Two-year survival after scheduled extubation in patients with pneumonia or ARDS: a prospective observational study.

PURPOSE: To report two-year survival after scheduled extubation in patients with pneumonia or acute respiratory distress syndrome (ARDS). METHODS: This was a prospective observational study performed in a respiratory ICU of a teaching hospital. Pneumonia or ARDS patients who successfully completed a spontaneous breathing trial were enrolled. Data were collected before extubation. Patients were followed up to two years by phone every 3 months. RESULTS: A total of 230 patients were enrolled in final analysis. One-, 3-, 6-, 12-, and 24-month survival was 77.4%, 63.8%, 61.3%, 57.8%, and 47.8%, respectively. Cox regression shows that Charlson comorbidity index (hazard ratio: 1.20, 95% confidence interval: 1.10-1.32), APACHE II score before extubation (1.11, 1.05-1.17), cough peak flow before extubation (0.993, 0.986-0.999), and extubation failure (3.96, 2.51-6.24) were associated with two-year mortality. To predict death within two years, the area under the curve of receiver operating characteristic was 0.79 tested by Charlson comorbidity index, 0.75 tested by APACHE II score, and 0.75 tested by cough peak flow. Two-year survival was 31% and 77% in patients with Charlson comorbidity index ≥ 1 and < 1, 28% and 62% in patients with APACHE II score ≥ 12 and < 12, and 64% and 17% in patients with cough peak flow > 58 and ≤ 58 L/min, respectively. CONCLUSIONS: Comorbidity, disease severity, weak cough and extubation failure were associated with increased two-year mortality in pneumonia or ARDS patients who experienced scheduled extubation. It provides objective information to caregivers to improve decision-making process during hospitalization and post discharge.

Performance of risk scores in predicting mortality at 3, 6, and 12 months in patients diagnosed with community-acquired pneumonia.

BACKGROUND: Risk scores (RS) evaluate the likelihood of short-term mortality in patients diagnosed with community-acquired pneumonia (CAP). However, there is a scarcity of evidence to determine the risk of long-term mortality. This article aims to compare the effectiveness of 16 scores in predicting mortality at three, six, and twelve months in adult patients with CAP. METHODS: A retrospective cohort study on individuals diagnosed with CAP was conducted across two hospitals in Colombia. Receiver Operating Characteristic (ROC) curves were constructed at 3, 6, and 12 months to assess the predictive ability of death for the following scoring systems: CURB-65, CRB-65, SCAP, CORB, ADROP, NEWS, Pneumonia Shock, REA-ICU, PSI, SMART-COP, SMRT-CO, SOAR, qSOFA, SIRS, CAPSI, and Charlson Comorbidity Index (CCI). RESULTS: A total of 3688 patients were included in the final analysis. Mortality at 3, 6, and 12 months was 5.2%, 8.3%, and 16.3% respectively. At 3 months, PSI, CCI, and CRB-65 scores showed ROC curves of 0.74 (95% CI: 0.71-0.77), 0.71 (95% CI: 0.67-0.74), and 0.70 (95% CI: 0.66-0.74). At 6 months, PSI and CCI scores showed performances of 0.74 (95% CI: 0.72-0.77) and 0.72 (95% CI: 0.69-0.74), respectively. Finally at 12 months, all evaluated scores showed poor discriminatory capacity, including PSI, which decreased from acceptable to poor with an ROC curve of 0.64 (95% CI: 0.61-0.66). CONCLUSION: When predicting mortality in patients with CAP, at 3 months, PSI, CCI, and CRB-65 showed acceptable predictive performances. At 6 months, only PSI and CCI maintained acceptable levels of accuracy. For the 12-month period, all evaluated scores exhibited very limited discriminatory ability, ranging from poor to almost negligible.

Development and verification of a prediction model for outcomes of elderly patients with nursing home-acquired pneumonia.

