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.

OBJECTIVE: COVID-19 has led to significant morbidity and mortality globally. Post-COVID sequelae can persist beyond the acute and subacute phases of infection, often termed Post-COVID Syndrome (PCS). There is limited evidence on the appropriate rehabilitation for people with PCS. The aim of this study is to evaluate the effect on exercise capacity, symptoms, cognition, anxiety, depression, health-related quality of life (HRQoL), and fatigue, of a 4-week, twice-weekly supervised pulmonary telerehabilitation program compared to usual medical care for people with PCS with persistent respiratory symptoms.
METHODS: The study will be a multi-site randomized controlled trial (RCT) with assessor blinding. Participants with confirmed previous COVID-19 infection and persistent respiratory symptoms who attend a post-COVID respiratory clinic will be randomized 1:1 to either an intervention group (IG) of 4 weeks, twice-weekly pulmonary telerehabilitation or a control group (CG) of usual medical care. Participants in the CG will be invited to cross-over into the IG after the week 4 assessment. Primary outcome: exercise capacity measured by the 1-minute sit-to-stand test. Secondary outcomes: 5 repetition sit-to-stand test; Montreal Cognitive Assessment; COVID-19 Yorkshire Rehabilitation Scale; COPD Assessment Test; 36-Item Short-Form Health Survey; Hospital Anxiety and Depression Scale; Fatigue Severity Scale; and the Kessler Psychological Distress Scale. Outcomes will be collected at baseline, after 4-weeks intervention or control period, after intervention in the cross-over group, and at 12-month follow-up.
UNASSIGNED: Research into effective rehabilitation programs is crucial given the substantial morbidity associated with PCS and the lack of long-term data for COVID-19 recovery. A short duration pulmonary telerehabilitation program, if effective compared to usual care, could inform practice guidelines and direct future clinical trials for the benefit of individuals with persistent respiratory symptoms post-COVID.

UNASSIGNED: Little is known about the degree to which suspected sepsis drives broad-spectrum antibiotic use in hospitals, what proportion of antibiotic courses are unnecessarily broad in retrospect, and whether these patterns are changing over time.
UNASSIGNED: To describe trends in empiric broad-spectrum antibiotic use for suspected community-onset sepsis.
UNASSIGNED: This cross-sectional study used clinical data from adults admitted to 241 US hospitals in the PINC AI Healthcare Database. Eligible participants were aged 18 years or more and were admitted between 2017 and 2021 with suspected community-onset sepsis, defined by a blood culture draw, lactate measurement, and intravenous antibiotic administration on admission.
UNASSIGNED: Empiric anti-methicillin-resistant Staphylococcus aureus (MRSA) and/or antipseudomonal β-lactam agent use.
UNASSIGNED: Annual rates of empiric anti-MRSA and/or antipseudomonal β-lactam agent use and the proportion that were likely unnecessary in retrospect based on the absence of β-lactam resistant gram-positive or ceftriaxone-resistant gram-negative pathogens from clinical cultures obtained through hospital day 4. Annual trends were calculated using mixed-effects logistic regression models, adjusting for patient and hospital characteristics.
UNASSIGNED: Among 6 272 538 hospitalizations (median [IQR] age, 66 [53-78] years; 443 465 male [49.6%]; 106 095 Black [11.9%], 65 763 Hispanic [7.4%], 653 907 White [73.1%]), 894 724 (14.3%) had suspected community-onset sepsis, of whom 582 585 (65.1%) received either empiric anti-MRSA (379 987 [42.5%]) or antipseudomonal β-lactam therapy (513 811 [57.4%]); 311 213 (34.8%) received both. Patients with suspected community-onset sepsis accounted for 1 573 673 of 3 141 300 (50.1%) of total inpatient anti-MRSA antibiotic days and 2 569 518 of 5 211 745 (49.3%) of total antipseudomonal β-lactam days. Between 2017 and 2021, the proportion of patients with suspected sepsis administered anti-MRSA or antipseudomonal therapy increased from 63.0% (82 731 of 131 275 patients) to 66.7% (101 003 of 151 435 patients) (adjusted OR [aOR] per year, 1.03; 95% CI, 1.03-1.04). However, resistant organisms were isolated in only 65 434 cases (7.3%) (30 617 gram-positive [3.4%], 38 844 gram-negative [4.3%]) and the proportion of patients who had any resistant organism decreased from 9.6% to 7.3% (aOR per year, 0.87; 95% CI, 0.87-0.88). Most patients with suspected sepsis treated with empiric anti-MRSA and/or antipseudomonal therapy had no resistant organisms (527 356 of 582 585 patients [90.5%]); this proportion increased from 88.0% in 2017 to 91.6% in 2021 (aOR per year, 1.12; 95% CI, 1.11-1.13).
UNASSIGNED: In this cross-sectional study of adults admitted to 241 US hospitals, empiric broad-spectrum antibiotic use for suspected community-onset sepsis accounted for half of all anti-MRSA or antipseudomonal therapy; the use of these types of antibiotics increased between 2017 and 2021 despite resistant organisms being isolated in less than 10% of patients treated with broad-spectrum agents.

