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Human herpes viruses (HHVs) are commonly detected in community-acquired pneumonia (CAP) patients, particularly those with complex complications, attracting increased attention from clinical practitioners. However, the significance of detecting HHVs in bronchoalveolar lavage fluid (BALF) with CAP patients is still unclear. This study retrospectively analyzed BALF samples from 64 CAP patients at the Kunming Third People's Hospital between August 2021 and December 2023. Metagenomic next generation sequencing (mNGS) was conducted on BALF samples during CAP onset. Multivariate Cox regression models were used to identify independent risk factors for 30-day all-cause mortality in CAP. HHVs were found in 84.4% of CAP patients, which were the most common pathogens (45.1%), followed by bacteria (30.2%) and fungi (11.5%). Bacterial-viral co-infections were most common, occurring in 39 patients. Notably, there was no significant difference in HHV presence between severe and non-severe CAP patients (EBV: P = 0.431, CMV: P = 0.825), except for HHV-7 (P = 0.025). In addition, there was no significant difference in the 30-day mortality between HHV positive and HHV negative groups (P = 0.470), as well as between the HHV-7 positive and HHV-7 negative groups (P = 0.910). However, neither HHVs nor HHV-7 was independent risk factors for 30-day mortality in CAP patients (HHVs: HR 1.171, P = 0.888; HHV-7: HR 1.947, P = 0.382). In summary, among the prevalent presence of multiple HHVs, EBV and CMV were the most prevalent in CAP patients. Patients with sCAP were more susceptible to HHV-7 than those with non-sCAP. These results provide valuable insights for clinicians in guiding appropriate interventions for CAP treatment.

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BACKGROUND: The quick sequential [sepsis-related] organ failure assessment (qSOFA) acts as a prompt to consider possible sepsis. The contributions of individual qSOFA elements to assessment of severity and for prediction of mortality remain unknown. METHODS: A total of 3974 patients with community-acquired pneumonia were recruited to an observational prospective cohort study. The area under the receiver operating characteristic curve (AUROC), odds ratio, relative risk and Youden's index were employed to assess discrimination. RESULTS: Respiratory rate ≥22/min demonstrated the most superior diagnostic value, indicated by largest odds ratio, relative risk and AUROC, and maximum Youden's index for mortality. However, the indices for altered mentation and systolic blood pressure (SBP) ≤100 mm Hg decreased notably in turn. The predictive validities of respiratory rate ≥22/min, altered mentation and SBP ≤100 mm Hg were good, adequate and poor for mortality, indicated by AUROC (0.837, 0.734 and 0.671, respectively). Respiratory rate ≥22/min showed the strongest associations with SOFA scores, pneumonia severity index, hospital length of stay and costs. However, SBP ≤100 mm Hg was most weakly correlated with the indices. CONCLUSIONS: Respiratory rate ≥22/min made the greatest contribution to parsimonious qSOFA to assess severity and predict mortality. However, the contributions of altered mentation and SBP ≤100 mm Hg decreased strikingly in turn. It is the first known prospective evidence of the contributions of individual qSOFA elements to assessment of severity and for prediction of mortality, which might have implications for more accurate clinical triage decisions.

Respiratory rate ≥22/min demonstrated the most superior diagnostic value.Respiratory rate ≥22/min showed the strongest association with severity.Respiratory rate ≥22/min, altered mentation and SBP ≤100 mm Hg predicted mortality well, adequately and poorly, respectively.

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BACKGROUND: Risk scores facilitate the assessment of mortality risk in patients with community-acquired pneumonia (CAP). Despite their utilities, there is a scarcity of evidence comparing the various RS simultaneously. This study aims to evaluate and compare multiple risk scores reported in the literature for predicting 30-day mortality in adult patients with CAP. METHODS: A retrospective cohort study on patients diagnosed with CAP was conducted across two hospitals in Colombia. The areas under receiver operating characteristic curves (ROC-curves) were calculated for the outcome of survival or death at 30 days using the scores obtained for each of the analyzed questionnaires. RESULTS: A total of 7454 potentially eligible patients were included, with 4350 in the final analysis, of whom 15.2% (662/4350) died within 30 days. The average age was 65.4 years (SD: 21.31), and 59.5% (2563/4350) were male. Chronic kidney disease was 3.7% (9.2% vs. 5.5%; p < 0.001) (OR: 1.85) higher in subjects who died compared to those who survived. Among the patients who died, 33.2% (220/662) presented septic shock compared to 7.3% (271/3688) of the patients who survived (p < 0.001). The best performances at 30 days were shown by the following scores: PSI, SMART-COP and CURB 65 scores with the areas under ROC-curves of 0.83 (95% CI: 0.8-0.85), 0.75 (95% CI: 0.66-0.83), and 0.73 (95% CI: 0.71-0.76), respectively. The RS with the lowest performance was SIRS with the area under ROC-curve of 0.53 (95% CI: 0.51-0.56). CONCLUSION: The PSI, SMART-COP and CURB 65, demonstrated the best diagnostic performances for predicting 30-day mortality in patients diagnosed with CAP. The burden of comorbidities and complications associated with CAP was higher in patients who died.