BACKGROUND: Among all infections in nursing homes, pneumonia has the highest mortality. Nurses have a 24-h relationship with patients and have a key role in identifying and preventing adverse outcomes. However, tools to engage nurses in pneumonia patient outcomes evaluation have not occurred. PURPOSE: This study aimed to develop and validate a prediction model to predict the outcome of elderly patients with nursing home-acquired pneumonia (NHAP). METHODOLOGY: A retrospective observational study was conducted with 219 elderly NHAP patients. Baseline characteristics, health history, and treatment/nursing status were collected. Variables for constructing nomograms were screened by univariate and multivariate analysis. The nomogram model was evaluated using the concordance index (C-index), decision curve analysis (DCA) curves, and receiver operating characteristic (ROC) curves. RESULTS: 9 independent risk factors were identified and assembled into the nomogram. The nomogram exhibited reasonably accurate discrimination (area under the receiver operating characteristic curve (AUC-ROC): 0.931, P < 0.05) and calibration (C-index: 0.931, 95 % CI: 0.898-0.964) in the validation cohort. DCA and clinical impact curves demonstrated that the nomogram was clinically beneficial. CONCLUSIONS: A visualization nomogram model was successfully established for predicting the outcome of the NHAP elderly patients. The model has extremely high reliability, extremely high predictive ability, and good clinical applicability.

Cluster analysis of thoracic muscle mass using artificial intelligence in severe pneumonia.

Severe pneumonia results in high morbidity and mortality despite advanced treatments. This study investigates thoracic muscle mass from chest CT scans as a biomarker for predicting clinical outcomes in ICU patients with severe pneumonia. Analyzing electronic medical records and chest CT scans of 778 ICU patients with severe community-acquired pneumonia from January 2016 to December 2021, AI-enhanced 3D segmentation was used to assess thoracic muscle mass. Patients were categorized into clusters based on muscle mass profiles derived from CT scans, and their effects on clinical outcomes such as extubation success and in-hospital mortality were assessed. The study identified three clusters, showing that higher muscle mass (Cluster 1) correlated with lower in-hospital mortality (8% vs. 29% in Cluster 3) and improved clinical outcomes like extubation success. The model integrating muscle mass metrics outperformed conventional scores, with an AUC of 0.844 for predicting extubation success and 0.696 for predicting mortality. These findings highlight the strong predictive capacity of muscle mass evaluation over indices such as APACHE II and SOFA. Using AI to analyze thoracic muscle mass via chest CT provides a promising prognostic approach in severe pneumonia, advocating for its integration into clinical practice for better outcome predictions and personalized patient management.

[Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning].

OBJECTIVE: To predict the risk of in-hospital death in patients with chronic heart failure (CHF) complicated by lung infections using interpretable machine learning. METHODS: The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database. According to the pathogen type, the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups, and their risks of in-hospital death were compared using Kaplan-Meier survival curves. Univariate analysis and LASSO regression were used to select the features for constructing LR, AdaBoost, XGBoost, and LightGBM models, and their performance was compared in terms of accuracy, precision, F1 value, and AUC. External validation of the models was performed using the data from eICU-CRD database. SHAP algorithm was applied for interpretive analysis of XGBoost model. RESULTS: Among the 4 constructed models, the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set. In the external test set, the XGBoost model had an AUC of 0.691 (95% CI: 0.654-0.720) in bacterial pneumonia group and an AUC of 0.725 (95% CI: 0.577-0.782) in non-bacterial pneumonia group, and showed better predictive ability and stability than the other models. CONCLUSION: The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections. The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.

MALAT1 predicts the prognosis of severe community-acquired pneumonia in pediatric patients.

