Defining and predicting severe community-acquired pneumonia

Severe community-acquired pneumonia (sCAP): advances in management and future directions

Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity and mortality, especially among patients requiring intensive care. Despite advancements in antimicrobial therapies and supportive care, sCAP remains a significant threat, particularly for those needing invasive mechanical ventilation or vasopressor support. Recent progress in diagnostics, therapeutics and management strategies offers hope for improved outcomes. Pathogen-specific management is now central to sCAP care, with molecular diagnostics enhancing pathogen detection accuracy and enabling tailored antimicrobial therapy. These tools help combat antimicrobial resistance by reducing unnecessary broad-spectrum antibiotic use.Host immune responses in sCAP vary widely and significantly impact outcomes. Some patients face an overwhelming pathogen burden, while others experience excessive immune responses, such as acute respiratory distress syndrome. This distinction is vital for guiding immunomodulatory therapies, as immunosuppression may benefit hyperinflammatory states but harm those overwhelmed by infection. Corticosteroids, though controversial, show potential benefits in select populations but carry risks like secondary infections and hyperglycaemia, requiring a nuanced approach.Non-invasive respiratory support strategies, such as high-flow nasal oxygen, have transformed care by improving oxygenation and reducing the need for invasive ventilation. However, their efficacy depends on timing, patient tolerance and disease severity, necessitating careful monitoring.Global disparities in sCAP management, particularly in low-income and middle-income countries, highlight the need for region-specific guidelines and scalable solutions. Limited access to advanced diagnostics and critical care resources exacerbates poor outcomes, underscoring the importance of investments in affordable diagnostics, infection control and multidisciplinary training. Emerging technologies, such as artificial intelligence and advanced imaging, promise to revolutionise sCAP management by enabling precision medicine and real-time insights into disease severity. A holistic, multidisciplinary approach integrating these advancements is essential to improving outcomes and advancing personalised care for this life-threatening condition.

Prognostic value of the platelet, neutrophil, monocyte, basophil, and eosinophil to lymphocyte ratios in patients with severe community-acquired pneumonia (SCAP)

Severe community-acquired pneumonia (SCAP) is a serious respiratory inflammation disease with high morbidity and mortality. This study aimed to evaluate the prognostic value of the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), basophil-to-lymphocyte ratio (BLR) and eosinophil-to-lymphocyte ratio (ELR) in patients with SCAP. The study retrospectively included 554 patients with SCAP, and the clinical data were obtained from the electronic patient record (EMR) system. The primary outcome was in-hospital mortality, and the secondary outcomes included hospital length of stay (LOS), overall survival (OS), admission to ICU, ICU LOS, and ICU mortality. The results showed that both NLR and BLR were significant but not independent prognostic factors for in-hospital mortality; NLR was negatively correlated with hospital LOS while ELR was positively correlated with hospital LOS; both increased NLR and increased BLR were associated with reduced OS, while increased ELR was associated with improved OS; increased PLR, NLR, MLR, and BLR were all correlated with elevated ICU admission rates, while increased ELR was correlated with a reduced ICU admission rate; ELR was positively correlated with ICU LOS; both higher NLR and higher BLR were associated with increased ICU mortality. In summary, NLR and BLR were useful prognostic factors for clinical outcomes in patients with SCAP.

Prognostic utility of paraspinal muscle index in elderly patients with community-acquired pneumonia

OBJECTIVE

This study investigated the associations between paraspinal muscle measurements on chest computed tomography and clinical outcomes of elderly patients with community-acquired pneumonia (CAP).

METHODS

This single-center, retrospective, observational study analyzed elderly patients (≥65 years) with CAP hospitalized through an emergency department between March 2020 and December 2022. We collected their baseline characteristics and laboratory data at the time of admission. The paraspinal muscle index and attenuation were calculated at the level of the 12th thoracic vertebra using chest computed tomography taken within 48 hours before or after admission. Univariable and multivariable logistic regression analyses were conducted to evaluate the association between paraspinal muscle measurements and 28-day mortality. Receiver operating characteristic (ROC) curve and area under the curve (AUC) analyses were used to evaluate the prognostic predictive power.