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BACKGROUND: Pneumonia, a leading cause of morbidity and mortality worldwide, often necessitates Intensive Care Unit (ICU) admission. Accurate prediction of pneumonia mortality is crucial for tailored prevention and treatment plans. However, existing mortality prediction models face limited adoption in clinical practice due to their lack of interpretability. OBJECTIVE: This study aimed to develop an interpretable model for predicting pneumonia mortality in ICUs. Leveraging the Shapley Additive Explanation (SHAP) method, we sought to elucidate the Extreme Gradient Boosting (XGBoost) model and identify prognostic factors for pneumonia. METHODS: Conducted as a retrospective cohort study, we utilized electronic health records from the eICU-CRD (2014-2015) for all adult pneumonia patients. The first 24 h of each ICU admission records were considered, with 70% of the dataset allocated for model training and 30% for validation. The XGBoost model was employed, and performance was assessed using the area under the receiver operating characteristic curve (AUC). The SHAP method provided insights into the XGBoost model. RESULTS: Among 10,962 pneumonia patients, in-hospital mortality was 16.33%. The XGBoost model demonstrated superior predictive performance (AUC: 0.778 ± 0.016)) compared to traditional scoring systems and other machine learning method, which achieved an improvement of 10% points. SHAP analysis identified Aspartate Aminotransferase (AST) as the most crucial predictor. CONCLUSIONS: Interpretable predictive models enhance mortality risk assessment for pneumonia patients in the ICU, fostering transparency. AST emerged as the foremost predictor, followed by patient age, albumin, BMI et al. These insights, rooted in strong correlations with mortality, facilitate improved clinical decision-making and resource allocation.

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BACKGROUND AND OBJECTIVE: Community-acquired pneumonia (CAP) is a common respiratory disease that frequently requires hospitalisation, and is a significant cause of death worldwide. This study aimed to evaluate the usefulness of alpha-1-antichymotrypsin (AACT) as a diagnostic and prognostic biomarker of CAP. METHODS: We conducted a multicentre prospective cohort study in patients hospitalised with CAP. Plasma AACT levels were measured using a quantitative enzyme-linked immunosorbent assay. Receiver-operating characteristic (ROC) curves and Cox proportional hazards regression were used to assess the association between plasma AACT levels and CAP diagnosis and prognosis. RESULTS: A total of 274 patients with CAP were enrolled in the study. AACT levels were elevated in patients with CAP, especially those with severe CAP and non-survivors. The area under the curve (AUC) of AACT and CRP for diagnosing CAP was 0.755 and 0.843. Cox regression showed that CURB-65 and AACT levels were independent predictors of 30-day mortality. ROC curves showed that plasma AACT levels had the highest accuracy for predicting acute respiratory distress syndrome (ARDS), with an AUC of 0.862. Combining AACT with Pneumonia Severity Index and CURB-65 significantly improved their predictive accuracy for predicting 30-day mortality. CONCLUSION: Plasma AACT levels are elevated in patients with CAP, but plasma AACT level is inferior to the C-reactive protein level for diagnosing CAP. The AACT level can reliably predict the occurrence of ARDS and 30-day mortality in patients with CAP.

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BACKGROUND: Pneumonia stands as a significant global contributor to mortality, particularly in South Africa, where it ranks as the second leading cause of death. The country's high prevalence of HIV infection compounds this issue, significantly increasing mortality rates associated with community-acquired pneumonia (CAP). OBJECTIVE: This study aimed to audit CAP patient management at a regional rural hospital in KwaZulu-Natal. METHOD: A retrospective review of patient files from September to December 2016 was undertaken. Data extraction from clinical files, conducted according to inclusion criteria, was transferred to a data collection sheet and analyzed using SPSS version 21. RESULTS: The review encompassed 124 patient files over four months, revealing that 117 (94.4%) patients were not managed by the Standard Treatment Guidelines and Essential Medicines List for South Africa. Of the patients admitted with CAP, 54% were HIV positive, and 49 (39.5%) patients succumbed to the illness. Notably, none of the patients underwent assessment using a severity score. CONCLUSION: The findings underscore a need for more adherence to South African guidelines for managing CAP among staff at the rural regional hospital. This leads to severe consequences, exemplified by the high mortality rate. Urgent intervention is required to incorporate severity assessment scores into pneumonia evaluations, thus enabling appropriate clinical management. CONTRIBUTION: This study sheds light on the significant impact of CAP within the South African hospital context, delineating critical gaps in clinical care and emphasizing the imperative to address clinical inertia.