BACKGROUND: To evaluate the role of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in the prognosis of severe community-acquired pneumonia (CAP) in children. METHODS: According to the median MALAT1 value of 3.2 at baseline, 93 pediatric patients with severe CAP were divided into low (n = 46, median MALAT1 level = 1.9) or high (n = 47, median MALAT1 level = 4.5) MALAT1 groups. Another 93 age-, gender-, and body mass index (BMI)-matched healthy individuals were included in the control group using the propensity-score matching (PSM) method. A multivariate Cox proportional hazards model was used to explore the association of MALAT1 level with the 28-day mortality after controlling for potential confounding factors. RESULTS: The MALAT1 expressions were significantly higher in the patients with severe CAP compared with those in the healthy controls (3.2 vs. 0.9, P < 0.01). The receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) was 0.927 when the cut-off value of MALAT1 was 1.5. Moreover, the MALAT1 expressions were substantially lower in survivals than non-survivals (3.8 vs. 2.6, P < 0.01), and the multivariate Cox regression analysis indicated a positive association between MALAT1 levels and mortality risk (HR = 3.32; 95% CI: 1.05-10.47; P = 0.04). CONCLUSION: MALAT1 might be a promising marker for predicting the prognosis of severe CAP in pediatric patients.

Risk factors at admission of in-hospital dysglycemia, mortality, and readmissions in patients with type 2 diabetes and pneumonia.

AIMS: In-hospital dysglycemia is associated with adverse outcomes. Identifying patients at risk of in-hospital dysglycemia early on admission may improve patient outcomes. METHODS: We analysed 117 inpatients admitted with pneumonia and type 2 diabetes monitored by continuous glucose monitoring. We assessed potential risk factors for in-hospital dysglycemia and adverse clinical outcomes. RESULTS: Time in range (3.9-10.0 mmol/l) decreased by 2.9 %-points [95 % CI 0.7-5.0] per 5 mmol/mol [2.6 %] increase in admission haemoglobin A1c, 16.2 %-points if admission diabetes therapy included insulin therapy [95 % CI 2.9-29.5], and 2.4 %-points [95 % CI 0.3-4.6] per increase in the Charlson Comorbidity Index (CCI) (integer, as a measure of severity and amount of comorbidities). Thirty-day readmission rate increased with an IRR of 1.24 [95 % CI 1.06-1.45] per increase in CCI. In-hospital mortality risk increased with an OR of 1.41 [95 % CI 1.07-1.87] per increase in Early Warning Score (EWS) (integer, as a measure of acute illness) at admission. CONCLUSIONS: Dysglycemia among hospitalised patients with pneumonia and type 2 diabetes was associated with high haemoglobin A1c, insulin treatment before admission, and the amount and severity of comorbidities (i.e., CCI). Thirty-day readmission rate increased with high CCI. The risk of in-hospital mortality increased with the degree of acute illness (i.e., high EWS) at admission. Clinical outcomes were independent of chronic glycemic status, i.e. HbA1c, and in-hospital glycemic status.

Loss-of-function/gain-of-function polymorphisms of the ATP sensitive P2X7R influence sepsis, septic shock, pneumonia, and survival outcomes.

Introduction: Extracellular ATP (eATP) released from damaged cells activates the P2X7 receptor (P2X7R) ion channel on the surface of surrounding cells, resulting in calcium influx, potassium efflux and inflammasome activation. Inherited changes in the P2X7R gene (P2RX7) influence eATP induced responses. Single nucleotide polymorphisms (SNPs) of P2RX7 influence both function and signaling of the receptor, that in addition to ion flux includes pathogen control and immunity. Methods: Subjects (n = 105) were admitted to the ICU at the University Hospital Ulm, Germany between June 2018 and August 2019. Of these, subjects with a diagnosis of sepsis (n = 75), were also diagnosed with septic shock (n = 24), and/or pneumonia (n = 42). Subjects with pneumonia (n = 43) included those without sepsis (n = 1), sepsis without shock (n = 29) and pneumonia with septic shock (n = 13). Out of the 75 sepsis/septic shock patients, 33 patients were not diagnosed with pneumonia. Controls (n = 30) were recruited to the study from trauma patients and surgical patients without sepsis, septic shock, or pneumonia. SNP frequencies were determined for 16 P2RX7 SNPs known to affect P2X7R function, and association studies were performed between frequencies of these SNPs in sepsis, septic shock, and pneumonia compared to controls. Results: The loss-of-function (LOF) SNP rs17525809 (T253C) was found more frequently in patients with septic shock, and non-septic trauma patients when compared to sepsis. The LOF SNP rs2230911 (C1096G) was found to be more frequent in patients with sepsis and septic shock than in non-septic trauma patients. The frequencies of these SNPs were even higher in sepsis and septic patients with pneumonia. The current study also confirmed a previous study by our group that showed a five SNP combination that included the GOF SNPs rs208294 (C489T) and rs2230912 (Q460R) that was designated #21211 was associated with increased odds of survival in severe sepsis. Discussion: The results found an association between expression of LOF P2RX7 SNPs and presentation to the ICU with sepsis, and septic shock compared to control ICU patients. Furthermore, frequencies of LOF SNPs were found to be higher in sepsis patients with pneumonia compared to those without pneumonia. In addition, a five SNP GOF combination was associated with increased odds of survival in severe sepsis. These results suggest that P2RX7 is required to control infection in pneumonia and that inheritance of LOF variants increases the risk of sepsis when associated with pneumonia. This study confirms that P2RX7 genotyping in pneumonia may identify patients at risk of developing sepsis. The study also identifies P2X7R as a target in sepsis associated with an excessive immune response in subjects with GOF SNP combinations.

