The safety of trastuzumab deruxtecan (DS-8201) with a focus on interstitial lung disease and/or pneumonitis: A systematic review and single-arm meta-analysis.

BACKGROUND: Previous studies involving risk-benefit analysis of trastuzumab deruxtecan (DS-8201) have indicated the benefit of this treatment, although it may increase the risk of interstitial lung disease (ILD) and/or pneumonitis in certain patients. This study aimed to assess the safety of DS-8201. METHODS: A search was done for relevant articles in four electronic databases: PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov. All reports published up until November 2, 2022, were included, and study types were restricted to clinical trials; the last search was then updated to January 10, 2023. We also assessed the quality of the literature with the Cochrane Handbook for Systematic Reviews of Interventions and the Methodological Index for Non-Randomized Studies tool, and then performed a meta-analysis with R version 4.2.1. RESULTS: A total of 1428 patients reported in 13 articles were included in this study. The analysis revealed that the most common all-grade treatment-emergent adverse events (TEAEs) were nausea and fatigue. The most common TEAE of grade 3 or above (grade ≥3) was neutropenia. The incidences of ILD and/or pneumonitis for all-grade and grade ≥3 TEAEs were 12.5% and 2.2%, respectively. CONCLUSIONS: This comprehensive summary of the incidence of TEAEs associated with DS-8201 in clinical trials provides an important guide for clinicians. The most common TEAEs were gastrointestinal reactions and fatigue; meanwhile, the most common grade ≥3 TEAE was hematological toxicity. ILD and/or pneumonitis were specific adverse drug reactions associated with DS-8201, of which physicians should be particularly aware for their higher morbidity and rates of grade ≥3 TEAEs.

Preoperative Prediction of Postoperative Infections Using Machine Learning and Electronic Health Record Data.

OBJECTIVE: To estimate preoperative risk of postoperative infections using structured electronic health record (EHR) data. BACKGROUND: Surveillance and reporting of postoperative infections is primarily done through costly, labor-intensive manual chart reviews on a small sample of patients. Automated methods using statistical models applied to postoperative EHR data have shown promise to augment manual review as they can cover all operations in a timely manner. However, there are no specific models for risk-adjusting infectious complication rates using EHR data. METHODS: Preoperative EHR data from 30,639 patients (2013-2019) were linked to the American College of Surgeons National Surgical Quality Improvement Program preoperative data and postoperative infection outcomes data from 5 hospitals in the University of Colorado Health System. EHR data included diagnoses, procedures, operative variables, patient characteristics, and medications. Lasso and the knockoff filter were used to perform controlled variable selection. Outcomes included surgical site infection, urinary tract infection, sepsis/septic shock, and pneumonia up to 30 days postoperatively. RESULTS: Among >15,000 candidate predictors, 7 were chosen for the surgical site infection model and 6 for each of the urinary tract infection, sepsis, and pneumonia models. Important variables included preoperative presence of the specific outcome, wound classification, comorbidities, and American Society of Anesthesiologists physical status classification. The area under the receiver operating characteristic curve for each model ranged from 0.73 to 0.89. CONCLUSIONS: Parsimonious preoperative models for predicting postoperative infection risk using EHR data were developed and showed comparable performance to existing American College of Surgeons National Surgical Quality Improvement Program risk models that use manual chart review. These models can be used to estimate risk-adjusted postoperative infection rates applied to large volumes of EHR data in a timely manner.

Use of inhaled corticosteroids and the risk of hospitalisation for pneumonia in children with asthma: a nationwide cohort study.