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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.

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Background: The clinical presentation of Community-acquired pneumonia (CAP) in hospitalized patients exhibits heterogeneity. Inflammation and immune responses play significant roles in CAP development. However, research on immunophenotypes in CAP patients is limited, with few machine learning (ML) models analyzing immune indicators. Methods: A retrospective cohort study was conducted at Xinhua Hospital, affiliated with Shanghai Jiaotong University. Patients meeting predefined criteria were included and unsupervised clustering was used to identify phenotypes. Patients with distinct phenotypes were also compared in different outcomes. By machine learning methods, we comprehensively assess the disease severity of CAP patients. Results: A total of 1156 CAP patients were included in this research. In the training cohort (n=809), we identified three immune phenotypes among patients: Phenotype A (42.0%), Phenotype B (40.2%), and Phenotype C (17.8%), with Phenotype C corresponding to more severe disease. Similar results can be observed in the validation cohort. The optimal prognostic model, SuperPC, achieved the highest average C-index of 0.859. For predicting CAP severity, the random forest model was highly accurate, with C-index of 0.998 and 0.794 in training and validation cohorts, respectively. Conclusion: CAP patients can be categorized into three distinct immune phenotypes, each with prognostic relevance. Machine learning exhibits potential in predicting mortality and disease severity in CAP patients by leveraging clinical immunological data. Further external validation studies are crucial to confirm applicability.

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BACKGROUND: Severe pneumonia has consistently been associated with high mortality. We sought to identify risk factors for the mortality of severe pneumonia to assist in reducing mortality for medical treatment. METHODS: Electronic databases including PubMed, Web of Science, EMBASE, Cochrane Library, and Scopus were systematically searched till June 1, 2023. All human research were incorporated into the analysis, regardless of language, publication date, or geographical location. To pool the estimate, a mixed-effect model was used. The Newcastle-Ottawa Scale (NOS) was employed for assessing the quality of included studies that were included in the analysis. RESULTS: In total, 22 studies with a total of 3655 severe pneumonia patients and 1107 cases (30.29%) of death were included in the current meta-analysis. Significant associations were found between age [5.76 years, 95% confidence interval [CI] (3.43, 8.09), P < 0.00001], male gender [odds ratio (OR) = 1.47, 95% CI (1.07, 2.02), P = 0.02], and risk of death from severe pneumonia. The comorbidity of neoplasm [OR = 3.37, 95% CI (1.07, 10.57), P = 0.04], besides the presence of complications such as diastolic hypotension [OR = 2.60, 95% CI (1.45, 4.67), P = 0.001], ALI/ARDS [OR = 3.63, 95% CI (1.78, 7.39), P = 0.0004], septic shock [OR = 9.43, 95% CI (4.39, 20.28), P < 0.00001], MOF [OR = 4.34, 95% CI (2.36, 7.95), P < 0.00001], acute kidney injury [OR = 2.45, 95% CI (1.14, 5.26), P = 0.02], and metabolic acidosis [OR = 5.88, 95% CI (1.51, 22.88), P = 0.01] were associated with significantly higher risk of death among patients with severe pneumonia. Those who died, compared with those who survived, differed on multiple biomarkers on admission including serum creatinine [Scr: + 67.77 mmol/L, 95% CI (47.21, 88.34), P < 0.00001], blood urea nitrogen [BUN: + 6.26 mmol/L, 95% CI (1.49, 11.03), P = 0.01], C-reactive protein [CRP: + 33.09 mg/L, 95% CI (3.01, 63.18), P = 0.03], leukopenia [OR = 2.63, 95% CI (1.34, 5.18), P = 0.005], sodium < 136 mEq/L [OR = 2.63, 95% CI (1.34, 5.18), P = 0.005], albumin [- 5.17 g/L, 95% CI (- 7.09, - 3.25), P < 0.00001], PaO2/FiO2 [- 55.05 mmHg, 95% CI (- 60.11, - 50.00), P < 0.00001], arterial blood PH [- 0.09, 95% CI (- 0.15, - 0.04), P = 0.0005], gram-negative microorganism [OR = 2.56, 95% CI (1.17, 5.62), P = 0.02], and multilobar or bilateral involvement [OR = 3.65, 95% CI (2.70, 4.93), P < 0.00001]. CONCLUSIONS: Older age and male gender might face a greater risk of death in severe pneumonia individuals. The mortality of severe pneumonia may also be significantly impacted by complications such diastolic hypotension, ALI/ARDS, septic shock, MOF, acute kidney injury, and metabolic acidosis, as well as the comorbidity of neoplasm, and laboratory indicators involving Scr, BUN, CRP, leukopenia, sodium, albumin, PaO2/FiO2, arterial blood PH, gram-negative microorganism, and multilobar or bilateral involvement. SYSTEMATIC REVIEW REGISTRATION: PROSPERO Protocol Number: CRD 42023430684.