Comparison of NEWS2 and PSI as mortality predictors in patients with community acquired pneumonia.

In the West, National Early Warning Score 2 (NEWS2) is commonly applied to predict the severity of illness using only bedside variables unlike the extensive Pneumonia Severity Index (PSI). The objective of this study was to compare these scores as mortality predictors in patients admitted with community acquired pneumonia (CAP). This cross-sectional study was conducted in Jinnah Postgraduate Medical Centre, Karachi, Pakistan, for six months in 2020 on 116 patients presenting with CAP. Cases of aspiration pneumonia, hospital acquired pneumonia, pulmonary tuberculosis, pulmonary embolism, and pulmonary oedema were excluded. In-hospital mortality was taken as the outcome of this study. The mean age of the participants was 46.9±20.5 years. The in-hospital mortalities were 45(38.8%). NEWS2 was 97.8% sensitive but only 15.5% specific in predicting the outcome, whereas PSI was less sensitive (68.9%) but more specific (50.7%), which showed that in comparison with PSI, NEWS2 is a more sensitive mortality predicting score among hospitalised CAP patients.

Clinical characteristics and risk factors for mortality in pneumonia-associated acute respiratory distress syndrome patients: a single center retrospective cohort study.

Background: Pathogenic diversity may have contributed to the high mortality of pneumonia-associated acute respiratory distress syndrome (p-ARDS). Metagenomics next-generation sequencing (mNGS) serves as a valuable diagnostic tool for early pathogen identification. However, its clinical utility in p-ARDS remains understudied. There are still limited researches on the etiology, clinical characteristics and risk factors for 28-day mortality in p-ARDS patients. Methods: A single center retrospective cohort study of 75 p-ARDS patients was conducted. Patients were categorized into survival and deceased groups based on their 28-day outcomes. A comprehensive clinical evaluation was conducted, including baseline characteristics, laboratory indicators, outcomes and pathogen identification by mNGS and traditional microbiological testing. We then evaluated the diagnostic value of mNGS and identified clinical characteristics and risk factors for 28-day mortality in p-ARDS. Result: The overall ICU mortality was 26.67%, and the 28-day mortality was 57.33%, with 32 cases (42.67%) in the survival group, and 43 cases (57.33%) in the deceased group. Patients in the deceased group were older than those in the survival group (68(59,73) years vs. 59(44,67) years, P=0.04). The average lengths of ICU and hospital stay were 9(5,13) days and 14(7,21) days, respectively. The survival group had longer lengths of ICU and hospital stay (ICU: 11(7,17) days and hospital: 17(9,27) days) compared to the deceased group (ICU: 8(4,11) days and hospital: 12(6,19) days) (P<0.05). Survival patients exhibited lower Acute Physiology and Chronic Health Evaluation (APACHE) II score on the 3rd and 7th days, higher lymphocyte counts, higher CD3+ and CD8+ T cell counts compared to deceased patients (P<0.05). Multivariate logistic regression analysis identified age, APACHE II scores on 3rd and 7th days, CD8+ T cell count and length of ICU as independent risk factors for 28-day mortality in p-ARDS patients. mNGS demonstrated a significantly higher overall pathogen detection rate (70/75, 93.33%) compared to the traditional method (50/75, 66.67%, P=0.022). The average turnaround time (TAT) for mNGS was significantly shorter at 1(1,1) day compared to 4(3,5) days for the traditional method (P<0.001). Conclusion: Metagenome next-generation sequencing can be used as a valuable tool for identifying pathogens in p-ARDS, reducing diagnostic time and improving accuracy. Early application of mNGS alongside traditional methods is recommended for p-ARDS. Furthermore, older age, higher APACHE II scores, lower lymphocyte counts and lymphocyte subset counts were associated with increased mortality in p-ARDS patients, highlighting the importance of timely assessment of immune status and disease severity, especially in elderly.

