and peritoneal dialysis. Methods: In this meta-synthesis, seven electronic databases (PubMed, CINAHL, EMBASE, PsycINFO, DBpia, KISS, and RISS) were searched for the terms “dialysis” and “qualitative.” Thirty qualitative studies were selected for examination. Results: The overriding theme observed in the studies was “I do not have much time left.”–navigating the dual realities of one’s limited existence, while other key themes were: (1) the inevitable experience of the troubles of dialysis, (2) life is extended, but deteriorating in every aspect, (3) accepting dialysis with a positive outlook for life, and (4) essential support experienced in an exhausting life. Conclusion These findings are important for the design and delivery of practical and tailored nursing interventions to help patients overcome the various challenges related to dialysis treatment, and improve their quality of life.

Background: Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease that needs further clinical investigation. Characterizing the temporal pattern of combined infections in patients with COVID-19 may help clinicians understand the clinical nature of this disease and provide valuable diagnostic and therapeutic guidelines. Methods: We retrospectively analyzed COVID-19 patients isolated in four study hospitals in Korea for one year period from May 2021 to April 2022 when the delta and omicron variants were dominant. The temporal characteristics of combined infections based on specific diagnostic tests were analyzed. Results: A total of 16,967 COVID-19 patients were screened, 2,432 (14.3%) of whom underwent diagnostic microbiologic tests according to the clinical decision-making, 195 of whom had positive test results, and 0.55% (94/16,967) of whom were ultimately considered to have clinically meaningful combined infections. The median duration for the diagnosis of combined infections was 15 (interquartile range [IQR], 5–25) days after admission. The proportion of community-acquired coinfections (≤ 2 days after admission) was 11.7% (11/94), which included bacteremia (10/94, 10.63%) and tuberculosis (1/94, 1.06%). Combined infections after 2 days of admission were diagnosed at median 16 (IQR, 9–26) days, and included bacteremia (72.3%), fungemia (19.3%), cytomegalovirus (CMV) diseases (8.4%), Pneumocystis jerovecii pneumonia (PJP, 8.4%) and invasive pulmonary aspergillosis (IPA, 4.8%). Conclusion Among COVID-19 patients with risk factors for severe complications, 0.55% had laboratory-confirmed combined infections, which included community and nosocomial pathogens in addition to unusual pathogens such as CMV disease, PJP and IPA.

Objective: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. Materials and Methods: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017–May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. Results: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS–HHUS agreement was 95.9% (236/246; Cohen’s kappa = 0.883). Conclusion Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

Purpose: Several predictive models have been developed to predict the pathological complete response (pCR) after neoadjuvant chemotherapy (NAC); however, few are broadly applicable owing to radiologic complexity and institution-specific clinical variables, and none have been externally validated. This study aimed to develop and externally validate a machine learning model that predicts pCR after NAC in patients with breast cancer using routinely collected clinical and demographic variables. Methods: The electronic medical records of patients with advanced breast cancer who underwent NAC before surgical resection between January 2017 and December 2020 were reviewed. Patient data from Seoul National University Bundang Hospital were divided into training and internal validation cohorts. Five machine learning techniques, including gradient boosting machine (GBM), support vector machine, random forest, decision tree, and neural network, were used to build predictive models, and the area under the receiver operating characteristic curve (AUC) was compared to select the best model. Finally, the model was validated using an independent cohort from Seoul National University Hospital. Results: A total of 1,003 patients were included in the study: 287, 71, and 645 in the training, internal validation, and external validation cohorts, respectively. Overall, 36.3% of the patients achieved pCR. Among the five machine learning models, the GBM showed the highest AUC for pCR prediction (AUC, 0.903; 95% confidence interval [CI], 0.833–0.972).External validation confirmed an AUC of 0.833 (95% CI, 0.800–0.865). Conclusion Commonly available clinical and demographic variables were used to develop a machine learning model for predicting pCR following NAC. External validation of the model demonstrated good discrimination power, indicating that routinely collected variables were sufficient to build a good prediction model.