Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Purpose: Triple-negative breast cancer (TNBC) is a particularly challenging subtype of breast cancer, with a poorer prognosis compared to other subtypes. Unfortunately, unlike luminal-type cancers, there is no validated biomarker to predict the prognosis of patients with early-stage TNBC. Accurate biomarkers are needed to establish effective therapeutic strategies. Materials and Methods: In this study, we analyzed gene expression profiles of tumor samples from 184 TNBC patients (training cohort, n=76; validation cohort, n=108) using RNA sequencing. Results: By combining weighted gene expression, we identified a 10-gene signature (DGKH, GADD45B, KLF7, LYST, NR6A1, PYCARD, ROBO1, SLC22A20P, SLC24A3, and SLC45A4) that stratified patients by risk score with high sensitivity (92.31%), specificity (92.06%), and accuracy (92.11%) for invasive disease-free survival. The 10-gene signature was validated in a separate institution cohort and supported by meta-analysis for biological relevance to well-known driving pathways in TNBC. Furthermore, the 10-gene signature was the only independent factor for invasive disease-free survival in multivariate analysis when compared to other potential biomarkers of TNBC molecular subtypes and T-cell receptor β diversity. 10-gene signature also further categorized patients classified as molecular subtypes according to risk scores. Conclusion Our novel findings may help address the prognostic challenges in TNBC and the 10-gene signature could serve as a novel biomarker for risk-based patient care.

Purpose: Patient-derived tumor cells can be a powerful resource for studying pathophysiological mechanisms and developing robust strategies for precision medicine. However, establishing organoids from patient-derived cells is challenging because of limited access to tissue specimens. Therefore, we aimed to establish organoids from malignant ascites and pleural effusions. Materials and Methods: Ascitic or pleural fluid from pancreatic, gastric, and breast cancer patients was collected and concentrated to culture tumor cells ex vivo. Organoids were considered to be successfully cultured when maintained for five or more passages. Immunohistochemical staining was performed to compare the molecular features, and drug sensitivity was assayed to analyze the clinical responses of original patients. Results: We collected 70 fluid samples from 58 patients (pancreatic cancer, n=39; gastric cancer, n=21; and breast cancer, n=10). The overall success rate was 40%; however, it differed with types of malignancy, with pancreatic, gastric, and breast cancers showing 48.7%, 33.3%, and 20%, respectively. Cytopathological results significantly differed between successful and failed cases (p=0.014). Immunohistochemical staining of breast cancer organoids showed molecular features identical to those of tumor tissues. In drug sensitivity assays, pancreatic cancer organoids recapitulated the clinical responses of the original patients. Conclusion Tumor organoids established from malignant ascites or pleural effusion of pancreatic, gastric, and breast cancers reflect the molecular characteristics and drug sensitivity profiles. Our organoid platform could be used as a testbed for patients with pleural and peritoneal metastases to guide precision oncology and drug discovery.

Background/Aims: There are few studies describing contemporary status of mechanical ventilation in Korea. We investigated changes in management and outcome of mechanical ventilation in Korea. Methods: International, prospective observational cohort studies have been conducted every 6 years since 1998. Korean intensive care units (ICUs) participated in 2010 and 2016 cohorts. We compared 2016 and 2010 Korean data. Results: Two hundred and twenty-six patients from 18 ICUs and 275 patients from 12 ICUs enrolled in 2016 and 2010, respectively. In 2016 compared to 2010, use of non-invasive ventilation outside ICU increased (10.2% vs. 2.5%, p = 0.001). Pressure-control ventilation was the most common mode in both groups. Initial tidal volume (7.1 mL/kg vs. 7.4 mL/kg, p = 0.372) and positive end-expiratory pressure (6 cmH2O vs. 6 cmH2O, p = 0.141) were similar, but peak pressure (22 cmH2O vs. 24 cmH2O, p = 0.011) was lower in 2016. More patients received sedatives (70.7% vs. 57.0%, p = 0.002) and analgesics (86.5% vs. 51.1%, p < 0.001) in 2016. The awakening (48.4% vs. 31.0%, p = 0.002) was more frequently attempted in 2016. The accidental extubation rate decreased to one tenth of what it was in 2010 (1.1% vs. 10.2%, p < 0.001). The ICU mortality did not change (31.4% 35.6%, p = 0.343) but ICU length of stay showed a decreasing trend (9 days vs. 10 days, p = 0.054) in 2016. Conclusions There were temporal changes in care of patients on mechanical ventilation including better control of pain and agitation, and active attempt of awakening.