Association between glucose levels at admission and outcomes of pneumonia: a systematic review and meta-analysis.

BACKGROUND: Elevated blood glucose at hospital admission is frequently observed and has been associated with adverse outcomes in various patient populations. This meta-analysis sought to consolidate existing evidence to assess the association between elevated blood glucose at admission and clinical outcomes amongst pneumonia patients. METHODS: We searched PubMed, Medline, Cochrane library, Web of Science (WoS), and Scopus databases for studies, published up to 31 August 2023, and reporting on the clinical outcomes and the blood glucose levels at admission. Data were extracted by two independent reviewers. Random-effects meta-analyses were used to pool odds ratios (ORs) with 95% confidence intervals (CI) for dichotomous outcomes and weighted mean differences (WMDs) for continuous outcomes. RESULTS: A total of 23 studies with 34,000 participants were included. Elevated blood glucose at admission was significantly associated with increased short-term (pooled OR: 2.67; 95%CI: 1.73-4.12) and long-term mortality (pooled OR: 1.70; 95%CI: 1.20-2.42). Patients with raised glucose levels were more likely to require ICU admission (pooled OR: 1.86; 95%CI: 1.31-2.64). Trends also suggested increased risks for hospital readmission and mechanical ventilation, though these were not statistically significant. Elevated blood glucose was linked with approximately 0.72 days longer duration of hospital stay. CONCLUSION: Elevated blood glucose level at the time of hospital admission is associated with several adverse clinical outcomes, especially mortality, in patients with pneumonia. These findings underscore the importance of recognizing hyperglycemia as significant prognostic marker in pneumonia patients. Further research is needed to determine whether targeted interventions to control glucose levels can improve these outcomes.

Clinical characteristics and prognostic factors of non-malignant pleural effusions in hospitalised patients: a retrospective cohort study.

OBJECTIVE: Non-malignant pleural effusions (NMPE) are common in hospitalised patients. Data on NMPE inpatients are scarce and the factors influencing the prognosis are unknown. DESIGN: This was a retrospective cohort study. SETTING AND PARTICIPANTS: We conducted a retrospective cohort of inpatients (n=86 645) admitted to the Chinese PLA General Hospital from 2018 to 2021, based on electronic medical records. The observations of 4934 subjects with effusions confirmed by chest radiological tests (CT or X-ray) without a diagnosis of malignancy were followed during admission. Logistic regression was used to analyse organ damage and other factors associated with in-hospital death. Patients were clustered according to their laboratory indicators, and the association between the clustering results and outcomes was studied. OUTCOME: The outcome of this study was in-hospital mortality. RESULTS: Among 4934 patients, heart failure + pneumonia + renal dysfunction was the most common (15.12%) among 100 different diagnostic groups. 318 (6.4%) patients died during hospitalisation. Lung (OR 3.70, 95% CI 2.42 to 5.89), kidney (OR 2.88, 95% CI 2.14 to 3.90) and heart (1.80, 95% CI 1.29 to 2.55) damage were associated with in-hospital mortality. Hierarchical clustering of laboratory indicators (estimated glomerular filtration rate, white blood cell count, platelet count, haemoglobin, N-terminal pro-B-type natriuretic peptide, serum albumin) demonstrated the ability to discriminate patients at high risk of in-hospital death. CONCLUSION: Comorbidities and multiorgan failure are the prominent characteristics of NMPE patients, which increase the risk of in-hospital mortality, and comprehensive intervention for specific comorbidity patterns is suggested.