BACKGROUND: The potential association between the use of inhaled corticosteroids (ICS) and the risk of pneumonia among adults is disputed and paediatric-specific evidence is scarce. AIM: To assess the potential association between ICS, use and the risk of hospitalisation for pneumonia among children (age 2-17 years) with asthma. METHODS: This was a cohort study based on nationwide data from routine clinical practice in Sweden (January 2007 to November 2021). From 425 965 children with confirmed asthma, episodes of new ICS use and no use were identified using records of dispensed drugs. We adjusted for potential confounders with propensity score overlap weighting and the risk of a hospitalisation with pneumonia as primary diagnosis was estimated. Multiple subgroup and sensitivity analyses were also performed. RESULTS: We identified 249 351 ICS (mean follow-up of 0.9 years) and 214 840 no-use (mean follow-up of 0.7 years) episodes. During follow-up, 369 and 181 events of hospitalisation for pneumonia were observed in the ICS and no-use episodes, respectively. The weighted incidence rates of hospitalisation for pneumonia was 14.5 per 10 000 patient-years for ICS use episodes and 14.6 for no-use episodes. The weighted HR for hospitalisation for pneumonia associated with ICS use was 1.06 (95% CI 0.88 to 1.28) and the absolute rate difference was -0.06 (95% CI -2.83 to 2.72) events per 10 000 patient-years, compared with no use. CONCLUSIONS: In this nationwide cohort study, we found no evidence of an association between ICS use and the risk of hospitalisation for pneumonia among children with asthma, as compared with no use.

Total infectome characterization of respiratory infections in pre-COVID-19 Wuhan, China.

At the end of 2019 Wuhan witnessed an outbreak of "atypical pneumonia" that later developed into a global pandemic. Metagenomic sequencing rapidly revealed the causative agent of this outbreak to be a novel coronavirus denoted SARS-CoV-2. To provide a snapshot of the pathogens in pneumonia-associated respiratory samples from Wuhan prior to the emergence of SARS-CoV-2, we collected bronchoalveolar lavage fluid samples from 408 patients presenting with pneumonia and acute respiratory infections at the Central Hospital of Wuhan between 2016 and 2017. Unbiased total RNA sequencing was performed to reveal their "total infectome", including viruses, bacteria and fungi. We identified 35 pathogen species, comprising 13 RNA viruses, 3 DNA viruses, 16 bacteria and 3 fungi, often at high abundance and including multiple co-infections (13.5%). SARS-CoV-2 was not present. These data depict a stable core infectome comprising common respiratory pathogens such as rhinoviruses and influenza viruses, an atypical respiratory virus (EV-D68), and a single case of a sporadic zoonotic pathogen-Chlamydia psittaci. Samples from patients experiencing respiratory disease on average had higher pathogen abundance than healthy controls. Phylogenetic analyses of individual pathogens revealed multiple origins and global transmission histories, highlighting the connectedness of the Wuhan population. This study provides a comprehensive overview of the pathogens associated with acute respiratory infections and pneumonia, which were more diverse and complex than obtained using targeted PCR or qPCR approaches. These data also suggest that SARS-CoV-2 or closely related viruses were absent from Wuhan in 2016-2017.

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

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)-ß-D-glucan test (G test). CONCLUSION: 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.

Endostar acts as a pneumonitis protectant in patients with locally advanced non-small cell lung cancer receiving concurrent chemoradiotherapy.

BACKGROUND: CCRT is presently the standard treatment for LA-NSCLC. RP is one of the main obstacles to the completion of thoracic radiation therapy, resulting in limited survival benefits in NSCLC patients. This research aims to explore the role of Endostar in the occurrence of grade≥2 RP and clinical curative effect in LA-NSCLC patients. METHODS: This study retrospectively analyzed 122 patients with stage III NSCLC who received CCRT from December 2008 to December 2017, or Endostar intravenous drip concurrently with chemoradiotherapy (Endostar + CCRT group). Standard toxicity of the pneumonitis endpoint was also collected by CTCAE V5.0. We further summarized other available studies on the role of Endostar in the prognosis of NSCLC patients and the incidence of RP. RESULTS: There were 76 cases in the CCRT group and 46 cases in the CCRT+ Endostar group. In the CCRT+ Endostar group, the occurrence of grade ≥2 RP in patients with V20Gy ≥25% was significantly higher than that in patients with V20Gy < 25% (p = 0.001). In the cohorts with V20Gy < 25%, 0 cases of 29 patients treated with Endostar developed grade ≥2 RP was lower than in the CCRT group (p = 0.026). The re-analysis of data from other available studies indicated that Endostar plus CCRT could be more efficient and safely in the occurrence of grade≥2 RP with LA-NSCLC. CONCLUSIONS: When receiving CCRT for LA-NSCLC patients, simultaneous combination of Endostar is recommended to enhance clinical benefit and reduce pulmonary toxicity.

