Identification of priority pathogens for aetiological diagnosis in adults with community-acquired pneumonia in China: a multicentre prospective study.

BACKGROUND: Community-acquired pneumonia (CAP) is a major public health challenge worldwide. However, the aetiological and disease severity-related pathogens associated with CAP in adults in China are not well established based on the detection of both viral and bacterial agents. METHODS: A multicentre, prospective study was conducted involving 10 hospitals located in nine geographical regions in China from 2014 to 2019. Sputum or bronchoalveolar lavage fluid (BALF) samples were collected from each recruited CAP patient. Multiplex real-time PCR and bacteria culture methods were used to detect respiratory pathogens. The association between detected pathogens and CAP severity was evaluated. RESULTS: Among the 3,403 recruited eligible patients, 462 (13.58%) had severe CAP, and the in-hospital mortality rate was 1.94% (66/3,403). At least one pathogen was detected in 2,054 (60.36%) patients, with two or more pathogens were co-detected in 725 patients. The ten major pathogens detected were Mycoplasma pneumoniae (11.05%), Haemophilus influenzae (10.67%), Klebsiella pneumoniae (10.43%), influenza A virus (9.49%), human rhinovirus (9.02%), Streptococcus pneumoniae (7.43%), Staphylococcus aureus (4.50%), adenovirus (2.94%), respiratory syncytial viruses (2.35%), and Legionella pneumophila (1.03%), which accounted for 76.06-92.52% of all positive detection results across sampling sites. Klebsiella pneumoniae (p < 0.001) and influenza viruses (p = 0.005) were more frequently detected in older patients, whereas Mycoplasma pneumoniae was more frequently detected in younger patients (p < 0.001). Infections with Klebsiella pneumoniae, Staphylococcus aureus, influenza viruses and respiratory syncytial viruses were risk factors for severe CAP. CONCLUSIONS: The major respiratory pathogens causing CAP in adults in China were different from those in USA and European countries, which were consistent across different geographical regions over study years. Given the detection rate of pathogens and their association with severe CAP, we propose to include the ten major pathogens as priorities for clinical pathogen screening in China.

Severe community-acquired pneumonia.

Severe community-acquired pneumonia is the most life-threatening form of community-acquired pneumonia, characterised by intensive care unit admission and high morbidity and mortality. In this review article, we cover in depth six aspects of severe community-acquired pneumonia that are still controversial: use of PCR molecular techniques for microbial diagnosis; the role of biomarkers for initial management; duration of treatment, macrolides or quinolones in the initial empirical antibiotic therapy; the use of prediction scores for drug-resistant pathogens to modify initial empiric therapy; the use of noninvasive mechanical ventilation and high-flow nasal oxygen; and the use of corticosteroids as adjunctive therapy in severe community-acquired pneumonia.

Computed tomography-based COVID-19 triage through a deep neural network using mask-weighted global average pooling.

Background: There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVID-19 triage based on chest computed tomography (CT) images, including normal, pneumonia, and COVID-19 cases. Methods: A total of 2,809 chest CT scans (1,105 COVID-19, 854 normal, and 850 non-3COVID-19 pneumonia cases) were acquired for this study and classified into the training set (n = 2,329) and test set (n = 480). A U-net-based convolutional neural network was used for lung segmentation, and a mask-weighted global average pooling (GAP) method was proposed for the deep neural network to improve the performance of COVID-19 classification between COVID-19 and normal or common pneumonia cases. Results: The results for lung segmentation reached a dice value of 96.5% on 30 independent CT scans. The performance of the mask-weighted GAP method achieved the COVID-19 triage with a sensitivity of 96.5% and specificity of 87.8% using the testing dataset. The mask-weighted GAP method demonstrated 0.9% and 2% improvements in sensitivity and specificity, respectively, compared with the normal GAP. In addition, fusion images between the CT images and the highlighted area from the deep learning model using the Grad-CAM method, indicating the lesion region detected using the deep learning method, were drawn and could also be confirmed by radiologists. Conclusions: This study proposed a mask-weighted GAP-based deep learning method and obtained promising results for COVID-19 triage based on chest CT images. Furthermore, it can be considered a convenient tool to assist doctors in diagnosing COVID-19.

Comparison of systemic inflammatory profiles in COVID-19 and community-acquired pneumonia patients: a prospective cohort study.