Development of a new prognostic model to predict pneumonia outcome using artificial intelligence-based chest radiograph results.

This study aimed to develop a new simple and effective prognostic model using artificial intelligence (AI)-based chest radiograph (CXR) results to predict the outcomes of pneumonia. Patients aged > 18 years, admitted the treatment of pneumonia between March 2020 and August 2021 were included. We developed prognostic models, including an AI-based consolidation score in addition to the conventional CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥ 65) and pneumonia severity index (PSI) for predicting pneumonia outcomes, defined as 30-day mortality during admission. A total of 489 patients, including 310 and 179 patients in training and test sets, were included. In the training set, the AI-based consolidation score on CXR was a significant variable for predicting the outcome (hazard ratio 1.016, 95% confidence interval [CI] 1.001-1.031). The model that combined CURB-65, initial O2 requirement, intubation, and the AI-based consolidation score showed a significantly high C-index of 0.692 (95% CI 0.628-0.757) compared to other models. In the test set, this model also demonstrated a significantly high C-index of 0.726 (95% CI 0.644-0.809) compared to the conventional CURB-65 and PSI (p < 0.001 and 0.017, respectively). Therefore, a new prognostic model incorporating AI-based CXR results along with traditional pneumonia severity score could be a simple and useful tool for predicting pneumonia outcomes in clinical practice.

Clinical characteristics and outcomes of community-acquired pneumonia in solid organ transplant recipients.

BACKGROUND: Pneumonia is a frequent complication of solid organ transplantation that adversely impacts both graft and recipient survival. There is a paucity of data on community-acquired pneumonia (CAP) in transplant recipients, particularly the long term outcomes. We conducted a study to compare the clinical characteristics and outcomes of pneumonia in solid organ transplant (SOT) recipients to those in non-transplant (NT) recipients. MATERIAL AND METHODS: Clinical characteristics were abstracted from electronic medical records. Outcomes included time to hospital discharge, short and long-term mortality. Inverse-propensity score weights were assigned to account for between-group differences. Adjusted analysis included a weighted logistic regression. Results were reported as odds ratios with a corresponding 95 % confidence interval (CI). RESULTS: A total of 7449 patients were admitted with CAP. Patients were divided into two groups: SOT recipients 42 (0.56 %) and NT recipients 7396 (99.2 %). SOT recipients were younger, more commonly males, with higher prevalence of comorbidities. After accounting for inverse-propensity score weighting, the odds of mortality were higher in SOT recipients in hospital, at 30 days and at 1 year. The magnitude of increase in mortality for SOT recipients was greatest at 1 year with 1.41 (95 % CI: 1.38-1.44) times higher odds. CONCLUSION: In patients with CAP, SOT recipients are younger, more commonly male and have more co-morbidities compared with NT recipients. They also have higher 1 year mortality after adjustment. Clinicians must be vigilant toward the pronounced long-term mortality risk among these patients and ensure continued follow-up care for them.

A targeted likelihood estimation comparing cefepime and piperacillin/tazobactam in critically ill patients with community-acquired pneumonia (CAP).

Cefepime and piperacillin/tazobactam are antimicrobials recommended by IDSA/ATS guidelines for the empirical management of patients admitted to the intensive care unit (ICU) with community-acquired pneumonia (CAP). Concerns have been raised about which should be used in clinical practice. This study aims to compare the effect of cefepime and piperacillin/tazobactam in critically ill CAP patients through a targeted maximum likelihood estimation (TMLE). A total of 2026 ICU-admitted patients with CAP were included. Among them, (47%) presented respiratory failure, and (27%) developed septic shock. A total of (68%) received cefepime and (32%) piperacillin/tazobactam-based treatment. After running the TMLE, we found that cefepime and piperacillin/tazobactam-based treatments have comparable 28-day, hospital, and ICU mortality. Additionally, age, PTT, serum potassium and temperature were associated with preferring cefepime over piperacillin/tazobactam (OR 1.14 95% CI [1.01-1.27], p = 0.03), (OR 1.14 95% CI [1.03-1.26], p = 0.009), (OR 1.1 95% CI [1.01-1.22], p = 0.039) and (OR 1.13 95% CI [1.03-1.24], p = 0.014)]. Our study found a similar mortality rate among ICU-admitted CAP patients treated with cefepime and piperacillin/tazobactam. Clinicians may consider factors such as availability and safety profiles when making treatment decisions.