Investigating causal associations between pneumonia and lung cancer using a bidirectional mendelian randomization framework.

BACKGROUND: Pneumonia and lung cancer are both major respiratory diseases, and observational studies have explored the association between their susceptibility. However, due to the presence of potential confounders and reverse causality, the comprehensive causal relationships between pneumonia and lung cancer require further exploration. METHODS: Genome-wide association study (GWAS) summary-level data were obtained from the hitherto latest FinnGen database, COVID-19 Host Genetics Initiative resource, and International Lung Cancer Consortium. We implemented a bidirectional Mendelian randomization (MR) framework to evaluate the causal relationships between several specific types of pneumonia and lung cancer. The causal estimates were mainly calculated by inverse-variance weighted (IVW) approach. Additionally, sensitivity analyses were also conducted to validate the robustness of the causalty. RESULTS: In the MR analyses, overall pneumonia demonstrated a suggestive but modest association with overall lung cancer risk (Odds ratio [OR]: 1.21, 95% confidence interval [CI]: 1.01 - 1.44, P = 0.037). The correlations between specific pneumonia types and overall lung cancer were not as significant, including bacterial pneumonia (OR: 1.07, 95% CI: 0.91 - 1.26, P = 0.386), viral pneumonia (OR: 1.00, 95% CI: 0.95 - 1.06, P = 0.891), asthma-related pneumonia (OR: 1.18, 95% CI: 0.92 - 1.52, P = 0.181), and COVID-19 (OR: 1.01, 95% CI: 0.78 - 1.30, P = 0.952). Reversely, with lung cancer as the exposure, we observed that overall lung cancer had statistically crucial associations with bacterial pneumonia (OR: 1.08, 95% CI: 1.03 - 1.13, P = 0.001) and viral pneumonia (OR: 1.09, 95% CI: 1.01 - 1.19, P = 0.037). Sensitivity analysis also confirmed the robustness of these findings. CONCLUSION: This study has presented a systematic investigation into the causal relationships between pneumonia and lung cancer subtypes. Further prospective study is warranted to verify these findings.

Pneumonia in childhood bacterial meningitis-Experience from three continents.

INTRODUCTION: Although concomitant pneumonia is sometimes diagnosed in childhood bacterial meningitis, its role in the illness course and prognosis is not known. We examined these associations using prospectively collected data from Finland, Latin America and Angola. METHODS: This was a secondary descriptive analysis of prospectively collected data (clinical and laboratory findings at admission, during hospitalisation and outcome) from five clinical bacterial meningitis trials. We included children aged 2 months to 15 years from sites with confirmed bacterial meningitis and potential concomitant pneumonia (diagnosed clinically with or without a chest radiograph). RESULTS: Pneumonia was not observed in the 341 children included in Finland. Pneumonia was observed in 8% (51/606) of children in Latin America and in 46% (377/819) in Angola (p < 0.0001). In multivariate analyses, predisposing factors for pneumonia in Latin America were age <1 year, seizures and severe anaemia; the corresponding factors for Angola were preadmission duration of illness >3 days and non-meningococcal meningitis. Concomitant pneumonia increased the severity of the disease and disabling sequelae. CONCLUSION: Bacterial meningitis with pneumonia is a major, previously undescribed entity of severe bacterial meningitis, especially in Angola.

Association of Cholinesterase With Postoperative Pneumonia After Gastrectomy for Gastric Cancer.

