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

Sepsis survivors readmitted within 30 days: outcomes of a single-center retrospective study

OBJECTIVE

To investigate a cohort of sepsis survivors readmitted within 30 days postdischarge, explore the one-year mortality rate based on different causes of readmission and identify factors associated with increased one-year mortality risk among all sepsis survivors readmitted within this timeframe.

METHODS

This was a single-center retrospective cohort study involving adult sepsis survivors who were readmitted within 30 days of discharge. Patients were categorized into 3 groups based on the cause of readmission: same-source infectious readmission, different-source infectious readmission, and noninfectious readmission. The outcome of interest was all-cause one-year mortality. Cox proportional hazard analysis was performed to compare factors associated with one-year mortality.

RESULTS

Of the 1,666 patients admitted with sepsis, 243 (14.5%) were readmitted within 30 days. Readmissions were due to same-source infections (40.7%), different-source infections (21.4%), or noninfectious causes (37.9%). All-cause one-year mortality was 46.9%, with no difference between the groups. Age (HR 1.02; 95%CI: 1.003 - 1.04; p = 0.01), Sequential Organ Failure Assessment score (HR 1.1; 95%CI: 1.02 - 1.18; p = 0.01), discharge to a care facility during index admission (HR 1.6; 95%CI: 1.04 - 2.40; p = 0.03), and malignancy (HR 2.3; 95%CI: 1.5 - 3.7; p < 0.001) were associated with one-year mortality.

CONCLUSION

Thirty-day readmission in sepsis survivors was common and was associated with a 46.9% one-year mortality rate regardless of readmission cause. Quality improvement patient safety initiatives based on local institutional factors may allow for targeted interventions to improve sepsis survivor outcomes.

Comprehensive risk factor-based nomogram for predicting one-year mortality in patients with sepsis-associated encephalopathy

Sepsis-associated encephalopathy (SAE) is a frequent and severe complication in septic patients, characterized by diffuse brain dysfunction resulting from systemic inflammation. Accurate prediction of long-term mortality in these patients is critical for improving clinical outcomes and guiding treatment strategies. We conducted a retrospective cohort study using the MIMIC IV database to identify adult patients diagnosed with SAE. Patients were randomly divided into a training set (70%) and a validation set (30%). Least absolute shrinkage and selection operator regression and multivariate logistic regression were employed to identify significant predictors of 1-year mortality, which were then used to develop a prognostic nomogram. The model's discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis, respectively. A total of 3,882 SAE patients were included in the analysis. The nomogram demonstrated strong predictive performance with AUCs of 0.881 (95% CI: 0.865, 0.896) in the training set and 0.859 (95% CI: 0.830, 0.888) in the validation set. Calibration plots indicated good agreement between predicted and observed 1-year mortality rates. The decision curve analysis showed that the nomogram provided greater net benefit across a range of threshold probabilities compared to traditional scoring systems such as Glasgow Coma Scale and Sequential Organ Failure Assessment. Our study presents a robust and clinically applicable nomogram for predicting 1-year mortality in SAE patients. This tool offers superior predictive performance compared to existing severity scoring systems and has significant potential to enhance clinical decision-making and patient management in critical care settings.

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.