Impact of cancer on mortality rates in patients with sepsis: A meta-analysis and meta-regression of current studies

Risk Factors and Outcomes of Community-Acquired Carbapenem-Resistant Klebsiella pneumoniae Infection in Elderly Patients

The increasing prevalence of carbapenem-resistant Klebsiella pneumoniae (CRKP) infections is a global concern. Elderly patients have a diminished immune response and functional reserve, and are thus more vulnerable to bacterial infection. This study aimed to investigate the risk factors and outcomes in elderly patients with community-acquired CRKP infections. We performed a retrospective cohort study in a tertiary medical center between 1 January 2021, and 31 December 2021. All elderly patients who visited the emergency department during this period with culture-positive K. pneumoniae were enrolled, and their baseline demographics, laboratory profiles, management strategies, and outcomes were recorded and analyzed. We identified 528 elderly patients with K. pneumonia infection, and the proportion of patients with CRKP infection was 10.2% (54/528). Recent intensive care unit (ICU) admission and prior carbapenem use are independent risk factors for CRKP infection in elderly patients. Compared to patients with carbapenem-sensitive K. pneumoniae infection, those with CRKP infection had a significantly higher risk of adverse outcomes, including ICU care, respiratory failure, septic shock, and 90-day mortality. CRKP infection was also identified as an independent risk factor for 90-day mortality. Clinicians should be aware of the increasing prevalence of CRKP infections in elderly patients and judiciously choose appropriate antibiotics for these patients.

An Individualized Nomogram for Predicting Mortality Risk of Septic Shock Patients During Hospitalization: A ten Years Retrospective Analysis

Purpose

We intend to develop a nomogram for predicting the mortality risk of hospitalized septic shock patients.

Patients and Methods

Data were collected from patients hospitalized with septic shock in Affiliated Dongyang Hospital of Wenzhou Medical University in China, over 10 years between January 2013 and January 2023. The eligible study participants were divided into modeling and validation groups. Factors independently related to the mortality in the modeling group were obtained by stepwise regression analysis. A logistic regression model and a nomogram were built. The model was evaluated based on the discrimination power (the area under the curve of the receiver operating characteristic, AUC), the calibration degree and decision curve analysis. In the validation group, the discrimination powers of the logistic regression model, the sequential organ failure assessment (SOFA) scoring model and machine learning model were compared.

Results

A total of 1253 patients, including 878 patients in the modeling group and 375 patients in the validation group, were included in this study. Age, respiratory failure, serum cholinesterase, lactic acid, blood phosphorus, blood magnesium, total bilirubin, and pH were independent risk factors related to the mortality risk of septic shock. The AUCs of the prediction model for the modeling and validation groups were 0.881 and 0.868, respectively. The models had a good calibration degree and clinical applicability. The AUC of the SOFA model for the validation population was 0.799, significantly lower than that of our model. The AUCs of the random forest and ensemble models were 0.865 and 0.863, respectively, comparable to that of our logistical prediction model.

Conclusion

The model established in this study can effectively predict the mortality risk in patients hospitalized with septic shock. Thus, the model could be used clinically to determine the best therapy or management for patients with septic shock.

Cancer and sepsis

Sepsis is one of the leading causes of death worldwide. While mortality is high regardless of inciting infection or comorbidities, mortality in patients with cancer and sepsis is significantly higher than mortality in patients with sepsis without cancer. Cancer patients are also significantly more likely to develop sepsis than the general population. The mechanisms underlying increased mortality in cancer and sepsis patients are multifactorial. Cancer treatment alters the host immune response and can increase susceptibility to infection. Preclinical data also suggests that cancer, in and of itself, increases mortality from sepsis with dysregulation of the adaptive immune system playing a key role. Further, preclinical data demonstrate that sepsis can alter subsequent tumor growth while tumoral immunity impacts survival from sepsis. Checkpoint inhibition is a well-accepted treatment for many types of cancer, and there is increasing evidence suggesting this may be a useful strategy in sepsis as well. However, preclinical studies of checkpoint inhibition in cancer and sepsis demonstrate results that could not have been predicted by examining either variable in isolation. As sepsis management transitions from a 'one size fits all' model to a more individualized approach, understanding the mechanistic impact of cancer on outcomes from sepsis represents an important strategy towards delivering on the promise of precision medicine in the intensive care unit.

Impact of Infection Patterns on the Outcomes of Patients with Hematological Malignancies in Southwest China: A 10-Year Retrospective Case-Control Study

Background

This study aimed to assess the effect of infection patterns on the outcomes of patients with hematological malignancies (HM) and to identify the determinants of in-hospital mortality.

Methods

A case-control study was retrospectively conducted in a tertiary teaching hospital in Chongqing, Southwest China from 2011 to 2020. Clinical characteristics, microbial findings, and outcomes of HM patients with infections were retrieved from the hospital information system. Chi-square or Fisher's exact test was adopted to test the significance of mortality rate. Kaplan-Meier survival analysis and Log rank test were applied to evaluate and compare the 30-day survival rates of those groups. Binary logistic regression, Cox proportional hazards regression, and receiver operating characteristic curves were used to investigate the determinants of in-hospital mortality.

Results

Of 1,570 enrolled participants, 43.63% suffered from acute myeloid leukemia, 69.62% received chemotherapy, and 25.73% had hematopoietic stem cell transplantation (HSCT). Microbial infection was documented in 83.38% of participants. Co-infection and septic shock were reported in 32.87% and 5.67% of participants, respectively. Patients with septic shock suffered a significantly lower 30-day survival rate, while those with distinct types of pathogens or co-infections had a comparable 30-day survival rate. The all-cause in-hospital mortality was 7.01% and higher mortality rate was observed in patients with allo-HSCT (7.20%), co-infection (9.88%), and septic shock (33.71%). Cox proportional hazards regression illustrated that elderly age, septic shock, and elevated procalcitonin (PCT) were independent predictors of in-hospital mortality. A PCT cut-off value of 0.24 ng/mL predicted in-hospital mortality with a sensitivity of 77.45% and a specificity of 59.80% (95% CI = 0.684-0.779, P<0.0001).

Conclusion

Distinct infectious patterns of HM inpatients were previously unreported in Southwest China. It was the severity of infection, not co-infection, source of infection, or type of causative pathogen that positively related to poor outcome. PCT guided early recognition and treatment of septic shock were advocated.