BACKGROUND: The emergence of metagenomic next-generation sequencing (mNGS) may provide a promising tool for early and comprehensive identification of the causative pathogen in community-acquired pneumonia (CAP). In this study, we aim to further evaluate the etiological diagnostic value of mNGS in suspected CAP.
METHODS: A total of 555 bronchoalveolar lavage fluid (BALF) samples were collected for pathogen detection by mNGS from 541 patients with suspected CAP. The clinical value was assessed based on infection diagnosis and treatment guidance. The diagnostic performance for pathogen identification by mNGS and sputum culture and for tuberculosis (TB) by mNGS and X-pert MTB/RIF were compared. To evaluate the potential for treatment guidance, we analyzed the treatment regimen of patients with suspected CAP, including imaging changes of lung after empirical antibacterial therapy, intensified regimen, antifungal treatment, and a 1-year follow up for patients with unconfirmed diagnosis and non-improvement imaging after anti-infective treatment and patients with high suspicion of TB or NTM infection who were transferred to the Wuhan Pulmonary Hospital for further diagnosis and even anti-mycobacterium therapy.
RESULTS: Of the 516 BALF samples that were analyzed by both mNGS and sputum culture, the positivity rate of mNGS was significantly higher than that of sputum culture (79.1% vs. 11.4%, P = 0.001). A total of 48 samples from patients with confirmed TB were analyzed by both mNGS and X-pert MTB/RIF, and the sensitivity of mNGS for the diagnosis of active TB was significantly lower than that of X-pert MTB/RIF (64.6% vs. 85.4%, P = 0.031). Of the 106 pathogen-negative cases, 48 were ultimately considered non-infectious diseases, with a negative predictive value of 45.3%. Of the 381 pathogen-positive cases, 311 were eventually diagnosed as CAP, with a positive predictive value of 81.6%. A total of 487 patients were included in the evaluation of the therapeutic effect, and 67.1% improved with initial empirical antibiotic treatment. Of the 163 patients in which bacteria were detected, 77.9% improved with antibacterial therapy; of the 85 patients in which fungi were detected, 12.9% achieved remission after antifungal therapy.
CONCLUSIONS: Overall, mNGS had unique advantages in the detection of suspected CAP pathogens. However, mNGS was not superior to X-pert MTB/RIF for the diagnosis of TB. In addition, mNGS was not necessary as a routine test for all patients admitted with suspected CAP. Furthermore, when fungi are detected by mNGS, antifungal therapy should be cautious.

