Predicting short-term and long-term mortalities from sepsis in patients who receive allogeneic haematopoietic stem cell transplantation

Patients who receive allogeneic haematopoietic stem cell transplantation (allo-HSCT) may develop sepsis, which result in a highly intensive care unit admission rate and mortality. Therefore, short-term and long-term prognostic models for sepsis after allo-HSCT are urgently needed. We enrolled patients receiving allo-HSCT who developed sepsis after allo-HSCT at Peking University People's Hospital between 2012 and 2021, including 287 patients who received allo-HSCT in 2018-2021 in the derivation cohort, and 337 patients in 2012-2017 in the validation cohort. Multivariate logistic regression analysis was used to identify prognostic factors, and these identified factors were incorporated into two scoring models. Seven independent factors (acute graft-versus-host disease (GVHD), chronic GVHD (cGVHD), total bilirubin, lactate dehydrogenase (LDH) and organ dysfunction [renal, lung and heart]) were included in the 6-month prognostic model, and six factors (cGVHD, C-reactive protein, LDH, organ dysfunction [lung, neurologic and coagulation]) were included in the 14-day prognostic model. The area under the receiver operating characteristic curves, calibration plots and decision curve analysis demonstrated the robust predictive performance of the models, better than the Sequential Organ Failure Assessment score. Early identification of patients with high risk of 6-month and 14-day death may allow clinicians to provide timely treatments and improve the therapeutic effects.

Risk Factors Associated With Six-Month Mortality in Hospitalized COVID-19 Patients: A Single-Institution Study

Background Coronavirus disease 2019 (COVID-19) infection can vary from asymptomatic infection to multi-organ dysfunction. The most serious complication of infection with COVID-19 is death. Various comorbid conditions and inflammatory markers have been associated with an increased risk of mortality, specifically within the immediate post-infection period; however, less is known about long-term mortality outcomes. Objectives Our objective is to determine risk factors associated with six-month mortality in hospitalized COVID-19 patients. Methods This is a single-institution, retrospective study. We included patients hospitalized with COVID-19 from the University of Toledo Medical Center in Toledo, Ohio, who were admitted from March 20, 2020, to June 30, 2021. This study was approved by a biomedical institutional review board at the University of Toledo. Patients with available pre-stored blood samples for laboratory testing were included, and hospital charts were assessed up to six months from the date of a positive COVID-19 test result. Two groups were created based on the mortality outcome at six months from COVID-19 positive test results: survivors and non-survivors. The clinical variables or outcomes and laboratory values were compared between the two groups using non-parametric methods due to the small sample size and non-normality of the data. Either the Mann-Whitney U-test for continuous variables or Fisher's exact test for categorical variables was used for statistical analysis. Results Lactate dehydrogenase (LDH) and D-dimer levels on admission were found to be significantly higher in non-survivors than in survivors. The median high D-dimer level in non-survivors was 5.96 micrograms/milliliter (μg/mL) (interquartile range (IQR): 3.95-11.29 μg/mL) vs 1.82 μg/mL (IQR 1.13-5.55 μg/mL) in survivors (p = 0.019). Median LDH levels were also higher in non-survivors vs survivors, i.e., 621.00 international units per liter (IU/L) (IQR 440.00-849.00 IU/L) vs 328.00 IU/L (IQR 274.00-529.00 IU/L), respectively (p = 0.032). The demographic profile, comorbidity profile, and laboratory data (typically associated with short-term mortality, inflammation, and organ dysfunction) were similar between survivors and non-survivors, except for LDH and D-dimer. Conclusion Higher LDH and D-dimer levels on admission were found to be associated with an increased six-month mortality rate in hospitalized COVID-19 patients. These hematologic data can serve as risk stratification tools to prevent long-term mortality outcomes and provide proactive clinical care in hospitalized COVID-19 patients.

Trends in Early Mortality From Multiple Myeloma: A Population-Based Analysis

INTRODUCTION

Despite significant improvements in multiple myeloma (MM) treatment modalities, patient mortality early in the course of disease has been identified as a persistent phenomenon with variable reported rates and causes. Trends in early mortality over time have not been clearly defined.