RESULTS

Of the 338 enrolled patients, 60 (17.8%) died within 28 days after admission. A high paraspinal muscle index was associated with low 28-day mortality in elderly patients with CAP (adjusted odds ratio, 0.994; 95% confidence interval, 0.992-0.997). The area under the ROC curve for the muscle index was 0.75, which outperformed the pneumonia severity index and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥65 years) metric, both of which showed an AUC of 0.64 in predicting mortality.

CONCLUSION

A high paraspinal muscle index was associated with low 28-day mortality in patients aged 65 years or older with CAP.

Novel pneumonia score based on a machine learning model for predicting mortality in pneumonia patients on admission to the intensive care unit

BACKGROUND

Scores for predicting the long-term mortality of severe pneumonia are lacking. The purpose of this study is to use machine learning methods to develop new pneumonia scores to predict the 1-year mortality and hospital mortality of pneumonia patients on admission to the intensive care unit (ICU).

METHODS

The study population was screened from the MIMIC-IV and eICU databases. The main outcomes evaluated were 1-year mortality and hospital mortality in the MIMIC-IV database and hospital mortality in the eICU database. From the full data set, we separated patients diagnosed with community-acquired pneumonia (CAP) and ventilator-associated pneumonia (VAP) for subgroup analysis. We used common shallow machine learning algorithms, including logistic regression, decision tree, random forest, multilayer perceptron and XGBoost.

RESULTS

The full data set of the MIMIC-IV database contained 4697 patients, while that of the eICU database contained 13760 patients. We defined a new pneumonia score, the "Integrated CCI-APS", using a multivariate logistic regression model including six variables: metastatic solid tumor, Charlson Comorbidity Index, readmission, congestive heart failure, age, and Acute Physiology Score III. The area under the curve (AUC) and accuracy of the integrated CCI-APS were assessed in three data sets (full, CAP, and VAP) using both the test set derived from the MIMIC-IV database and the external validation set derived from the eICU database. The AUC value ranges in predicting 1-year and hospital mortality were 0.784-0.797 and 0.691-0.780, respectively, and the corresponding accuracy ranges were 0.723-0.725 and 0.641-0.718, respectively.

CONCLUSIONS

The main contribution of this study was a benchmark for using machine learning models to build pneumonia scores. Based on the idea of integrated learning, we propose a new integrated CCI-APS score for severe pneumonia. In the prediction of 1-year mortality and hospital mortality, our new pneumonia score outperformed the existing score.

Interpretations of the Role of Plasma Albumin in Prognostic Indices: A Literature Review

This review assesses how publications interpret factors that influence the serum or plasma albumin (PA) level in prognostic indices, focusing on inflammation and nutrition. On PubMed, a search for "albumin AND prognosis" yielded 23,919 results. From these records, prognostic indices were retrieved, and their names were used as search strings on PubMed. Indices found in 10 or more original research articles were included. The same search strings, restricted to "Review" or "Systematic review", retrieved yielded on the indices. The data comprised the 10 latest original research articles and up to 10 of the latest reviews. Thirty indices had 294 original research articles (6 covering two indices) and 131 reviews, most of which were from recent years. A total of 106 articles related the PA level to inflammation, and 136 related the PA level to nutrition. For the reviews, the equivalent numbers were 54 and 65. In conclusion, more publications mention the PA level as a marker of nutrition rather than inflammation. This is in contrast to several general reviews on albumin and nutritional guidelines, which state that the PA level is a marker of inflammation but not nutrition. Hypoalbuminemia should prompt clinicians to focus on the inflammatory aspects in their patients.

Skeletal muscle depletion predicts death in severe community-acquired pneumonia patients entering ICU

BACKGROUND

Sarcopenia, or skeletal muscle depletion, was common in the elderly and often led to a poor prognosis of diseases. The area of the psoas muscle in abdominal computed tomography (CT) is the most common used for diagnosing sarcopenia. However, patients with pneumonia routinely only undergo chest CT.