INTRODUCTION: Cholinesterase is a classical marker that reflects nutritional and inflammatory status. The aim of the present study was to evaluate the association between serum cholinesterase levels and postoperative infectious complications in patients undergoing gastrectomy for gastric cancer. MATERIALS AND METHODS: This retrospective study comprised 108 patients who underwent gastrectomy for gastric cancer. We comprehensively investigated the association between clinicopathological variables and postoperative infectious complications after gastrectomy. Then patients were divided into the cholinesterase-high and -low groups to analyze their clinicopathological variables. Finally, we analyzed the types of infectious complications that were most associated with preoperative serum cholinesterase levels. RESULTS: Twenty-six patients (24%) developed postoperative infectious complications. Multivariate analysis revealed that serum cholinesterase levels (P = 0.026) and N stage (P = 0.009) were independent risk factors for postoperative infectious complications. In particular, the incidence of pneumonia (P = 0.001) was significantly higher in the cholinesterase-low group. Age (P = 0.023), cerebrovascular comorbidities (P = 0.006), serum cholinesterase levels (P = 0.013), and total gastrectomy (P = 0.017) were identified as independent risk factors for postoperative pneumonia. CONCLUSIONS: Preoperative serum cholinesterase levels were associated with postoperative pneumonia after gastrectomy for gastric cancer, suggesting the importance of preoperative nutritional assessment in gastric cancer surgery.

Usefulness of a predictive model to hospitalize patients with low-risk community-acquired pneumonia.

INTRODUCTION: A high proportion of patients with low-risk community-acquired pneumonia (CAP) (classes I-III of the Pneumonia Severity Index) are hospitalized. The purpose of this study was to determine whether validated severity scales are used in clinical practice to make admission decisions, identify the variables that influence this decision, and evaluate the potential predictive value of these variables. MATERIALS AND METHODS: A prospective, observational study of patients ≥ 18 years of age with a diagnosis of low-risk CAP hospitalized or referred from the Emergency Department to outpatient consultations. A multivariate logistic regression predictive model was built to predict the decision to hospitalize a patient. RESULTS: The study population was composed of 1,208 patients (806 inpatients and 402 outpatients). The severity of CAP was estimated in 250 patients (20.7%). The factors that determined hospitalization were "abnormal findings in complementary studies" (643/806: 79.8%; due to respiratory failure in 443 patients) and "signs of clinical deterioration" [64/806 (7.9%): hypotension (16/64, 25%); hemoptoic expectoration (12/64, 18.8%); tachypnea (10/64, 15.6%)]. In total, ambulatory management was not contraindicated in 24.7% of hospitalized patients (199). The predictive model built to decide about hospitalization had a good power of discrimination (AUC 0.876; 95%CI: 0.855-0.897). CONCLUSIONS: Scales are rarely used to estimate the severity of CAP at the emergency department. The decision to hospitalize or not a patient largely depends on the clinical experience of the physician. Our predictive model showed a good power to discriminate the patients who required hospitalization. Further studies are warranted to validate these results.

Incidence of Pneumonia, Related Hospitalization, and Mortality Among Younger Unvaccinated IBD Patients in a Nationwide Cohort.

BACKGROUND AND GOALS: Community Acquired Pneumonia (CAP) is among the most common infections among Inflammatory Bowel Disease (IBD) patients. Our aim was to determine the absolute and relative risk of CAP, related hospitalization, and death among younger (age < 65) unvaccinated IBD patients exposed and unexposed to immunosuppressive medications. MATERIALS AND METHODS: We conducted a retrospective cohort study among a nationwide cohort of younger IBD unvaccinated patients in the VAHS. Exposure was administration of any immunosuppressive medication. The primary outcome was the first occurrence of pneumonia; secondary outcomes being pneumonia related hospitalization and mortality. We reported event rate per 1000 person-years, hazard ratio, and 95% confidence intervals (CIs) for each outcome. RESULTS: Among a total of 26,707 patients, 513 patients developed pneumonia. Mean age in years (SD) was 51.67 (11.34) for the exposed and 45.91 (12.34) for the unexposed group. The overall crude incidence rate was 3.2 per 1000 patient-years (PYs) [4.04/1000 PYs in the exposed versus 1.45/1000 PYs in the unexposed]. The overall crude incidence rates for pneumonia-related-hospitalization and mortality 1.12 and 0.09 per 1000 PYs, respectively. In Cox regression, the exposed group was associated with an increased risk of pneumonia (AHR 2.85; 95% CI: 2.21 to 3.66, P < 0.001) and pneumonia-related-hospitalization (AHR 3.46; 95% CI: 2.20 to 5.43, P < 0.001). CONCLUSIONS: Overall incidence of CAP among younger unvaccinated IBD patients was 3.2 per 1000 PYs. The overall associated hospitalization rates were low, however, higher amongst those exposed to immunosuppressive medications. This data will help patients and physicians make informed decisions regarding pneumococcal vaccine recommendations.