BACKGROUND: Inflammatory responses contribute to tissue damage in COVID-19 and community-acquired pneumonia (CAP). Although predictive values of different inflammatory biomarkers have been reported in both, similarities and differences of inflammatory profiles between these conditions remain uncertain. Therefore, we aimed to determine the similarities and differences of the inflammatory profiles between COVID-19 and CAP, and their association with clinical outcomes. METHODS: We report a prospective observational cohort study; conducted in a reference hospital in Latin America. Patients with confirmed COVID-19 pneumonia and CAP were included. Multiplex (Luminex) cytokine assays were used to measure the plasma concentration of 14 cytokines at hospital admission. After comparing similarities and differences in the inflammatory profile between COVID-19 and CAP patients, an unsupervised classification method (i.e., hierarchical clustering) was used to identify subpopulations within COVID-19 and CAP patients. RESULTS: A total of 160 patients were included, 62.5% were diagnosed with COVID-19 (100/160), and 37.5% with CAP (60/160). Using the hierarchical clustering, COVID-19 and CAP patients were divided based on its inflammatory profile: pauci, moderate, and hyper-inflammatory immune response. COVID-19 hyper-inflammatory subpopulation had the highest mortality. COVID-19 hyper-inflammatory subpopulation, compared to pauci-inflammatory, had higher levels of IL-10 (median [IQR] 61.4 [42.0-109.4] vs 13.0 [5.0-24.9], P: < 0.001), IL-6 (48.1 [22.3-82.6] vs 9.1 [0.1-30.4], P: < 0.001), among others. Hyper-inflammatory vs pauci-inflammatory CAP patients were characterized by elevation of IFN2 (48.8 [29.7-110.5] vs 3.0 [1.7-10.3], P: < 0.001), TNFα (36.3 [24.8-53.4] vs 13.1 [11.3-16.9], P: < 0.001), among others. Hyper-inflammatory subpopulations in COVID-19 and CAP compared to the corresponding pauci-inflammatory subpopulations had higher MCP-1. CONCLUSIONS: Our data highlights three distinct subpopulations in COVID-19 and CAP, with differences in inflammatory marker profiles and risks of adverse clinical outcomes. TRIAL REGISTRATION: This is a prospective study, therefore no health care intervention were applied to participants and trial registration is not applicable.

Healthcare-seeking behavior for respiratory illnesses in Kenya: implications for burden of disease estimation.

BACKGROUND: Understanding healthcare-seeking patterns for respiratory illness can help improve estimation of disease burden and target public health interventions to control acute respiratory disease in Kenya. METHODS: We conducted a cross-sectional survey to determine healthcare utilization patterns for acute respiratory illness (ARI) and severe pneumonia in four diverse counties representing urban, peri-urban, rural mixed farmers, and rural pastoralist communities in Kenya using a two-stage (sub-locations then households) cluster sampling procedure. Healthcare seeking behavior for ARI episodes in the last 14 days, and severe pneumonia in the last 12 months was evaluated. Severe pneumonia was defined as reported cough and difficulty breathing for > 2 days and report of hospitalization or recommendation for hospitalization, or a danger sign (unable to breastfeed/drink, vomiting everything, convulsions, unconscious) for children < 5 years, or report of inability to perform routine chores. RESULTS: From August through September 2018, we interviewed 28,072 individuals from 5,407 households. Of those surveyed, 9.2% (95% Confidence Interval [CI] 7.9-10.7) reported an episode of ARI, and 4.2% (95% CI 3.8-4.6) reported an episode of severe pneumonia. Of the reported ARI cases, 40.0% (95% CI 36.8-43.3) sought care at a health facility. Of the74.2% (95% CI 70.2-77.9) who reported severe pneumonia and visited a medical health facility, 28.9% (95% CI 25.6-32.6) were hospitalized and 7.0% (95% CI 5.4-9.1) were referred by a clinician to the hospital but not hospitalized. 21% (95% CI 18.2-23.6) of self-reported severe pneumonias were hospitalized. Children aged < 5 years and persons in households with a higher socio-economic status were more likely to seek care for respiratory illness at a health facility. CONCLUSION: Our findings suggest that hospital-based surveillance captures less than one quarter of severe pneumonia in the community. Multipliers from community household surveys can account for underutilization of healthcare resources and under-ascertainment of severe pneumonia at hospitals.