PATIENTS AND METHODS

The Surveillance Epidemiology and End Results (SEER) database was used to identify adult patients with MM between 1975 and 2015. Association of available sociodemographic factors with all-cause and MM-specific early mortality (death within 6 months after the diagnosis of MM) was conducted by multivariate analysis. Trends in early mortality were studied by joinpoint regression analysis.

RESULTS

Of the 90,975 MM cases included in this analysis, early mortality was noted in 21%. Median age was 68 years overall, and 75 years for the early mortality cohort (P < .01). The most common causes of death for early mortality were MM itself, followed by cardiovascular, infections, and renal failure. Male gender, "other" race/ethnicity group, advancing age, and West, Midwest or South regions (reference Northeast) were associated with increased risk of both all-cause and MM-specific early mortality. Joinpoint regression analysis of trends data resulted in 1 joinpoint for all-cause 6-month mortality (2006-2015), while 2 joinpoints were noticed for myeloma-specific 6-month mortality (1975-1987 and 2003-2015).

CONCLUSION

Early mortality remains a significant unmet need for MM patient care, despite improving trends in recent years. Understanding the factors associated with early mortality can help develop individualized plans of patient care and mitigate circumstances that may contribute to early mortality among MM patients.

[An independent observatory in Vendée on ST-elevated acute myocardial infarction (the OVISCA Register). A Departmental evaluation of demographic trends, mortality and delays before treatment]

AIM

Mortality from acute myocardial infarction has been falling during the past 30 years. The aim of the study was to evaluate the temporal trends of demographics, mortality rates, and time to treatment in patients admitted for acute ST elevation myocardial infarction (STEMI) in Vendée.

PATIENTS AND METHODS

From 2008 to 2016, 1994 patients hospitalised in CHD Vendée for STEMI <48hours were included. Two groups were compared, 838 patients admitted between 2008 and 2011 (group 1), and 1156 admitted between 2013 and 2016 (group 2).

RESULTS

Between the 2 periods, mean age was comparable (63.8 vs. 64.4 years), the gender ratio decreased (from 3.15 to 2.79 ; P=0.25). The mean duration of hospital stay was 0.8 day shorter (P=0.008). Treatment at discharge was optimum in 97.5% patients versus 92% (P<0.001). Left ventricular ejection fraction was comparable (50.6% vs. 50.2%). There was a non-significant trend to a decrease in hospital mortality (from 6.3% to 4.4%; p=0.12), and 6-month mortality (from 6.9% to 5.9%; P=0.51). There was a reduction in the use of emergency call-outs (74.9% to 68.9%; P<0.01), but an increase in direct presentations from 44% to 48.7% (P<0.05). The time before calling was comparable (2.5hours vs. 2.3hours; P=04.7). The "door-to-balloon" time decreased (0.71 vs. 0.55hour; P<0.001). The mean time between pain and angioplasty increased (5.7 vs. 6.8hours; P<0.05).

CONCLUSIONS

In vendee, from 2011 to 2016, hospital and 6-month mortality of STEMI trend to decrease non-significantly. The door to balloon time decreased, although emergency call-out rates and delays did not. Considerable efforts are still required with respect to patient information and education. Our registry offers an excellent tool to improve practices, the aim being to ensure its integration in the CRAC-France PCI registry.

Derivation and Validation of a Prognostic Model to Predict 6-Month Mortality in an Intensive Care Unit Population

RATIONALE

Identification of terminally ill patients in the intensive care unit (ICU) would facilitate decision making and timely palliative care.

OBJECTIVES

To develop and validate a patient-specific integrated prognostic model to predict 6-month mortality in medical ICU patients.

METHODS

A longitudinal prospective cohort study of temporally split samples of 1,049 consecutive medical ICU patients in a tertiary care hospital was performed. For each patient, we collected demographic data, Acute Physiology and Chronic Health Evaluation III score, Charlson comorbidity index, intensivist response to a surprise question (SQ; "Would I be surprised if this patient died in the next 6 months?") on admission, and vital status at 6 months.