Prediction of new-onset atrial fibrillation with the C2HEST score in patients admitted with community-acquired pneumonia.

PURPOSE: Patients hospitalized for community-acquired pneumonia (CAP) may have a higher risk of new-onset atrial fibrillation (NOAF). The C2HEST score was developed to evaluate the NOAF risk in the general population. Data on the value of the C2HEST score in acute patients admitted with CAP are lacking. We want to establish the predictive value of C2HEST score for NOAF in patients with CAP. METHODS: Patients with CAP enrolled in the SIXTUS cohort were enrolled. C2HEST score was calculated at baseline. In-hospital NOAF was recorded. Receiver-operating Characteristic (ROC) curve and multivariable Cox proportional hazard regression analysis were performed. RESULTS: We enrolled 473 patients (36% women, mean age 70.6 ± 16.5 years), and 54 NOAF occurred. Patients with NOAF were elderly, more frequently affected by hypertension, heart failure, previous stroke/transient ischemic attack, peripheral artery disease and hyperthyroidism. NOAF patients had also higher CURB-65, PSI class and CHA2DS2-VASc score. The C-index of C2HEST score for NOAF was 0.747 (95% confidence interval [95%CI] 0.705-0.786), higher compared to CURB-65 (0.611, 95%CI 0.566-0.655, p = 0.0016), PSI (0.665, 95%CI 0.621-0.708, p = 0.0199) and CHA2DS2-VASc score (0.696, 95%CI 0.652-0.737, p = 0.0762). The best combination of sensitivity (67%) and specificity (70%) was observed with a C2HEST score ≥ 4. This result was confirmed by the multivariable Cox analysis (Hazard Ratio [HR] for C2HEST score ≥ 4 was 10.7, 95%CI 2.0-57.9; p = 0.006), independently from the severity of pneumonia. CONCLUSION: The C2HEST score was a useful predictive tool to identify patients at higher risk for NOAF during hospitalization for CAP. CLINICAL TRIAL REGISTRATION: www. CLINICALTRIALS: gov (NCT01773863).

Systemic inflammatory response index as a predictor of stroke-associated pneumonia in patients with acute ischemic stroke treated by thrombectomy: a retrospective study.

BACKGROUND: The predictive value of systemic inflammatory response index (SIRI) for stroke-associated pneumonia (SAP) risk in patients with acute ischemic stroke (AIS) treated by thrombectomy remains unclear. This study aimed to investigate the predictive value of SIRI for SAP in patients with AIS treated by thrombectomy. METHODS: We included AIS patients treated by thrombectomy between August 2018 and August 2022 at our institute. We used multivariate logistic regression to construct the prediction model and performed a receiver operating characteristic curve analysis to evaluate the ability of SIRI to predict SAP and constructed a calibration curve to evaluate the prediction accuracy of the model. We evaluated the clinical application value of the nomogram using decision curve analysis. RESULTS: We included 84 eligible patients with AIS in the analysis, among which 56 (66.7%) had SAP. In the univariate analysis, there were significant differences in sex (p = 0.035), National Institute of Health Stroke Scale score at admission ≥ 20 (p = 0.019) and SIRI (p < 0.001). The results of multivariable logistic analysis showed that the risk of SAP increased with the SIRI value (OR = 1.169, 95% CI = 1.049-1.344, p = 0.014). Age ≥ 60 (OR = 4.076, 95% CI = 1.251-14.841, p = 0.024) was also statistically significant. A nomogram with SIRI showed good prediction accuracy for SAP in AIS patients treated by thrombectomy (C-index value = 0.774). CONCLUSIONS: SIRI is an independent predictor for SAP in patients with AIS treated by thrombectomy. A high SIRI value may allow for the early identification of patients with AIS treated by thrombectomy at high risk for SAP.