Assessment of the pneumonia severity score in community-acquired and nursing and healthcare-associated pneumonia due to COVID-19.

INTRODUCTION: The Japanese Respiratory Society (JRS) pneumonia guidelines recommend simple predictive rules, the A-DROP scoring system, for assessment of the severity of community-acquired pneumonia (CAP) and nursing and healthcare-associated pneumonia (NHCAP). We evaluated whether the A-DROP system can be adapted for assessment of the severity of coronavirus disease 2019 (COVID-19) pneumonia. METHODS: Data from 1141 patients with COVID-19 pneumonia were analyzed, comprising 502 patients observed in the 1st to 3rd wave period, 338 patients in the 4th wave and 301 patients in the 5th wave in Japan. RESULTS: The mortality rate and mechanical ventilation rate were 0% and 1.4% in patients classified with mild disease (A-DROP score, 0 point), 3.2% and 46.7% in those with moderate disease (1 or 2 points), 20.8% and 78.3% with severe disease (3 points), and 55.0% and 100% with extremely severe disease (4 or 5 points), indicating an increase in the mortality and mechanical ventilation rates in accordance with severity (Cochran-Armitage trend test; p = <0.001). This significant relationship between the severity in the A-DROP scoring system and either the mortality rate or mechanical ventilation rate was observed in patients with COVID-19 CAP and NHCAP. In each of the five COVID-19 waves, the same significant relationship was observed. CONCLUSIONS: The mortality rate and mechanical ventilation rate in patients with COVID-19 pneumonia increased depending on severity classified according to the A-DROP scoring system. Our results suggest that the A-DROP scoring system can be adapted for the assessment of severity of COVID-19 CAP and NHCAP.

[Advances in epidemiology, etiology, and treatment of community-acquired pneumonia].

Community-acquired pneumonia (CAP) is the third leading cause of death worldwide and one of the most commonly infectious diseases. Its epidemiological characteristics vary with host and immune status, and corresponding pathogen spectrums migrate over time and space distribution. Meanwhile, with the outbreak of COVID-19, some unconventional treatment strategies are on the rise. This article reviewed the epidemiological characteristics, pathogen spectrum and treatment direction of CAP in China over the years, and aimed to provide guidance for the diagnosis and treatment of CAP in clinical practice.

Management of Unique Pneumonias Seen in the Intensive Care Unit.

Infection of the lower respiratory tract is a potentially severe or life-threatening illness. Taking the right steps to recognize, identify, and treat pneumonia is critical to improving patient outcomes. An awareness of the diversity of potential infectious causes, the local endemic flora and resistance patterns, as well as testing strategies to differentiate causes of pneumonia is essential to providing the best patient outcomes. Understanding surveillance definitions allow intensivists to become partners in reducing hospital-associated infections and improving quality of care.

Neutrophil count multiplied by D-dimer combined with pneumonia may better predict short-term outcomes in patients with acute ischemic stroke.

OBJECTIVE: To investigate the predictive value of neutrophil, D-dimer and diseases associated with stroke for short-term outcomes of acute ischemic stroke (AIS). METHODS: By collecting the subitems of laboratory data especially routine blood and coagulation test in AIS patients, and recording their clinical status, the correlation, regression and predictive value of each subitem with the short-term outcomes of AIS were analyzed. The predict model was constructed. RESULTS: The neutrophil count multiplied by D-dimer (NDM) had the best predictive value among the subitems, and the area under the receiver operating characteristic (ROC) curve reached 0.804. When clinical information was not considered, the Youden index of NDM was calculated to be 0.48, corresponding to an NDM value of 7.78, a diagnostic sensitivity of 0.79, specificity of 0.69, negative predictive value of 96%. NDM were divided into 5 quintiles, the five grade of NDM (quintile) were < = 1.82, 1.83-2.41, 2.42-3.27, 3.28-4.49, 4.95+, respectively. The multivariate regression analysis was conducted between NDM (quintile), Babinski+, pneumonia, cardiac disease and poor outcomes of AIS. Compared with the first grade of NDM (quintile), the second grade of NDM (quintile) was not significant, but the third grade of NDM (quintile) showed 7.061 times, the fourth grade of NDM (quintile) showed 11.776 times, the fifth grade of NDM (quintile) showed 23.394 times in short-term poor outcomes occurrence. Babinski sign + showed 1.512 times, pneumonia showed 2.995 times, cardiac disease showed 1.936 times in short-term poor outcomes occurrence compared with those negative patients. CONCLUSIONS: NDM combined with pneumonia may better predict short-term outcomes in patients with AIS. Early prevention, regular examination and timely intervention should be emphasized for patients, which may reduce the risk of short-term poor outcomes.

