Charlson Comorbidity Index and other predictors of in-hospital mortality among adults with community-acquired pneumonia

How to assess survival prognosis in patients hospitalized for community-acquired pneumonia in 2024?

PURPOSE OF REVIEW

Community-acquired pneumonia (CAP) is increasingly recognized as a complex, multisystemic disease with the potential to cause both acute and long-term sequelae, significantly impacting patient mortality rates. In this manuscript, the authors review the current methodologies for assessing mortality risk among CAP patients.

RECENT FINDINGS

The most common prediction scores for ICU care and short-term mortality include Pneumonia Severity Index (PSI), CURB-65, SMART COP, SCAP, and ATS/IDSA criteria. These models have clinical utility in the prediction of short-term mortality, but they have significant limitations in addressing long-term mortality. For patients who are discharged alive from the hospital, we do not have scores to predict long term mortality.

SUMMARY

The development of an optimal prognostic tool for postacute sequelae of CAP is imperative. Such a tool should identify specific populations at increased risk. Moreover, accurately identifying at-risk populations is essential for their inclusion in clinical trials that evaluate potential therapies designed to improve short and long-term clinical outcomes in patients with CAP.

ACCI could be a poor prognostic indicator for the in-hospital mortality of patients with SFTS

This study aims to evaluate the predictive role of age-adjusted Charlson comorbidity index (ACCI) scores for in-hospital prognosis of severe fever in thrombocytopenia syndrome (SFTS) patients. A total of 192 patients diagnosed with SFTS were selected as the study subjects. Clinical data were retrospectively collected. Receiver operating characteristic curves were used to evaluate the diagnostic value of ACCI for the mortality of SFTS patients, and Cox regression models were used to assess the association between predictive factors and prognosis. The 192 SFTS patients were divided into two groups according to the clinical endpoints (survivors/non-survivors). The results showed that the mortality of the 192 hospitalized SFTS patients was 26.6%. The ACCI score of the survivor group was significantly lower than that of the non-survivor group. Multivariate Cox regression analysis showed that the increased ACCI score was a significant predictor of poor prognosis in SFTS. Kaplan-Meier survival analysis showed that SFTS patients with an ACCI >2.5 had shorter mean survival times, indicating a poor prognosis. Our findings suggest that ACCI, as an easy-to-use clinical indicator, may offer a simple and feasible approach for clinicians to determine the severity of SFTS.

Role of Charlson comorbidity index in predicting the ICU admission in patients with thoracic aortic aneurysm undergoing surgery

OBJECTIVES

This study aimed to explore the value of the Charlson comorbidity index (CCI) in predicting ICU admission in patients with aortic aneurysm (AA).

METHODS

The clinical data of patients were obtained from the Medical Information Mart for Intensive Care-IV database. The association between CCI and ICU admission was explored by restricted cubic spline (RCS), threshold effect analysis, generalized linear model, logistic regression, interaction, and mediation analyses. Its clinical value was evaluated by decision curve analysis (DCA), receiver operating characteristic curve (ROC), DeLong's test, and net reclassification index (NRI) analyses.

RESULTS

The ICU admission was significantly associated with the thoracic AA (TAA), unruptured status, and surgery status. Therefore, 288 candidate patients with unruptured TAA who received surgery were enrolled in the further analysis. We found that CCI was independently associated with the ICU admission of candidates (P = 0.005). Further, their nonlinear relationship was observed (adjusted P = 0.008), and a significant turning point of 6 was identified. The CCI had a favorable performance in predicting ICU admission (area under curve = 0.728) and achieved a better clinical net benefit. New models based on CCI significantly improved the accuracy of prediction. Besides the importance of CCI in ICU admission, CCI also exerted important interaction effect (rather than mediating effects) on the association of other variables (such as age and blood variables) with ICU admission requirements (all P < 0.05).

CONCLUSIONS

The CCI is an important predictor of ICU admission after surgery in patients with unruptured TAA.

The Battle of the Pneumonia Predictors: A Comprehensive Meta-Analysis Comparing the Pneumonia Severity Index (PSI) and the CURB-65 Score in Predicting Mortality and the Need for ICU Support

The CURB-65 (confusion, uremia, respiratory rate, blood pressure, age ≥ 65 years) score and the pneumonia severity index (PSI) are widely used and recommended in predicting 30-day mortality and the need for intensive care support in community-acquired pneumonia. This study aims to compare the performance of these two severity scores in both mortality prediction and the need for intensive care support. A systematic review and meta-analysis was carried out, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 guidelines, and PubMed, Scopus, ScienceDirect, and Google Scholar were searched for articles published from 2012 to 2022. The reference lists of the included studies were also searched to retrieve possible additional studies. Twenty-five studies reporting prognostic information for CURB 65 and PSI were identified. ReviewManager (RevMan) 5.4.1 was used to produce risk ratios, and a random effects model was used to pool them. Both PSI and CURB-65 showed a high strength in identifying high-risk patients. However, CURB-65 was slightly better in early mortality prediction and had more sensitivity (96.7%) and specificity (89.3%) in predicting admission to intensive care support. Thus, CURB-65 seems to be the preferred tool in predicting mortality and the need for admission into intensive care support.

