Sepsis poses a significant threat to human health due to its high morbidity and mortality rates worldwide. Traditional diagnostic methods for identifying sepsis or its causative organisms are time-consuming and contribute to a high mortality rate. Biomarkers have been developed to overcome these limitations and are currently used for sepsis diagnosis, prognosis prediction, and treatment response assessment. Over the past few decades, more than 250 biomarkers have been identified, a few of which have been used in clinical decision-making. Consistent with the limitations of diagnosing sepsis, there is currently no specific treatment for sepsis. Currently, the general treatment for sepsis is conservative and includes timely antibiotic use and hemodynamic support. When planning sepsis-specific treatment, it is important to select the most suitable patient, considering the heterogeneous nature of sepsis. This comprehensive review summarizes current and evolving biomarkers and therapeutic approaches for sepsis.

Background: Successful sepsis treatment depends on early diagnosis. We aimed to develop and validate a system to predict sepsis and septic shock in real time using deep learning. Methods: Clinical data were retrospectively collected from electronic medical records (EMRs). Data from 2010 to 2019 were used as development data, and data from 2020 to 2021 were used as validation data. The collected EMRs consisted of eight vital signs, 13 laboratory data points, and three demographic information items. We validated the deep-learning-based sepsis and septic shock early prediction system (DeepSEPS) using the validation datasets and compared our system with other traditional early warning scoring systems, such as the national early warning score, sequential organ failure assessment (SOFA), and quick sequential organ failure assessment. Results: DeepSEPS achieved even higher area under receiver operating characteristic curve (AUROC) values (0.7888 and 0.8494 for sepsis and septic shock, respectively) than SOFA. The prediction performance of traditional scoring systems was enhanced because the early prediction time point was close to the onset time of sepsis; however, the DeepSEPS scoring system consistently outperformed all conventional scoring systems at all time points. Furthermore, at the time of onset of sepsis and septic shock, DeepSEPS showed the highest AUROC (0.9346). Conclusions: The sepsis and septic shock early warning system developed in this study exhibited a performance that is worth considering when predicting sepsis and septic shock compared to other traditional early warning scoring systems. DeepSEPS showed better performance than existing sepsis prediction programs. This novel real-time system that simultaneously predicts sepsis and septic shock requires further validation.

Kim TW, et al. J Korean Med Sci. 2024 Feb;39:e75. https://doi.org/10.3346/jkms.2024.39.e75

Rehabilitation during extracorporeal membrane oxygenation (ECMO) has become a promising intervention to mitigate the profound physical and functional decline that occurs with prolonged critical illness. With the wider adoption of ECMO, interest has grown in integrating early mobilization into routine care practices to preserve muscle mass, reduce intensive care unit-acquired weakness, and improve long-term patient outcomes. Emerging observational data indicate that structured rehabilitation protocols—including passive and active mobilization—are feasible and safe, including for individuals undergoing femoral cannulation. Nevertheless, multiple obstacles, including patient instability, technical constraints, staffing limitations, and gaps in clinical knowledge, impede broader implementation. Although the theoretical rationale and initial data are compelling, further robust randomized controlled trials are essential to establish the definitive efficacy, best-practice protocols, and cost-effectiveness of rehabilitation interventions in ECMO-supported patients.

Background: There is a lack of information on the waitlist performance and post‐transplant outcomes of lung transplants in elderly recipients in Korea.Methods: We retrospectively reviewed and analyzed data from the Korean Network for Organ Sharing database between March 2010 and August 2023.Results: In total, 2574 patients were listed for lung transplantation during the study period, with 511 (19.9%) of them being over 65 years of age. Among these, 188 patients (36.8%) underwent transplantation, while 184 patients (36%) passed away without undergoing transplantation at the time of data extraction. The most prevalent underlying disease on the waitlist was idiopathic pulmonary fibrosis, accounting for 68.1%. The 1‐year survival rate was significantly lower in the elderly compared to that in the nonelderly (65.4 vs. 75.4%;p = .004). In the multivariate Cox analysis, elderly (hazard ratio [HR], 1.49; 95% CI, 1.14–1.97;p = .004) and a high urgent status at registration (HR, 1.83; 95% CI, 1.40–2.40;p < .001) were significantly associated with post‐transplant 1‐year mortality. Kaplan–Meier curves demonstrated a significant difference in post‐transplant mortality based on the urgency status at enrollment (χ² = 8.302,p = .016). Even with the same highly urgent condition at the time of transplantation, different prognoses were observed depending on the condition at listing (χ² = 9.056,p = .029).Conclusion: The elderly exhibited worse transplant outcomes than nonelderly adults, with a highly urgent status at registration identified as a significant risk factor. Unprepared, highly urgent transplantation was associated with poor outcomes.

Background: The coronavirus disease (COVID-19) pandemic has significantly strained global healthcare, particularly in the management of patients requiring mechanical ventilation (MV) and continuous renal replacement therapy (CRRT). This study investigated the characteristics and prognoses of these patients. Methods: This multicenter retrospective cohort study gathered data from patients with COVID-19 across 26 medical centers. Logistic analysis was used to identify the factors associated with CRRT implementation. Results: Of the 640 patients with COVID-19 who required MV, 123 (19.2%) underwent CRRT. Compared to the non-CRRT group, the CRRT group was older and exhibited higher sequential organ failure assessment scores. The incidence of hypertension, diabetes, cardiovascular disease, chronic neurological disease, and chronic kidney disease was also higher in the CRRT group. Moreover, the CRRT group had higher intensive care unit (ICU) (75.6% vs. 26.9%, p < 0.001) and in-hospital (79.7% vs. 29.6%, p < 0.001) mortality rates. CRRT implementation was identified as an independent risk factor for both ICU mortality (hazard ratio [HR]:1.833, 95% confidence interval [CI]:1.342–2.505, p < 0.001) and in-hospital mortality (HR: 2.228, 95% CI: 1.648–3.014, p < 0.001). Refractory respiratory failure (n = 99, 19.1%) was the most common cause of death in the non-CRRT death group, and shock with multi-organ failure (n = 50, 40.7%) was the most common cause of death in the CRRT death group. Shock with multi-organ failure and cardiac death were significantly more common in the CRRT death group, compared to non-CRRT death group. Conclusion: This study indicates that CRRT is associated with higher ICU and in-hospital mortality rates in patients with COVID-19 who require MV. Notably, the primary cause of death in the CRRT group was shock with multi-organ failure, emphasizing the severe clinical course for these patients, while refractory respiratory failure was most common in non-CRRT patients.