BACKGROUND: Necrotizing fasciitis (NF) is a rare but potentially life-threatening soft tissue infection. The objective of this study was to assess the association between timely surgery within 6 h and hospital mortality in patients with limb NF, and to describe the trends in patients with NF, time to surgery and standardized mortality ratio (SMR) over 11 years.
METHODS: This was a multicenter, retrospective cohort study of all intensive care unit patients who had emergency surgery within 24 h of hospitalization for limb NF between April 1, 2008 and March 31, 2019 in Hong Kong. Timely surgery was defined as the first surgical treatment within 6 h of initial hospitalization. Appropriate antibiotics were achieved if the patient was given antibiotic(s) for all documented pathogens prior to or on day of culture results. The primary outcome was hospital mortality.
RESULTS: There were 495 patients (median age 62 years, 349 (70.5%) males) with limb NF treated by surgery within 24 h of hospitalization over the 11 years. Appropriate antibiotic(s) were used in 392 (79.2%) patients. There were 181 (36.5%) deaths. Timely surgery was not associated with hospital mortality (Relative Risk 0.89, 95% CI: 0.73 to 1.07) but admission year, advanced age, higher severity of illness, comorbidities, renal replacement therapy, vasopressor use, and type of surgery were significant predictors in the multivariable model. There was an upward trend in NF diagnosis (1.9 cases/year, 95% CI: 0.7 to 3.1; P < 0.01; R2 = 0.60) but there was no downward trend in median time to surgery (-0.2 h/year, 95% CI: -0.4 to 0.1; P = 0.16) or SMR (-0.02/year, 95% CI: -0.06 to 0.01; P = 0.22; R2 = 0.16).
CONCLUSIONS: Among patients operated within 24 h, very early surgery within 6-12 h was not associated with survival. Increasing limb NF cases were reported each year but mortality remained high despite a high rate of appropriate antibiotic use and timely surgical intervention.

BACKGROUND: COVID-19 clinical course is highly variable and secondary infections contribute to COVID-19 complexity. Early detection of secondary infections is clinically relevant for patient outcome. Procalcitonin (PCT) and C-reactive protein (CRP) are the most used biomarkers of infections. Pentraxin 3 (PTX3) is an acute phase protein with promising performance as early biomarker in infections. In patients with COVID-19, PTX3 plasma concentrations at hospital admission are independent predictor of poor outcome. In this study, we assessed whether PTX3 contributes to early identification of co-infections during the course of COVID-19.
METHODS: We analyzed PTX3 levels in patients affected by COVID-19 with (n = 101) or without (n = 179) community or hospital-acquired fungal or bacterial secondary infections (CAIs or HAIs).
RESULTS: PTX3 plasma concentrations at diagnosis of CAI or HAI were significantly higher than those in patients without secondary infections. Compared to PCT and CRP, the increase of PTX3 plasma levels was associated with the highest hazard ratio for CAIs and HAIs (aHR 11.68 and 24.90). In multivariable Cox regression analysis, PTX3 was also the most significant predictor of 28-days mortality or intensive care unit admission of patients with potential co-infections, faring more pronounced than CRP and PCT.
CONCLUSIONS: PTX3 is a promising predictive biomarker for early identification and risk stratification of patients with COVID-19 and co-infections.
BACKGROUND: Dolce & Gabbana fashion house donation; Ministero della Salute for COVID-19; EU funding within the MUR PNRR Extended Partnership initiative on Emerging Infectious Diseases (Project no. PE00000007, INF-ACT) and MUR PNRR Italian network of excellence for advanced diagnosis (Project no. PNC-E3-2022-23683266 PNC-HLS-DA); EU MSCA (project CORVOS 860044).