OBJECTIVES

This study aimed to determine whether paraspinal muscle area (PMA) obtained by chest CT can predict death for community-acquired pneumonia (SCAP) patients entering intensive care unit (ICU).

METHODS

This study enrolled 208 SCAP patients admitted to ICU after undergoing chest CT. PMA, paraspinal muscle radiodensity (PMD), and lean paraspinal muscle area (LPMA) were calculated on chest CT images. The main outcome was mortality during hospitalization. Logistic regression, receiver operating characteristic (ROC) curve, and Kaplan-Meier curves were used to evaluate forecasting effectiveness.

RESULTS

The primary outcome occurred in 76 (36.53%) patients. In multivariate logistic regression, PMA, lactic dehydrogenase (LDH), invasive mechanical ventilation (IMV), red blood cell (RBC) and age≥ 65 years were independent risk factors predicting death during hospitalization (adjusted Odds Ratio [OR]: 0.886, 1.002, 3.178, 0.612 and 2.003, respectively). The area under curve (AUC) of PMA to predict death was 0.720 (P< 0.001). During hospitalization, the median survival time of high-PMA (51.00 days) and low-PMA groups (20.00 days) was statistically significant (P< 0.001).

CONCLUSION

Lower PMA was associated with an increased risk of death for SCAP patients admitted to the ICU. In other words, PMA may help early identify adverse prognosis of SCAP patients admitted to ICU.

Urea-to-Albumin Ratio and In-Hospital Mortality in Severe Pneumonia Patients

Objective

The urea-to-albumin ratio (UAR), as a new marker of the systemic inflammatory response, is associated with the mortality in pneumonia patients. However, the association between the UAR and in-hospital mortality in severe pneumonia (SP) has received little attention.

Methods

In this single-center retrospective cohort study, 212 SP patients in intensive care unit (ICU) from June 1, 2016, to June 1st, 2020, with baseline UAR were enrolled. The primary outcome was in-hospital mortality. The association of UAR with in-hospital mortality was assessed using a multivariable-adjusted Cox model.

Results

Of 212 patients, the median age was 73.0 (61.0, 82.8) years, 70.8% of patients were male, and the APACHE II score was 20.0 (16.0, 26.0). During the hospital period, 101 (47.6%) patients died. In-hospital mortality rates for the lower and higher UAR were 16 (27.6%) and 85 (55.2%), respectively (P < 0.001). Kaplan–Meier analysis revealed that survival rates were significantly different between the two groups (log rank = 13.71, P < 0.001). After adjusted for confounding factors, the higher UAR group was significantly associated with a hazard ratio (HR) for in-hospital mortality of 2.234 (95% confidence interval: 1.146–4.356, P=0.018). Besides, this pattern persisted in subgroup analyses considering sex (HR = 9.380; 95% CI: 2.248–39.138; P=0.002).

Conclusions

Higher UAR levels at the commencement of admission to ICU may be independently associated with increased in-hospital mortality in SP patients.

Systematic review and meta-analysis of the safety of erythromycin compared to clarithromycin in adults and adolescents with pneumonia

Macrolides are recommended for the treatment of community-acquired pneumonia (CAP). It is debatable whether erythromycin is associated with more adverse drug reactions (ADRs) compared to clarithromycin, and both are recommended in clinical practice guidelines. This meta-analysis aim is to compare ADRs in CAP patients treated with erythromycin versus clarithromycin. Two investigators independently searched PubMed, EMBASE and Cochrane Library databases through Feb 07, 2019. Randomized-controlled trials (RCTs) comparing ADRs of monotherapy with erythromycin versus with clarithromycin in adults or adolescents with CAP were included. We estimated risk ratios (RRs) with 95% confidence intervals (CIs) using random-effects models and evaluated heterogeneity (I²). Bias risk was assessed using the Cochrane risk of bias tool for RCTs. Five RCTs (total of 693 patients) were included. A significantly higher discontinuation rate due to ADRs was found with erythromycin compared with clarithromycin (RR, 4.347; 95% CI, 2.506-7.539; p < 0.001; I²=0%). Overall, ADRs occurred more significantly with erythromycin compared with clarithromycin (RR, 1.773; 95% CI, 1.423-2.209; p < 0.001; I²=0%). Gastrointestinal (GI) ADRs were higher with erythromycin (RR, 2.678; 95% CI, 1.791-4.006; p < 0.001; I²=5.835%). Restriction of analyses to double-blind RCTs did not change our findings. Based on meta-analysis of RCTs in adults and adolescents with CAP, erythromycin results in more overall ADRs and GI ADRs, as well as a higher rate of discontinuation due to ADRs. Therefore, given that erythromycin is not more effective than clarithromycin, erythromycin should not be selected unless other macrolides cannot be used.