Association between fibrinogen levels and stroke-associated pneumonia in acute ischemic stroke patients.

PURPOSE: Prior research had indicated a relationship between fibrinogen and stroke-associated pneumonia (SAP), yet the nature of this relationship had not been thoroughly investigated. Therefore, this study was designed to elucidate the prognostic value of fibrinogen levels in forecasting the occurrence of SAP among patients with acute ischemic stroke (AIS). PATIENTS AND METHODS: In this retrospective cross-sectional analysis, we included 1092 patients who had experienced AIS and were admitted to our facility within 72 h of the onset of their symptoms. Based on the SAP diagnostic criteria, patients were classified into two groups: SAP and non-SAP. The correlation between serum fibrinogen concentration and SAP was examined using univariate analysis. Curve fitting and multivariable logistic regression model were utilized for statistical evaluation. RESULTS: Out of the ischemic stroke patients included in the study, SAP was identified in 112 (10.26%) patients. A direct correlation was observed between fibrinogen levels and the incidence of SAP. An increase in fibrinogen levels corresponded with a heightened incidence of SAP. Multivariable logistic regression revealed a significant positive association between fibrinogen levels and SAP incidence (OR = 1.53, 95% confidence interval [CI]: 1.18, 1.99)). CONCLUSION: A linear relationship between serum fibrinogen levels and the incidence of SAP in ischemic stroke patients was shown. The serum fibrinogen levels were positively and linearly correlated to SAP risk.

Association and temporal sequence of pneumonia and gastrointestinal bleeding after acute ischemic stroke.

BACKGROUND: Stroke-associated pneumonia (SAP) and gastrointestinal bleeding (GIB) are common medical complications after stroke. The previous study suggested a strong association between SAP and GIB after stroke. However, little is known about the time sequence of SAP and GIB. In the present study, we aimed to verify the association and clarify the temporal sequence of SAP and GIB after ischemic stroke. METHODS: Patients with ischemic stroke from in-hospital Medical Complication after Acute Stroke study were analyzed. Data on occurrences of SAP and GIB during hospitalization and the intervals from stroke onset to diagnosis of SAP and GIB were collected. Multiple logistic regression was used to evaluate the association between SAP and GIB. Kruskal-Wallis test was used to compare the time intervals from stroke onset to diagnosis of SAP and GIB. RESULTS: A total of 1129 patients with ischemic stroke were included. The median length of hospitalization was 14 days. Overall, 86 patients (7.6%; 95% CI, 6.1-9.2%) developed SAP and 47 patients (4.3%; 95% CI, 3.0-5.3%) developed GIB during hospitalization. After adjusting potential confounders, SAP was significantly associated with the development of GIB after ischemic stroke (OR = 5.13; 95% CI, 2.02-13.00; P < 0.001). The median time from stroke onset to diagnosis of SAP was shorter than that of GIB after ischemic stroke (4 days vs. 5 days; P = 0.039). CONCLUSIONS: SAP was associated with GIB after ischemic stroke, and the onset time of SAP was earlier than that of GIB. It is imperative to take precautions to prevent GIB in stroke patients with SAP.

Uncovering the burden of Influenza in children in Portugal, 2008-2018.

BACKGROUND: Despite their higher risk of developing severe disease, little is known about the burden of influenza in Portugal in children aged < 5 years old. This study aims to cover this gap by estimating the clinical and economic burden of severe influenza in children, in Portugal, during ten consecutive influenza seasons (2008/09-2017/18). METHODS: We reviewed hospitalizations in children aged < 5 years old using anonymized administrative data covering all public hospitals discharges in mainland Portugal. The burden of hospitalization and in-hospital mortality directly coded as due to influenza was supplemented by the indirect burden calculated from excess hospitalization and mortality (influenza-associated), estimated for four groups of diagnoses (pneumonia or influenza, respiratory, respiratory or cardiovascular, and all-cause), through cyclic regression models integrating the incidence of influenza. Means were reported excluding the H1N1pdm09 pandemic (2009/10). RESULTS: The mean annual number of hospitalizations coded as due to influenza was 189 (41.3 cases per 100,000 children aged < 5 years old). Hospitalization rates decreased with increasing age. Nine-in-ten children were previously healthy, but the presence of comorbidities increased with age. Children stayed, on average, 6.1 days at the hospital. Invasive mechanical ventilation was used in 2.4% of hospitalizations and non-invasive in 3.1%. Influenza-associated excess hospitalizations between 2008 and 2018 were estimated at 1,850 in pneumonia or influenza, 1,760 in respiratory, 1,787 in respiratory or cardiovascular, and 1,879 in all-cause models. A total of 95 influenza-associated excess deaths were estimated in all-cause, 14 in respiratory or cardiovascular, and 9 in respiratory models. Over ten years, influenza hospitalizations were estimated to have cost the National Health Service at least €2.9 million, of which 66.5% from healthy children. CONCLUSIONS: Influenza viruses led to a high number of hospitalizations in children. Most were previously healthy. Results should lead to a reflection on the adequate preventive measures to protect this age group.