BACKGROUND: Sepsis is a leading cause of death and serious illness that requires early recognition and therapeutic management to improve survival. The quick-SOFA score helps in its recognition, but its diagnostic performance is insufficient. To develop a score that can rapidly identify a community acquired septic situation at risk of clinical complications in patients consulting the emergency department (ED).
METHODS: We conducted a monocentric, prospective cohort study in the emergency department of a university hospital between March 2016 and August 2018 (NCT03280992). All patients admitted to the emergency department for a suspicion of a community-acquired infection were included. Predictor variables of progression to septic shock or death within the first 90 days were selected using backward stepwise multivariable logistic regression to develop a clinical score. Receiver operating characteristic (ROC) curves were constructed to determine the discriminating power of the area under the curve (AUC). We also determined the threshold of our score that optimized the performance required for a sepsis-worsening score. We have compared our score with the NEWS-2 and qSOFA scores.
RESULTS: Among the 21,826 patients admitted to the ED, 796 patients were suspected of having community-acquired infection and 461 met the sepsis criteria; therefore, these patients were included in the analysis. The median [interquartile range] age was 72 [54-84] years, 248 (54%) were males, and 244 (53%) had respiratory symptoms. The clinical score ranged from 0 to 90 and included 8 variables with an area under the ROC curve of 0.85 (confidence interval [CI] 95% 0.81-0.89). A cut-off of 26 yields a sensitivity of 88% (CI 95% 0.79-0.93), a specificity of 62% (CI 95% 57-67), and a negative predictive value of 95% (CI 95% 91-97). The area under the ROC curve for our score was 0.85 (95% CI, 0.81-0.89) versus 0.73 (95% CI, 0.68-0.78) for qSOFA and 0.66 (95% CI, 0.60-0.72) for NEWS-2.
CONCLUSIONS: Our study provides an accurate clinical score for identifying septic patients consulting the ED early at risk of worsening disease. This score could be implemented at admission.

BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients.
METHODS: This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model.
RESULTS: The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-β-D-glucan test (G test).
CONCLUSIONS: We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

There are numerous prognostic predictive models for evaluating mortality risk, but current scoring models might not fully cater to sepsis patients\' needs. This study developed and validated a new model for sepsis patients that is suitable for any care setting and accurately forecasts 28-day mortality. The derivation dataset, gathered from 20 hospitals between September 2019 and December 2021, contrasted with the validation dataset, collected from 15 hospitals from January 2022 to December 2022. In this study, 7436 patients were classified as members of the derivation dataset, and 2284 patients were classified as members of the validation dataset. The point system model emerged as the optimal model among the tested predictive models for foreseeing sepsis mortality. For community-acquired sepsis, the model\'s performance was satisfactory (derivation dataset AUC: 0.779, 95% CI 0.765-0.792; validation dataset AUC: 0.787, 95% CI 0.765-0.810). Similarly, for hospital-acquired sepsis, it performed well (derivation dataset AUC: 0.768, 95% CI 0.748-0.788; validation dataset AUC: 0.729, 95% CI 0.687-0.770). The calculator, accessible at https://avonlea76.shinyapps.io/shiny_app_up/ , is user-friendly and compatible. The new predictive model of sepsis mortality is user-friendly and satisfactorily forecasts 28-day mortality. Its versatility lies in its applicability to all patients, encompassing both community-acquired and hospital-acquired sepsis.

BACKGROUND: Community-acquired pneumonia (CAP) patients with chronic obstructive pulmonary disease (COPD) have higher disease severity and mortality compared to those without COPD. However, deep investigation into microbiome distribution of lower respiratory tract of CAP with or without COPD was unknown.
METHODS: So we used metagenomic next generation sequencing (mNGS) to explore the microbiome differences between the two groups.
RESULTS: Thirty-six CAP without COPD and 11 CAP with COPD cases were retrieved. Bronchoalveolar lavage fluid (BALF) was collected and analyzed using untargeted mNGS and bioinformatic analysis. mNGS revealed that CAP with COPD group was abundant with Streptococcus, Prevotella, Bordetella at genus level and Cutibacterium acnes, Rothia mucilaginosa, Bordetella genomosp. 6 at species level. While CAP without COPD group was abundant with Ralstonia, Prevotella, Streptococcus at genus level and Ralstonia pickettii, Rothia mucilaginosa, Prevotella melaninogenica at species level. Meanwhile, both alpha and beta microbiome diversity was similar between groups. Linear discriminant analysis found that pa-raburkholderia, corynebacterium tuberculostearicum and staphylococcus hominis were more enriched in CAP without COPD group while the abundance of streptococcus intermedius, streptococcus constellatus, streptococcus milleri, fusarium was higher in CAP with COPD group.
CONCLUSIONS: These findings revealed that concomitant COPD have an mild impact on lower airway microbiome of CAP patients.