Impact of macrolide treatment on long-term mortality in patients admitted to the ICU due to CAP: a targeted maximum likelihood estimation and survival analysis

INTRODUCTION

Patients with community-acquired pneumonia (CAP) admitted to the intensive care unit (ICU) have high mortality rates during the acute infection and up to ten years thereafter. Recommendations from international CAP guidelines include macrolide-based treatment. However, there is no data on the long-term outcomes of this recommendation. Therefore, we aimed to determine the impact of macrolide-based therapy on long-term mortality in this population.

METHODS

Registered patients in the MIMIC-IV database 16 years or older and admitted to the ICU due to CAP were included. Multivariate analysis, targeted maximum likelihood estimation (TMLE) to simulate a randomised controlled trial, and survival analyses were conducted to test the effect of macrolide-based treatment on mortality six-month (6 m) and twelve-month (12 m) after hospital admission. A sensitivity analysis was performed excluding patients with Pseudomonas aeruginosa or MRSA pneumonia to control for Healthcare-Associated Pneumonia (HCAP).

RESULTS

3775 patients were included, and 1154 were treated with a macrolide-based treatment. The non-macrolide-based group had worse long-term clinical outcomes, represented by 6 m [31.5 (363/1154) vs 39.5 (1035/2621), p < 0.001] and 12 m mortality [39.0 (450/1154) vs 45.7 (1198/2621), p < 0.001]. The main risk factors associated with long-term mortality were Charlson comorbidity index, SAPS II, septic shock, and respiratory failure. Macrolide-based treatment reduced the risk of dying at 6 m [HR (95% CI) 0.69 (0.60, 0.78), p < 0.001] and 12 m [0.72 (0.64, 0.81), p < 0.001]. After TMLE, the protective effect continued with an additive effect estimate of - 0.069.

CONCLUSION

Macrolide-based treatment reduced the hazard risk of long-term mortality by almost one-third. This effect remains after simulating an RCT with TMLE and the sensitivity analysis for the HCAP classification.

All Patient Refined-Diagnosis Related Groups' (APR-DRGs) Severity of Illness and Risk of Mortality as predictors of in-hospital mortality

The aims of this study were to assess All-Patient Refined Diagnosis-Related Groups' (APR-DRG) Severity of Illness (SOI) and Risk of Mortality (ROM) as predictors of in-hospital mortality, comparing with Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) scores. We performed a retrospective observational study using mainland Portuguese public hospitalizations of adult patients from 2011 to 2016. Model discrimination (C-statistic/ area under the curve) and goodness-of-fit (R-squared) were calculated. Our results comprised 4,176,142 hospitalizations with 5.9% in-hospital deaths. Compared to the CCI and ECI models, the model considering SOI, age and sex showed a statistically significantly higher discrimination in 49.6% (132 out of 266) of APR-DRGs, while in the model with ROM that happened in 33.5% of APR-DRGs. Between these two models, SOI was the best performer for nearly 20% of APR-DRGs. Some particular APR-DRGs have showed good discrimination (e.g. related to burns, viral meningitis or specific transplants). In conclusion, SOI or ROM, combined with age and sex, perform better than more widely used comorbidity indices. Despite ROM being the only score specifically designed for in-hospital mortality prediction, SOI performed better. These findings can be helpful for hospital or organizational models benchmarking or epidemiological analysis.

Risk factors and mortality in elderly patients with severe hyponatremia admitted to the emergency department

BACKGROUND

This study was aimed at determining the risk factors associated with mortality in elderly patients with severe hyponatremia admitted to the emergency department.

MATERIALS AND METHODS

The data of patients aged ≥ 65 years who were admitted to the emergency department and whose serum sodium levels were < 125 mEq/L were retrospectively collected.

RESULTS

Mortality was associated with chronic liver disease/cirrhosis (p = 0.036), metastatic tumor (p = 0.007) and solid tumor (p = 0.013) cancers, antiarrhythmic drug use (p = 0.003), potassium-sparing diuretic use (p = 0.044), antineoplastic drug use (p = 0.0029), and dialysis treatment (p = 0.015). The following cutoff values were determined to be predictive of mortality: urea > 63.6 (AUC: 0.771; p = 0.0001), creatinine > 1.39 (AUC: 0.675; p = 0.0003), potassium > 4.64 (AUC: 0.711; p = 0.0001), C-reactive protein > 44 (AUC: 0.765; p = 0.0001), white blood cell count > 12.21 (AUC: 0.688; p = 0.0001), hemoglobin < 11.2 (AUC: 0.611; p = 0.0103), and Charlson comorbidity index > 2 (AUC: 0.739; p = 0.0001). The use of antineoplastic drugs (OR: 4.502; p = 0.010) and increased values of the following were associated with an increased risk of mortality: urea (OR: 1.007; p = 0.024), C-reactive protein (OR: 1.005; p = 0.026), glucose (OR: 1.008; p = 0.001), and Charlson comorbidity index (OR: 1.198; p = 0.025).