Purpose: To develop a web-based solution for patient need-driven staffing (PNDS) that automatically determines nurses’ staffing requirements. Methods: Activities provided by nurses in four integrated nursing care wards (INCWs) and non-INCWs each in a tertiary hospital were observed over three days. Nursing hours per patient hour (NHPPH) were calculated by dividing nursing hours by patient stay hours per day. Patient needs were evaluated using 19 items. Results: The nurse-patient ratios in INCWs and non-INCWs were 1:4.5 and 1:8.1 (including overtime), respectively. Admitted and transferred-in patients had higher NHPPHs than those with continuing stays. The patients were classified into five groups: Group A for admissions and transfers-in, and Groups 1~4 for the remainder. In INCWs, the nurse-patient ratios ranged from 1:5.3 (Group 1) to 1:2.4 (Group 4), and Group A required 1:3.0, the secondhighest level. In non-INCWs, ratios ranged from 1:9.4 (Group 1) to 1:5.2 (Group 4 and Group A). The PNDS solution was developed to determine staffing requirements by classifying patients into five groups using the entered data on patient needs, assigning the group’s NHPPH to each patient, and calculating the staffing ratio required in the unit. Conclusion The PNDS is expected to support staffing decisions to meet patient needs.

Purpose: The purpose of the study was to shorten the KPCS-1 (Korean Patient Classification System-1) for predicting nursing care need level and to explore whether the patients can be clustered by their acuity and dependency. Methods: The participants were inpatients in two surgical wards and two internal medicine wards at a teritory hospital during 14 days investigations. The KPCS-1 was evaluated once a day for all inpatients and 2,082 cases of data from a total of 411 patients were analyzed. Results: The items were reducted from 50 items to 26 items by partial least squares analysis and expert review. Through factor analysis, it was confirmed that hygiene, diet, elimination, and exercise were categorized as dependence factors. Patients were clustered with low acuity/low dependency (average score: 7.68±2.81/1.05±1.33), high acuity/low dependency (average score: 17.20±4.15/1.94±2.40), medium acuity/high dependency (average score: 13.56±5.30/9.66±2.64) through cluster analysis. The total score of the three groups for their nursing care needs was 8.73±3.36, 19.14±5.74, and 23.24±6.31 in order, and the results showed a statistically significant difference (F=1712.12, p<.001). Conclusion The shortening of the KPCS-1 and the new criteria for categorizing patients according to acuity and dependence will increase clinical utility and be useful for manpower assignment criteria in detail.

Objective: To compare the convenience and effectiveness of the existing lumbosacral orthoses (LSO) (classic LSO and Cybertech) and a newly developed LSO (V-LSO) by analyzing postoperative data. Methods: This prospective cohort study was performed from May 2019 to November 2019 and enrolled and analyzed 88 patients with degenerative lumbar spine disease scheduled for elective lumbar surgery. Three types of LSO that were provided according to the time of patient registration were applied for 6 weeks. Patients were randomized into the classic LSO group (n=31), Cybertech group (n=26), and V-LSO group (n=31). All patients were assessed using the Oswestry Disability Index (ODI) preoperatively and underwent plain lumbar radiography (anteroposterior and lateral views) 10 days postoperatively. Lumbar lordosis (LS angle) and frontal imbalance were measured with and without LSO. At the sixth postoperative week, a follow-up assessment with the ODI and orthosis questionnaire was conducted. Results: No significant differences were found among the three groups in terms of the LS angle, frontal imbalance, ODI, and orthosis questionnaire results. When the change in the LS angle and frontal imbalance toward the reference value was defined as a positive change with and without LSO, the rate of positive change was significantly different in the V-LSO group (LS angle: 41.94% vs. 61.54% vs. 83.87%; p=0.003). Conclusion The newly developed LSO showed no difference regarding its effectiveness and compliance when compared with the existing LSO, but it was more effective in correcting lumbar lordosis.