In septic shock and CAP, hydrocortisone + fludrocortisone reduced 90-d mortality.

SOURCE CITATION: Heming N, Renault A, Kuperminc E, et al; APROCCHSS investigators and CRICS-TRIGGERSEP network. Hydrocortisone plus fludrocortisone for community acquired pneumonia-related septic shock: a subgroup analysis of the APROCCHSS phase 3 randomised trial. Lancet Respir Med. 2024;12:366-374. 38310918.

Pulmonary inflammation and viral replication define distinct clinical outcomes in fatal cases of COVID-19.

COVID-19 has affected more than half a billion people worldwide, with more than 6.3 million deaths, but the pathophysiological mechanisms involved in lethal cases and the host determinants that determine the different clinical outcomes are still unclear. In this study, we assessed lung autopsies of 47 COVID-19 patients and examined the inflammatory profiles, viral loads, and inflammasome activation. Additionally, we correlated these factors with the patient's clinical and histopathological conditions. Robust inflammasome activation was detected in the lungs of lethal cases of SARS-CoV-2. Experiments conducted on transgenic mice expressing hACE2 and infected with SARS-CoV-2 showed that Nlrp3-/- mice were protected from disease development and lethality compared to Nlrp3+/+ littermate mice, supporting the involvement of this inflammasome in disease exacerbation. An analysis of gene expression allowed for the classification of COVID-19 patients into two different clusters. Cluster 1 died with higher viral loads and exhibited a reduced inflammatory profile than Cluster 2. Illness time, mechanical ventilation time, pulmonary fibrosis, respiratory functions, histopathological status, thrombosis, viral loads, and inflammasome activation significantly differed between the two clusters. Our data demonstrated two distinct profiles in lethal cases of COVID-19, thus indicating that the balance of viral replication and inflammasome-mediated pulmonary inflammation led to different clinical outcomes. We provide important information to understand clinical variations in severe COVID-19, a process that is critical for decisions between immune-mediated or antiviral-mediated therapies for the treatment of critical cases of COVID-19.

Impact of COVID-19 and Non-COVID-19 Hospitalized Pneumonia on Longer-Term Cardiovascular Mortality in People With Type 2 Diabetes: A Nationwide Prospective Cohort Study From Scotland.

OBJECTIVE: In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim to quantify the relative cardiovascular disease (CVD) mortality risks associated with COVID-19 versus non-COVID-19 pneumonia. RESEARCH DESIGN AND METHODS: With use of the SCI-Diabetes register, two cohorts were identified: individuals with type 2 diabetes in 2016 and at the 2020 pandemic onset. Hospital and death records were linked for determination of pneumonia exposure and CVD deaths. Poisson regression estimated rate ratios (RRs) for CVD death associated with both pneumonia types, with adjustment for confounders. Median follow-up durations were 1,461 days (2016 cohort) and 700 days (2020 cohort). RESULTS: The adjusted RR for CVD death following non-COVID-19 pneumonia was 5.51 (95% CI 5.31-5.71) prepandemic and 7.3 (6.86-7.76) during the pandemic. For COVID-19 pneumonia, the RR was 9.13 (8.55-9.75). Beyond 30 days post pneumonia, the RRs converged, to 4.24 (3.90-4.60) for non-COVID-19 and 3.35 (3.00-3.74) for COVID-19 pneumonia, consistent even with exclusion of prior CVD cases. CONCLUSIONS: Hospitalized pneumonia, irrespective of causal agent, marks an increased risk for CVD death immediately and over the long-term. COVID-19 pneumonia poses a higher CVD death risk than other pneumonias in the short-term, but this distinction diminishes over time. These insights underscore the need for including pneumonia in CVD risk assessments, with particular attention to the acute impact of COVID-19 pneumonia.