Galectin-3 as a Novel Biomarker for Predicting Clinical Outcomes in Hospitalized COVID-19 Patients.

BACKGROUND: Galectin-3 has been shown to play a key pathophysiological role in pulmonary associated inflammatory response and lung fibrosis in COVID-19 and is a mediator for viral adhesion. However, there is limited data about its potential role in severity and prognosis of COVID-19. This study aimed to investigate the predictive role of serum galectin-3 concentrations in the severe clinical outcomes of hospitalized COVID-19 patients: the severity of pneumonia, in-hospital mortality, and the need for intensive care unit (ICU) admission. METHODS: This single-center study included 68 patients with laboratory- and radiologically-confirmed COVID-19 admitted to our emergency department. The study population was divided into patients with primary clinical out-comes (n = 32) and those without (n = 36). The need for ICU admission and/or in-hospital mortality were the primary clinical endpoints. The study group was also classified based on pneumonia severity: severe or mild/moderate. Blood samples were collected within 48 hours of admission to estimate serum galectin-3 concentrations. RESULTS: Multivariate regression analysis showed that lower concentrations of galectin-3 and arterial oxygen saturation (SpO2) were independently associated with the primary clinical outcomes (OR = 0.951, p = 0.035; OR = 0.862, p = 0.017, respectively); increased concentrations of galectin-3 were an independent predictor of severe pneumonia (OR = 1.087, p = 0.016). In the receiver operating characteristics curve analysis, serum galectin-3 concentrations at hospital admission predicted pneumonia severity with 52.1% sensitivity and 90% specificity with a cutoff of 38.76 ng/mL. CONCLUSIONS: Circulating galectin-3 at hospital admission could be a useful biomarker for identifying COVID-19 patients at high risk for severe pneumonia.

Community-Acquired Pneumonia: Postpandemic, Not Post-COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic upended our approach to imaging community-acquired pneumonia, and this will alter our diagnostic algorithms for years to come. In light of these changes, it is worthwhile to consider several postpandemic scenarios of community-acquired pneumonia: (1) patient with pneumonia and recent positive COVID-19 testing; (2) patient with air space opacities and history of prior COVID-19 pneumonia (weeks earlier); (3) multifocal pneumonia with negative or unknown COVID-19 status; and (4) lobar or sublobar pneumonia with negative or unknown COVID-19 status. In the setting of positive COVID-19 testing and typical radiologic findings, the diagnosis of COVID-19 pneumonia is generally secure. The diagnosis prompts vigilance for thromboembolic disease acutely and, in severely ill patients, for invasive fungal disease. Persistent or recurrent air space opacities following COVID-19 infection may more often represent organizing pneumonia than secondary infection. When COVID-19 status is unknown or negative, widespread airway-centric disease suggests infection with mycoplasma, Haemophilus influenzae, or several respiratory viruses. Necrotizing pneumonia favors infection with pneumococcus, Staphylococcus, Klebsiella, and anaerobes. Lobar or sublobar pneumonia will continue to suggest the diagnosis of pneumococcus or consideration of other pathogens in the setting of local outbreaks. A positive COVID-19 test accompanied by these imaging patterns may suggest coinfection with one of the above pathogens, or when the prevalence of COVID-19 is very low, a false positive COVID-19 test. Clinicians may still proceed with testing for COVID-19 when radiologic patterns are atypical for COVID-19, dependent on the patient's exposure history and the local epidemiology of the virus.

External Validation and Recalibration of the CURB-65 and PSI for Predicting 30-Day Mortality and Critical Care Intervention in Multiethnic Patients with COVID-19.