Hospitalization, case fatality, comorbidities, and isolated pathogens of adult inpatients with pneumonia from 2013 to 2022: a real-world study in Guangzhou, China.

BACKGROUND: In the context of increasing population aging, ongoing drug-resistant pathogens and the COVID-19 epidemic, the changes in the epidemiological and clinical characteristics of patients with pneumonia remain unclear. This study aimed to assess the trends in hospitalization, case fatality, comorbidities, and isolated pathogens of pneumonia-related adult inpatients in Guangzhou during the last decade. METHODS: We retrospectively enrolled hospitalized adults who had doctor-diagnosed pneumonia in the First Affiliated Hospital of Guangzhou Medical University from January 1, 2013 to December 31, 2022. A natural language processing system was applied to automatically extract the clinical data from electronic health records. We evaluated the proportion of pneumonia-related hospitalizations in total hospitalizations, pneumonia-related in-hospital case fatality, comorbidities, and species of isolated pathogens during the last decade. Binary logistic regression analysis was used to assess predictors for patients with prolonged length of stay (LOS). RESULTS: A total of 38,870 cases were finally included in this study, with 70% males, median age of 64 (53, 73) years and median LOS of 7.9 (5.1, 12.8) days. Although the number of pneumonia-related hospitalizations showed an upward trend, the proportion of pneumonia-related hospitalizations decreased from 199.6 per 1000 inpatients in 2013 to 123.4 per 1000 in 2021, and the case fatality decreased from 50.2 per 1000 in 2013 to 23.9 per 1000 in 2022 (all P < 0.05). The most common comorbidities were chronic obstructive pulmonary disease, lung malignancy, cardiovascular diseases and diabetes. The most common pathogens were Pseudomonas aeruginosa, Candida albicans, Acinetobacter baumannii, Stenotrophomonas maltophilia, Klebsiella pneumoniae, and Staphylococcus aureus. Glucocorticoid use during hospitalization (Odd Ratio [OR] = 1.86, 95% Confidence Interval (CI): 1.14-3.06), immunosuppressant use during hospitalization (OR = 1.99, 1.14-3.46), ICU admission (OR = 16.23, 95%CI: 11.25-23.83), receiving mechanical ventilation (OR = 3.58, 95%CI: 2.60-4.97), presence of other underlying diseases (OR = 1.54, 95%CI: 1.15-2.06), and elevated procalcitonin (OR = 1.61, 95%CI: 1.19-2.19) were identified as independent predictors for prolonged LOS. CONCLUSION: The proportion of pneumonia-related hospitalizations and the in-hospital case fatality showed downward trends during the last decade. Pneumonia inpatients were often complicated by chronic underlying diseases and isolated with gram-negative bacteria. ICU admission was a significant predictor for prolonged LOS in pneumonia inpatients.

Associations of MMP9 polymorphism with the risk of severe pneumonia in a Southern Chinese children population.