CONCLUSION

Malignancy; liver cirrhosis; dialysis treatment; increased Charlson comorbidity index, urea, and C-reactive protein values and the use of antineoplastic drugs are associated with mortality.

The Impact of Risk Factors on Treatment Outcomes of Nosocomial Pneumonia Due to Gram-Negative Bacteria in the Intensive Care Unit

Introduction

Nosocomial pneumonia is a common infection associated with high mortality in hospitalized patients. Nosocomial pneumonia, caused by gram-negative bacteria, often occurs in the elderly and patients with co-morbid diseases.

Methods

Original research using a prospective cross-sectional design was conducted on 281 patients in an intensive care unit setting with nosocomial pneumonia between July 2015 and July 2019. For each nosocomial pneumonia case, data regarding comorbidities, risk factors, patient characteristics, Charlson comorbidity index (CCI), Systemic Inflammatory Response Syndrome (SIRS), and quick Sepsis-Related Organ Failure Assessment (qSOFA) points and treatment outcomes were collected. Data were analyzed by SPSS 22.0.

Results

Nosocomial pneumonia due to gram-negative bacteria occurred in patients with neurological disorders (34.87%), heart diseases (16.37%), chronic renal failure (7.12%), and post-surgery (10.68%). Worse outcomes attributed to nosocomial pneumonia were high at 75.8%. Mechanical ventilation, change of antibiotics, and CCI ≥ 3 and qSOFA ≥ 2 were significantly negative prognostic factors (p < 0.05) on outcomes of nosocomial pneumonia. There was no difference in treatment effects between gender, age, time of onset pneumonia, SIRS score (p > 0.05). The pathogens were significant factors that influence treatment effects, but they weren't independent risk factors for poor outcomes (p = 0.823).

Conclusions

Patients with nosocomial pneumonia hospitalized in intensive care units are usually associated with many underlying diseases, including neurological diseases. Mechanical ventilation, a change in antibiotics, CCI ≥ 3, and qSOFA ≥ 2 are also associated with a worse prognosis of nosocomial pneumonia. CCI and qSOFA might be used in predicting the outcome of nosocomial pneumonia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41030-021-00175-4.

Predictive capacity of prognostic scores for kidney injury, dialysis, and death in intensive care units

OBJECTIVE

To assess the capacity of Charlson, SAPS 3 and SOFA scores to predict acute kidney injury, need for dialysis, and death in intensive care unit patients.

METHOD

Prospective cohort, with 432 individuals admitted to four intensive care units. Clinical characteristics at admission, severity profile, and intensity of care were analyzed using association and correlation tests. The scores sensitivity and specificity were assessed using the ROC curve.

RESULTS

The results show that patients with acute kidney injury were older (65[27] years vs. 60[25] years, p = 0.019) and mostly are from the emergency department (57.9% vs. 38.0 %, p < 0.001), when compared to those in the group without acute kidney injury. For dialysis prediction, the results of SAPS 3 and SOFA were AUC: 0.590; 95%CI: 0.507-0.674; p-value: 0.032 and AUC: 0.667; 95%CI: 0.591-0.743; p-value: 0.000, respectively. All scores performed well for death.

CONCLUSION

The prognostic scores showed good capacity to predict acute kidney injury, dialysis, and death. Charlson Comorbidity Index showed good predictive capacity for acute kidney injury and death; however, it did not perform well for the need for dialysis.

Evaluation of severity scoring systems in patients with severe community acquired pneumonia

BACKGROUND

The aim of this study was to evaluate the ability of severity scoring systems to predict 30-day mortality in patients with severe community-acquired pneumonia.

METHODS

The study included 98 patients aged ≥18 years with community acquired pneumonia hospitalized at the Intensive Care Unit of the University Clinic for Infectious Diseases in Skopje, Republic of North Macedonia, during a 3-year period. We recorded demographic, clinical and common biochemical parameters. Five severity scores were calculated at admission: CURB 65 (Confusion, Urea, Respiratory Rate, Blood pressure, Age ≥65 years), SCAP (Severe Community Acquired Pneumonia score), SAPS II (Simplified Acute Physiology Score), SOFA (Sequential Organ Failure Assessment Score) and MPM (Mortality Prediction Model). Primary outcome variable was 30-day in-hospital mortality.

RESULTS

The mean age of the patients was 59.08 ± 15.76 years, predominantly males (68%). The overall 30-day mortality was 52%. Charlson Comorbidity index was increased in non-survivors (3.72 ± 2.33) and was associated with the outcome. All severity indexes had higher values in patients who died, that showed statistical significance between the analysed groups. The areas under curve (AUC) values of the five scores for 30-day mortality were 0.670, 0.732, 0,726, 0.785 and 0.777, respectively.

CONCLUSION

Widely used severity scores accurately detected patients with pneumonia that had increased risk for poor outcome, but none of them individually demonstrated any advantage over the others.