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This study investigates serum calcium's prognostic value in pediatric pneumonia, focusing on its correlation with PICU mortality, to enhance understanding and treatment approaches in this field. Data from 414 pediatric pneumonia patients (2010-2019) admitted to the intensive care units at the Children's Hospital, Zhejiang University School of Medicine were analyzed. The study utilized restricted cubic spline analysis, Cox proportional hazard regression, and Kaplan-Meier survival curve analysis to assess the relationship between serum calcium levels at admission and PICU mortality risk. After adjusting for multivariate factors, for each 1 mmol/dL increase in serum calcium, the risk of mortality decreased by 24% (HR: 0.76, 95% CI 0.67-0.87). Among the three levels of serum calcium groups, higher serum calcium levels were linked to a 63% reduction in the mortality rate compared to lower levels (HR: 0.37, 95% CI 0.16-0.84). The cumulative hazard estimates of mortality significantly differed across serum calcium groups (log-rank P = 0.032). This association was consistent across diverse subgroups (P for interaction > 0.05). Higher serum calcium levels are associated with decreased PICU mortality in pediatric pneumonia, highlighting its potential as a prognostic marker.

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BACKGROUND: Community-acquired pneumonia (CAP) is a significant health issue among the elderly, with severe cases (SCAP) having high mortality rates. This study assesses the predictive significance of the stress hyperglycemia ratio (SHR) in elderly SCAP patients and its impact on outcomes in both diabetic and non-diabetic patients. METHODS AND MATERIALS: This retrospective study included 406 SCAP patients aged 65 or older from the Second People's Hospital of Lianyungang (January 2020 to December 2023). Data collected included demographics, medical history, vital signs, and lab results. SHR was calculated from initial blood glucose and estimated average glucose (HbA1c). Statistical analyses, including Cox regression and Kaplan-Meier analysis, evaluated SHR's impact on mortality. Mediation models explored the effects of neutrophil-lymphocyte ratio (NLR) and SHR. RESULTS: The 28-day mortality rate was 21.67%. Deceased patients had higher age, Charlson Comorbidity Index, procalcitonin, NLR, glucose, and SHR levels compared to survivors (P < 0.05). Both SHR and NLR significantly increased mortality risk, particularly in non-diabetic patients. Combining NLR and SHR improved ROC AUC to 0.898, with 89.80% sensitivity and 81.10% specificity. Kaplan-Meier analysis showed higher cumulative survival for SHR < 1.14, regardless of diabetes status (P < 0.05). NLR mediated 13.02% of the SHR-survival relationship, while SHR mediated 14.06% of the NLR-survival relationship. CONCLUSION: Elevated SHR is a significant mortality risk factor in elderly SCAP patients, independent of diabetes status. Stringent glucose control and careful monitoring of SHR may improve outcomes in elderly patients with acute respiratory conditions.

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BACKGROUND: The Hospital Readmission Reduction Programme (HRRP) was created to decrease the number of hospital readmissions for acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), heart failure (HF), pneumonia (PNA), coronary artery bypass graft (CABG), elective total hip arthroplasty (THA) and total knee arthroplasty. OBJECTIVES: To analyse the impact of the HRRP on readmission rates from 2010 to 2019 and how time to readmission impacted outcomes. DESIGN: Population-based retrospective study. SETTING: All patients included in the US National Readmission database from 2010 to 2019. PATIENTS: We recorded demographic and clinical variables. MEASUREMENTS: Using linear regression models, we analysed the association between readmission status and timing with death and length of stay (LOS) outcomes. We transformed LOS and charges into log-LOS and log-charges to normalise the data. RESULTS: There were 31 553 363 records included in the study. Of those, 4 593 228 (14.55%) were readmitted within 30 days. From 2010 to 2019, readmission rates for COPD (20.8%-19.8%), HF (24.9%-21.9%), PNA (16.4%-15.1%), AMI (15.6%-12.9%) and TKR (4.1%-3.4%) decreased whereas CABG (10.2%-10.6%) and THA (4.2%-5.8%) increased. Readmitted patients were at higher risk of mortality (6% vs 2.8%) and had higher LOS (3 (2-5) vs 4 (3-7)). Patients readmitted within 10 days had a mortality 6.4% higher than those readmitted in 11-20 days (5.4%) and 21-30 days (4.6%). Increased time from discharge to readmission was associated with a lower likelihood of mortality, like LOS. CONCLUSION: Over the last 10 years, readmission rates decreased for most conditions included in the HRRP except CABG and THA. Patients readmitted shortly after discharge were at higher risk of death.