BACKGROUND: Severe pneumonia frequently causes irreversible sequelae and represents a major health burden for children under the age of 5. Matrix Metallopeptidase 9 (MMP9) is a zinc-dependent endopeptidase that is involved in various cellular processes. The correlation between MMP9 and the risk of severe childhood pneumonia remains unclear. METHODS: Here we assemble a case-control cohort to study the association of genetic variants in MMP9 gene with severe childhood pneumonia susceptibility in a Southern Chinese population (1034 cases and 8426 controls). RESULTS: Our results indicate that the allele G in rs3918262 SNP was significantly associated with an increased risk of severe pneumonia. Bioinformatic analyses by expression quantitative trait loci (eQTL), RegulomeDB and FORGEdb database analysis showed that rs3918262 SNP has potential regulatory effect on translational efficiency and protein level of MMP9 gene. Furthermore, MMP9 concentrations were significantly up-regulated in the bronchoalveolar lavages (BALs) of children with severe pneumonia. CONCLUSION: In summary, our findings suggest that MMP9 is a novel predisposing gene for childhood pneumonia.

Impacts of environmental factors on the aetiological diagnosis and disease severity of community-acquired pneumonia in China: a multicentre, hospital-based, observational study.

Environmental exposures are known to be associated with pathogen transmission and immune impairment, but the association of exposures with aetiology and severity of community-acquired pneumonia (CAP) are unclear. A retrospective observational study was conducted at nine hospitals in eight provinces in China from 2014 to 2019. CAP patients were recruited according to inclusion criteria, and respiratory samples were screened for 33 respiratory pathogens using molecular test methods. Sociodemographic, environmental and clinical factors were used to analyze the association with pathogen detection and disease severity by logistic regression models combined with distributed lag nonlinear models. A total of 3323 CAP patients were included, with 709 (21.3%) having severe illness. 2064 (62.1%) patients were positive for at least one pathogen. More severe patients were found in positive group. After adjusting for confounders, particulate matter (PM) 2.5 and 8-h ozone (O3-8h) were significant association at specific lag periods with detection of influenza viruses and Klebsiella pneumoniae respectively. PM10 and carbon monoxide (CO) showed cumulative effect with severe CAP. Pollutants exposures, especially PM, O3-8h, and CO should be considered in pathogen detection and severity of CAP to improve the clinical aetiological and disease severity diagnosis.

Spectrum and antimicrobial resistance in acute exacerbation of chronic obstructive pulmonary disease with pneumonia: a cross-sectional prospective study from Vietnam.

BACKGROUND: Respiratory infections have long been recognized as a primary cause of acute exacerbation of chronic obstructive pulmonary disease (AE-COPD). Additionally, the emergence of antimicrobial resistance has led to an urgent and critical situation in developing countries, including Vietnam. This study aimed to investigate the distribution and antimicrobial resistance of bacteria in patients with AE-COPD using both conventional culture and multiplex real-time PCR. Additionally, associations between clinical characteristics and indicators of pneumonia in these patients were examined. METHODS: This cross-sectional prospective study included 92 AE-COPD patients with pneumonia and 46 without pneumonia. Sputum specimens were cultured and examined for bacterial identification, and antimicrobial susceptibility was determined for each isolate. Multiplex real-time PCR was also performed to detect ten bacteria and seven viruses. RESULTS: The detection rates of pathogens in AE-COPD patients with pneumonia were 92.39%, compared to 86.96% in those without pneumonia. A total of 26 pathogenic species were identified, showing no significant difference in distribution between the two groups. The predominant bacteria included Klebsiella pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, and Streptococcus pneumoniae, followed by Acinetobacter baumannii and Streptococcus mitis. There was a slight difference in antibiotic resistance between bacteria isolated from two groups. The frequency of H. influenzae was notably greater in AE-COPD patients who experienced respiratory failure (21.92%) than in those who did not (9.23%). S. pneumoniae was more common in patients with stage I (44.44%) or IV (36.36%) COPD than in patients with stage II (17.39%) or III (9.72%) disease. ROC curve analysis revealed that C-reactive protein (CRP) levels could distinguish patients with AE-COPD with and without pneumonia (AUC = 0.78). CONCLUSION: Gram-negative bacteria still play a key role in the etiology of AE-COPD patients, regardless of the presence of pneumonia. This study provides updated evidence for the epidemiology of AE-COPD pathogens and the appropriate selection of antimicrobial agents in Vietnam.