OBJECTIVES: To validate and recalibrate the CURB-65 and pneumonia severity index (PSI) in predicting 30-day mortality and critical care intervention (CCI) in a multiethnic population with COVID-19, along with evaluating both models in predicting CCI. METHODS: Retrospective data was collected for 1181 patients admitted to the largest hospital in Qatar with COVID-19 pneumonia. The area under the curve (AUC), calibration curves, and other metrics were bootstrapped to examine the performance of the models. Variables constituting the CURB-65 and PSI scores underwent further analysis using the Least Absolute Shrinkage and Selection Operator (LASSO) along with logistic regression to develop a model predicting CCI. Complex machine learning models were built for comparative analysis. RESULTS: The PSI performed better than CURB-65 in predicting 30-day mortality (AUC 0.83, 0.78 respectively), while CURB-65 outperformed PSI in predicting CCI (AUC 0.78, 0.70 respectively). The modified PSI/CURB-65 model (respiratory rate, oxygen saturation, hematocrit, age, sodium, and glucose) predicting CCI had excellent accuracy (AUC 0.823) and good calibration. CONCLUSIONS: Our study recalibrated, externally validated the PSI and CURB-65 for predicting 30-day mortality and CCI, and developed a model for predicting CCI. Our tool can potentially guide clinicians in Qatar to stratify patients with COVID-19 pneumonia.

[Organizing pneumonia as a pulmonary manifestation of post-COVID syndrome: features of diagnosis and treatment].

Treatment of patients with long-term persistent symptoms after COVID-19 is an urgent problem for clinicians around the world. One of the most significant manifestations of post-COVID-19 syndrome is organizing pneumonia that is usually treat with corticosteroids. The paper presents a clinical case of typical course of post-COVID-19 organizing pneumonia in a patient without previous lung disease. Risk factors, diagnostic methods and treatment options in this group of patients are also discuss.

How and when to manage respiratory infections out of hospital.

Lower respiratory infections include acute bronchitis, influenza, community-acquired pneumonia, acute exacerbation of COPD and acute exacerbation of bronchiectasis. They are a major cause of death worldwide and often affect the most vulnerable: children, elderly and the impoverished. In this paper, we review the clinical presentation, diagnosis, severity assessment and treatment of adult outpatients with lower respiratory infections. The paper is divided into sections on specific lower respiratory infections, but we also dedicate a section to COVID-19 given the importance of the ongoing pandemic. Lower respiratory infections are heterogeneous entities, carry different risks for adverse events, and require different management strategies. For instance, while patients with acute bronchitis are rarely admitted to hospital and generally do not require antimicrobials, approximately 40% of patients seen for community-acquired pneumonia require admission. Clinicians caring for patients with lower respiratory infections face several challenges, including an increasing population of patients with immunosuppression, potential need for diagnostic tests that may not be readily available, antibiotic resistance and social aspects that place these patients at higher risk. Management principles for patients with lower respiratory infections include knowledge of local surveillance data, strategic use of diagnostic tests according to surveillance data, and judicious use of antimicrobials.

Human-to-human transmission of Chlamydia psittaci in China, 2020: an epidemiological and aetiological investigation.

BACKGROUND: Chlamydia psittaci can infect a wide range of avian species, occasionally causing psittacosis (also known as parrot fever) in humans. Most human psittacosis cases are associated with close contact with pet birds or poultry. In December, 2020, an outbreak of severe community-acquired pneumonia of unknown aetiology was reported in a hospital in Shandong province, China, and some of the patients' close contacts had respiratory symptoms. Our aims were to determine the causative agent of this epidemic and whether there had been human-to-human transmission. METHODS: For this epidemiological and aetiological investigation study, we enrolled patients who had community-acquired pneumonia confirmed by chest CT at two local hospitals in Shandong Province in China. We collected sputum, bronchoalveolar lavage fluid, and nasopharyngeal swab samples from participants and detected pathogens by surveying for 22 target respiratory microbes using a commercial assay, followed by metagenomic next-generation sequencing, specific nested PCR, and qPCR tests. We excluded individuals who were C psittaci-negative on both tests. We recruited close contacts of the C psittaci-positive patients, and tested nasopharyngeal swabs from the close contacts and samples from ducks from the processing plant where these patients worked. We then integrated the epidemiological, clinical, and laboratory data to reveal the potential chain of transmission of C psittaci that characterised this outbreak. FINDINGS: Between Dec 4 and 29, 2020, we used metagenomic next-generation sequencing and different PCR-based approaches to test 12 inpatients with community-acquired pneumonia, of whom six (50%) were workers at a duck-meat processing plant and two (17%) were unemployed people, who were positive for C psittaci and enrolled in this study. We contacted 61 close contacts of the six patients who worked at the duck-meat processing plant, of whom 61 (100%) were enrolled and tested, and we determined that the community-acquired pneumonia outbreak was caused by C psittaci. Within the outbreak cluster, 17 (77%) of 22 participants had confirmed C psittaci infections and five (23%) of 22 participants were asymptomatic C psittaci carriers. The outbreak had begun with avian-to-human transmission, and was followed by secondary and tertiary human-to-human transmission, which included transmission by several asymptomatic carriers and by health-care workers. In addition, some of the participants with confirmed C psittaci infection had no identified source of infection, which suggested cryptic bacterial transmission. INTERPRETATION: Our study data might represent the first documented report of human-to-human transmission of C psittaci in China. Therefore, C psittaci has the potential to evolve human-to-human transmission via various routes, should be considered an elevated biosecurity and emergent risk, and be included as part of the routine diagnosis globally, especially for high-risk populations. FUNDING: Academic Promotion Programme of Shandong First Medical University, National Science and Technology Major Project, ARC Australian Laureate Fellowship.