Hot topics and current controversies in community-acquired pneumonia

Community-acquired pneumonia (CAP) is one of the most common infectious diseases, as well as a major cause of death both in developed and developing countries, and it remains a challenge for physicians around the world. Several guidelines have been published to guide clinicians in how to diagnose and take care of patients with CAP. However, there are still many areas of debate and uncertainty where research is needed to advance patient care and improve clinical outcomes. In this review we highlight current hot topics in CAP and present updated evidence around these areas of controversy.

Community-acquired pneumonia is the most frequent cause of infectious death worldwide; however, there are several areas of controversy that should be addressed to improve patient care. This review presents the available data on these topics.http://bit.ly/2ShnH7A

Utility of community-acquired pneumonia severity scores in guiding disposition from the emergency department: Intensive care or short-stay unit?

OBJECTIVE

To assess community-acquired pneumonia severity scores from two perspectives: (i) prediction of ICU admission or mortality; and (ii) utility of low scores for prediction of discharge within 48 h, potentially indicating suitability for short-stay unit admission.

METHODS

Patients with community-acquired pneumonia were identified from a prospective database of emergency patients admitted with infection. Pneumonia severity index (PSI), CURB-65, CORB, CURXO, SMARTCOP scores and the Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS) minor criteria were calculated. Diagnostic accuracy statistics (sensitivity, specificity, predictive values, likelihood ratios and area under receiver operating characteristic curves [AUROC]) were determined for both end-points.

RESULTS

Of 618 patients admitted with community-acquired pneumonia judged eligible for invasive therapies, 75 (12.1%) were admitted to ICU or deceased at 30 days, and 87 (14.1%) were discharged within 48 h. All scores effectively stratified patients into categories of risk. For prediction of severe pneumonia, SMARTCOP, CURXO and IDSA/ATS discriminated well (AUROC 0.84-0.87). SMARTCOP and CURXO showed optimal sensitivity (85% [95% confidence interval (CI) 75-92]), while specificity was highest for CORB and CURB-65 (93% and 94%, respectively). Using lowest risk categories for prediction of discharge within 48 h, only SMARTCOP and CURXO showed specificity >80%. PSI demonstrated highest positive predictive value (31% [95% CI 24-39]) and AUROC (0.74 [95% CI 0.69-0.79]).

CONCLUSIONS

Community-acquired pneumonia severity scores had different strengths; SMARTCOP and CURXO were sensitive with potential to rule out severe disease, while the high specificity of CORB and CURB-65 facilitated identification of patients at high risk of requirement for ICU. Low severity scores were not useful to identify patients suitable for admission to short-stay units.

Development of a Risk Tool to Support Discussions of Care for Older Adults Admitted to the ICU With Pneumonia

BACKGROUND

Early, data-driven discussion surrounding palliative care can improve care delivery and patient experience.

OBJECTIVE

To develop a 30-day mortality prediction tool for older patients in intensive care unit (ICU) with pneumonia that will initiate palliative care earlier in hospital course.

DESIGN

Retrospective Electronic Health Record (EHR) review.

SETTING

Four urban and suburban hospitals in a Western New York hospital system.

PARTICIPANTS

A total of 1237 consecutive patients (>75 years) admitted to the ICU with pneumonia from July 2011 to December 2014.