RESULTS

Between November 2013 and May 2015, derivation and validation cohorts of 500 and 549 consecutive patients were studied to develop a multivariate logistic regression model. In the multivariate logistic regression model, Charlson comorbidity index (P = 0.033), Acute Physiology and Chronic Health Evaluation III score (P < 0.001), and SQ response (P < 0.001) were predictors of vital status at 6 months. The odds of dying within 6 months were significantly higher when the SQ was answered "no" than when it was answered "yes" (odds ratio, 7.29; P < 0.001). The c-statistic for the derivation and validation cohorts were 0.832 (95% confidence interval, 0.795-0.870) and 0.84 (95% confidence interval, 0.806-0.875), respectively.

CONCLUSIONS

Our integrated prognostic model, which includes the SQ, has strong discrimination and calibration to predict 6-month mortality in medical ICU patients. This model can aid clinicians in identifying ICU patients who may benefit from the integration of palliative care into their treatment.

Predicting 6-month mortality risk of patients commencing dialysis treatment for end-stage kidney disease

Background

There is evidence that end-stage kidney disease patients who are older or with more comorbidity may have a poor trade-off between benefits of dialysis and potential harms. We aimed to develop a tool for predicting patient mortality in the early stages of receiving dialysis.

Methods

In 23 658 patients aged 15+ years commencing dialysis between 2000 and 2009 in Australia and New Zealand a point score tool was developed to predict 6-month mortality based on a logistic regression analysis of factors available at dialysis initiation. Temporal validation used 2009-11 data from Australia and New Zealand. External validation used the UK Renal Registry.

Results

Within 6 months of commencing dialysis 6.1% of patients had died. A small group (4.7%) of patients had a high predicted mortality risk (>20%), as predicted by the point score tool. Predictive variables were: older age, underweight, chronic lung disease, coronary artery disease, peripheral vascular disease, cerebrovascular disease (particularly for patients <60 years of age), late referral to nephrologist care and underlying cause of renal disease. The new point score tool outperformed existing models, and had an area under the receiver operating characteristic curve of 0.755 on temporal validation with acceptable calibration and 0.713 on external validation with poor calibration.

Conclusion

Our point score tool for predicting 6-month mortality in patients at dialysis commencement has sufficient prognostic accuracy to use in Australia and New Zealand for prognosis and identification of high risk patients who may be given appropriate supportive care. Use in other countries requires further study.

Has invasive management for acute coronary syndromes become more 'risk-appropriate': pooled results of five Australian registries

Background

Despite being recommended in acute coronary syndrome (ACS) guidelines, the use of invasive management within specific risk groups continues to be debated. This study examines the change in the use of invasive management in ACS by patient risk and the associated change in mortality within Australia over the last 17 years.

Methods

Pooled cohorts derived from five ACS registries (ACACIA, CONCORDANCE, GRACE, Snapshot-ACS, and Predict) spanned from 1999 to 2015. After excluding patients without a final diagnosis of ACS (n = 4460), enrolled outside Australia (n = 1477) and without an enrolling year (n = 4), 15 912 patients were analysed. Data was stratified across three time periods (1999-2004, 2005-2009, and 2010-2015) using clinical risk characteristics (age, ACS diagnosis, biomarker elevation, and GRACE score) to monitor change in practice.

Results

Over the 17-year period, the use of invasive management increased (4073/6863 (59.3%) cases [1999-2009] vs. 6670/8706 (76.6%) cases [2010-2015]). Invasive management accounted for improvements in mortality in intermediate- and high-risk groups (intermediate risk: 14% (95% CI 1-66%) [1999-2009] vs. 49% (95% CI 2-59%) [2010-2015]; high risk: 24% (95% CI 6-42%) [1999-2009] vs. 48% (95% CI 19-76%) [2010-2015]). Patients receiving no angiography compared with interventional management had worse outcomes (1999-2004 1.55 HR [95% CI 1.36-1.80], P < 0.0001 vs. 2010-2015 1.90 HR [95% CI 1.45-2.51], P < 0.0001).

Conclusions

Clinical practice in ACS has changed over the last 17 years with positive outcomes seen with invasive management among high-risk patients. Unfortunately, a considerable burden of mortality remains in patients managed medically, highlighting a need for more focused strategies that improve care and outcomes in this group.