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Objective: This retrospective cohort study aimed to investigate the composition and diversity of lung microbiota in patients with severe pneumonia and explore its association with short-term prognosis. Methods: A total of 301 patients diagnosed with severe pneumonia underwent bronchoalveolar lavage fluid metagenomic next-generation sequencing (mNGS) testing from February 2022 to January 2024. After applying exclusion criteria, 236 patients were included in the study. Baseline demographic and clinical characteristics were compared between survival and non-survival groups. Microbial composition and diversity were analyzed using alpha and beta diversity metrics. Additionally, LEfSe analysis and machine learning methods were employed to identify key pathogenic microorganism associated with short-term mortality. Microbial interaction modes were assessed through network co-occurrence analysis. Results: The overall 28-day mortality rate was 37.7% in severe pneumonia. Non-survival patients had a higher prevalence of hypertension and exhibited higher APACHE II and SOFA scores, higher procalcitonin (PCT), and shorter hospitalization duration. Microbial α and ß diversity analysis showed no significant differences between the two groups. However, distinct species diversity patterns were observed, with the non-survival group showing a higher abundance of Acinetobacter baumannii, Klebsiella pneumoniae, and Enterococcus faecium, while the survival group had a higher prevalence of Corynebacterium striatum and Enterobacter. LEfSe analysis identified 29 distinct terms, with 10 potential markers in the non-survival group, including Pseudomonas sp. and Enterococcus durans. Machine learning models selected 16 key pathogenic bacteria, such as Klebsiella pneumoniae, significantly contributing to predicting short-term mortality. Network co-occurrence analysis revealed greater complexity in the non-survival group compared to the survival group, with differences in central genera. Conclusion: Our study highlights the potential significance of lung microbiota composition in predicting short-term prognosis in severe pneumonia patients. Differences in microbial diversity and composition, along with distinct microbial interaction modes, may contribute to variations in short-term outcomes. Further research is warranted to elucidate the clinical implications and underlying mechanisms of these findings.

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BACKGROUND: Patients with severe community-acquired pneumonia (sCAP) admitted to the intensive care unit (ICU) often exhibit muscle catabolism, muscle weakness, and/or atrophy, all related to an increased morbidity and mortality. However, the relationship between thoracic skeletal muscle mass and sCAP-related mortality has not been well-studied. Early recognition of sarcopenia in ICU patients with sCAP would benefit their prognosis. METHODS: A retrospective study was conducted in Taizhou Hospital of Zhejiang Province, involving 101 patients with sCAP admitted in the ICU between December 2022 and February 2023. We measured the cross-sectional aera of the pectoralis, intercostal, paraspinal, serratus, and latissimus muscles at the T4 vertebral level (T4CSA) using chest computed tomography. Discriminatory thresholds were established by performing receiver operating characteristic curve analysis, with a designated cutoff value of 96.75 cm2 for male patients. This cohort was classified into mortality and survival groups based on a 6-month post-admission outcome. Univariate and multifactorial logistic regression analyses were performed to validate the correlation between low thoracic skeletal muscle area and prognostic outcomes. RESULTS: The mean age of the patients was 75.39 ± 12.09 years, with an overall 6-month mortality of 73.27%. T4CSA of the 6-month survival group was significantly larger than that in the mortality group for overall cohort. The T4CSA in the survival group was significantly larger than that in the mortality group (104.29 ± 23.98cm2 vs. 87.44 ± 23.0cm2, p = 0.008). T4CSA predicted the 6-month mortality from sCAP in males with an AUC of 0.722 (95% confidence interval (CI), 0.582-0.861). The specificity and sensitivity were 71.4% and 71.1%, respectively, (p < 0.05). No significant difference was observed between the two groups in terms of T4CSA. CONCLUSIONS: This study revealed that low thoracic skeletal muscle mass increased the risk of all-cause 6-month mortality in ICU patients with sCAP, particularly among male patients.

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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.

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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.

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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.

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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.

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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.

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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.

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