MEASUREMENTS

Data abstracted included demographics, insurance type, comorbidities, and clinical factors. Thirty-day mortality was also determined. Logistic regression identified predictors of 30-day mortality. Area under the receiver operating curve (ROC) was calculated to quantify the degree to which the model accurately classified participants. Using the coordinates of the ROC, a predicted probability was identified to indicate high risk.

RESULTS

A total of 1237 patients were included with 30-day mortality data available for 100% of patients. The mortality rate equaled 14.3%. Age >85 years, having active cancer, Congestive Heart Failure (CHF), Chronic Obstructive Pulmonary Disease (COPD), sepsis, and being on a vasopressor all predicted mortality. Using the derived index, with a predicted probability of mortality >0.146 as a cutoff, sensitivity equaled 70.6% and specificity equaled 65.6%. The area under the ROC was 0.735.

CONCLUSION

Our risk tool can help care teams make more informed decisions among care options by identifying a patient group for whom a careful review of goals of care is indicated both during and after hospitalization. External validation and further refinement of the index with a larger sample will improve prognostic value.

Factors affecting treatment success in community-acquired pneumonia

BACKGROUND/AIM

Treatment failure in hospitalized patients with community-acquired pneumonia is a major cause of mortality. The aim of this study was to evaluate the factors affecting treatment success in community-acquired pneumonia.

MATERIALS AND METHODS

A total of 537 patients (mean age: 66.1 ± 15.8 years, 365 males) registered to the Turkish Thoracic Society Pneumonia Database were analyzed. Of these, clinical improvement or cure, defined as treatment success, was achieved in 477, whereas 60 patients had treatment failure and/or died.

RESULTS

Lower numbers of neutrophils (5989.9 ± 6237.3 vs. 8495.6 ± 7279.5/mm³), higher blood urea levels (66.1 ± 42.1 vs. 51.2 ± 38.2 mg/dL), higher Pneumonia Severity Index (PSI) scores (123.3 ± 42.6 vs. 96.3 ± 32.9), higher CURB-65 scores (2.7 ± 1.2 vs. 2.2 ± 0.9), lower PaO₂/FiO₂ ratios (216.3 ± 86.8 vs. 269.9 ± 65.6), and the presence of multilobar (33.3% vs. 16.4%) and bilateral (41.7% vs. 18.9%) radiologic infiltrates were related to treatment failure. The PSI score and PaO₂/FiO₂ ratio were independent parameters affecting treatment results in multivariate linear regression analysis (P < 0.001).

CONCLUSION

The risk of treatment failure is high in patients with severe pneumonia and with respiratory failure. Effective treatment and close monitoring are required for these cases.

Procalcitonin in patients with influenza A (H1N1) infection and acute respiratory failure

OBJECTIVE

To verify serum procalcitonin levels of patients with acute respiratory failure secondary to influenza A (H1N1) upon their admission to the Intensive Care Unit and to compare these results to values found in patients with sepsis and trauma admitted to the same unit.

METHODS

Analysis of records of patients infected with influenza A (H1N1) and respiratory failure admitted to the General Intensive Care Unit during in a period of 60 days. The values of serum procalcitonin and clinical and laboratory data were compared to those of all patients admitted with sepsis or trauma in the previous year.

RESULTS

Among patients with influenza A (H1N1) (n = 16), the median serum procalcitonin level upon admission was 0.11 ng/mL, lower than in the sepsis group (p < 0.001) and slightly lower than in trauma patients. Although the mean values were low, serum procalcitonin was a strong predictor of hospital mortality in patients with influenza A (H1N1).

CONCLUSION

Patients with influenza A (H1N1) with severe acute respiratory failure presented with low serum procalcitonin values upon admission, although their serum levels are predictors of hospital mortality. The kinetics study of this biomarker may be a useful tool in the management of this group of patients.