Basic host response parameters to classify mortality risk in COVID-19 and community-acquired pneumonia.

Improved phenotyping in pneumonia is necessary to strengthen risk assessment. Via a feasible and multidimensional approach with basic parameters, we aimed to evaluate the effect of host response at admission on severity stratification in COVID-19 and community-acquired pneumonia (CAP). Three COVID-19 and one CAP multicenter cohorts including hospitalized patients were recruited. Three easily available variables reflecting different pathophysiologic mechanisms-immune, inflammation, and respiratory-were selected (absolute lymphocyte count [ALC], C-reactive protein [CRP] and, SpO2/FiO2). In-hospital mortality and intensive care unit (ICU) admission were analyzed as outcomes. A multivariable, penalized maximum likelihood logistic regression was performed with ALC (< 724 lymphocytes/mm3), CRP (> 60 mg/L), and, SpO2/FiO2 (< 450). A total of 1452, 1222 and 462 patients were included in the three COVID-19 and 1292 in the CAP cohort for the analysis. Mortality ranged between 4 and 32% (0 to 3 abnormal biomarkers) and 0-9% in SARS-CoV-2 pneumonia and CAP, respectively. In the first COVID-19 cohort, adjusted for age and sex, we observed an increased odds ratio for in-hospital mortality in COVID-19 with elevated biomarkers altered (OR 1.8, 3, and 6.3 with 1, 2, and 3 abnormal biomarkers, respectively). The model had an AUROC of 0.83. Comparable findings were found for ICU admission, with an AUROC of 0.76. These results were confirmed in the other COVID-19 cohorts Similar OR trends were reported in the CAP cohort; however, results were not statistically significant. Assessing the host response via accessible biomarkers is a simple and rapidly applicable approach for pneumonia.

The relationship between comprehensive geriatric assessment on the pneumonia prognosis of older adults: a cross-sectional study.

BACKGROUND: The mortality of pneumonia in older adults surpasses that of other populations, especially with the prevalence of coronavirus disease 2019 (COVID-19). Under the influence of multiple factors, a series of geriatric syndromes brought on by age is one of the main reasons for the poor prognosis of pneumonia. This study attempts to analyze the impact of geriatric syndrome on the prognosis of pneumonia. METHODS: This is a prospective cross-sectional study. Patients over 65 years old with COVID-19 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-negative community-acquired pneumonia (SN-CAP) were included in the research. General characteristics, laboratory tests, length of stay (LOS), and comprehensive geriatric assessment (CGA) were collected. Multivariate regression analysis to determine the independent predictors of the severity, mortality, and LOS of COVID-19. At the same time, the enrolled subjects were divided into three categories by clustering analysis of 10 CGA indicators, and their clinical characteristics and prognoses were analyzed. RESULTS: A total of 792 subjects were included in the study, including 204 subjects of SN-CAP (25.8%) and 588 subjects (74.2%) of COVID-19. There was no significant difference between non-severe COVID-19 and SN-CAP regarding mortality, LOS, and CGA (P > 0.05), while severe COVID-19 is significantly higher than both (P < 0.05). The Barthel Index used to assess the activities of daily living was an independent risk factor for the severity and mortality of COVID-19 and linearly correlated with the LOS (P < 0.05). The cluster analysis based on the CGA indicators divided the geriatric pneumonia patients into three groups: Cluster 1 (n = 276), named low ability group, with the worst CGA, laboratory tests, severity, mortality, and LOS; Cluster 3 (n = 228), called high ability group with the best above indicators; Cluster 2 (n = 288), named medium ability group, falls between the two. CONCLUSION: The Barthel Index indicates that decreased activities of daily living are an independent risk factor for the severity, mortality, and LOS of geriatric COVID-19. Geriatric syndrome can help judge the prognosis of pneumonia in older adults.