Severe pneumonia in intensive care: cause, diagnosis, treatment and management: a review of the literature

PURPOSE OF REVIEW

Severe pneumonia is a common disease that intensive care physicians have to face. The review highlights recent findings about microbiology, diagnosis and treatment, including the management of critically ill patients with severe respiratory failure.

RECENT FINDINGS

Epidemiological and clinical risk factors strongly influence microbiological cause in patients with severe pneumonia. In addition to typical respiratory pathogens, less common microrganisms and multidrug-resistant (MDR) germs may cause severe lung infections. New molecular diagnostic techniques appear promising for early detection of microbes involved in severe pneumonia. Antimicrobials remain the mainstay of causative severe pneumonia treatment and the optimization of antibiotic therapy may be obtained by applying their pharmacodynamic/pharmacokinetic properties. Several new strategies have been implemented for the management of acute respiratory failure (ARF) due to severe pneumonia; however, their extensive clinical application is limited by the need for well trained physicians and adequate hospital centers.

SUMMARY

Despite advancements in antibiotic and life-supportive treatments, severe pneumonia remains a leading cause of intensive care unit (ICU) admission and death. Prompt and appropriate antimicrobial therapy is essential. The use of new nonconventional strategies for ARF management might be effective in more severe patients.

Retrospective epidemiological study for the characterization of community- acquired pneumonia and pneumococcal pneumonia in adults in a well-defined area of Badalona (Barcelona, Spain)

Background

Community-acquired pneumonia (CAP) has large impact on direct healthcare costs, especially those derived from hospitalization. This study determines impact, clinical characteristics, outcome and economic consequences of CAP in the adult (≥18 years) population attended in 6 primary-care centers and 2 hospitals in Badalona (Spain) over a two-year period.

Methods

Medical records were identified by codes from the International Classification of Diseases in databases (January 1^st 2008-December 31^st 2009).

Results

A total of 581 patients with CAP (55.6% males, mean age 57.5 years) were identified. Prevalence: 0.64% (95% CI: 0.5%-0.7%); annual incidence: 3.0 cases/1,000 inhabitants (95% CI: 0.2-0.5). Up to 241 (41.5%) required hospitalization. Hospital admission was associated (p<0.002) with liver disease (OR=5.9), stroke (OR=3.6), dementia (OR=3.5), COPD (OR=2.9), diabetes mellitus (OR=1.9) and age (OR=1.1 per year). Length of stay (4.4±0.3 days) was associated with PSI score (β=0.195), in turn associated with age (r=0.827) and Charlson index (r=0.497). Microbiological tests were performed in all inpatients but only in 35% outpatients. Among patients with microbiological tests, results were positive in 51.7%, and among them, S pneumoniae was identified in 57.5% cases. Time to recovery was 29.9±17.2 days. Up to 7.5% inpatients presented complications, 0.8% required ICU admission and 19.1% readmission. Inhospital mortality rate was 2.5%. Adjusted mean total cost was €2,332.4/inpatient and €698.6/outpatient (p<0.001). Patients with pneumococcal CAP (n=107) showed higher comorbidity and hospitalization (76.6%), higher PSI score, larger time to recovery and higher overall costs among inpatients.

Conclusions

Strategies preventing CAP, thus reducing hospital admissions could likely produce substantial costs savings in addition to the reduction of CAP burden.

Year in review 2011: Critical Care - respirology

Management of acute respiratory failure is an important component of intensive care. In this review, we analyze 21 original research articles published last year in Critical Care in the field of respiratory and critical care medicine. The articles are summarized according to the following topic categories: acute respiratory distress syndrome, mechanical ventilation, adjunctive therapies, and pneumonia.

Defining severe pneumonia

Pneumonia is an important clinical and public health problem. Identification and prediction of severe pneumonia are significant concerns. Attempts to define severe pneumonia should recognize that different purposes are served by different definitions; no single definition meets all needs. At present, several prediction models have been proposed or validated. Biomarkers are not yet ready for routine use. The authors recommend careful consideration of the implications of any given definition of pneumonia severity. Outcome studies are needed to integrate human and health care system factors with the application of pneumonia severity definitions.