Utility of Differential White Cell Count and Cell Population Data for Ruling Out COVID-19 Infection in Patients With Community-Acquired Pneumonia.

INTRODUCTION: The main aim of this study was to assess the utility of differential white cell count and cell population data (CPD) for the detection of COVID-19 in patients admitted for community-acquired pneumonia (CAP) of different etiologies. METHODS: This was a multicenter, observational, prospective study of adults aged ≥18 years admitted to three teaching hospitals in Spain from November 2019 to November 2021 with a diagnosis of CAP. At baseline, a Sysmex XN-20 analyzer was used to obtain detailed information related to the activation status and functional activity of white cells. RESULTS: The sample was split into derivation and validation cohorts of 1065 and 717 patients, respectively. In the derivation cohort, COVID-19 was confirmed in 791 patients and ruled out in 274 patients, with mean ages of 62.13 (14.37) and 65.42 (16.62) years, respectively (p<0.001). There were significant differences in all CPD parameters except MO-Y. The multivariate prediction model showed that lower NE-X, NE-WY, LY-Z, LY-WY, MO-WX, MO-WY, and MO-Z values and neutrophil-to-lymphocyte ratio were related to COVID-19 etiology with an AUC of 0.819 (0.790, 0.846). No significant differences were found comparing this model to another including biomarkers (p=0.18). CONCLUSIONS: Abnormalities in white blood cell morphology based on a few cell population data values as well as NLR were able to accurately identify COVID-19 etiology. Moreover, systemic inflammation biomarkers currently used were unable to improve the predictive ability. We conclude that new peripheral blood biomarkers can help determine the etiology of CAP fast and inexpensively.

Feasibility of establishing acute respiratory infection treatment units (ATU) for improvement of care of children with acute respiratory infection.

BACKGROUND: Acute respiratory infections (ARI) are the leading cause of morbidity and mortality in children below 5 years of age. METHODS: This multisite prospective observational study was carried out in the Pediatrics' out-patient departments of 5 medical colleges across India with an objective to assess the feasibility of establishing Acute Respiratory Infection Treatment Unit (ATU) in urban medical college hospitals. ATU (staffed with a nurse and a medical officer) was established in the out-patient areas at study sites. Children, aged 2-59 months, with cough and/ breathing difficulty for < 14 days were screened by study nurse in the ATU for pneumonia, severe pneumonia or no pneumonia. Diagnosis was verified by study doctor. Children were managed as per the World Health Organization (WHO) guidelines. The key outcomes were successful establishment of ATUs, antibiotic usage, treatment outcomes. RESULTS: ATUs were successfully established at the 5 study sites. Of 18,159 under-five children screened, 7026 (39%) children were assessed to have ARI. Using the WHO criteria, 938 were diagnosed as pneumonia (13.4%) and of these, 347 (36.9%) had severe pneumonia. Ambulatory home-based management was done in 6341 (90%) children with ARI; of these, 16 (0.25%) required admission because of non-response or deterioration on follow-up. Case-fatality rate in severe pneumonia was 2%. Nearly 12% of children with 'no pneumonia' received antibiotics. CONCLUSIONS: Setting up of ATUs dedicated to management of ARI in children was feasible in urban medical colleges. The observed case fatality, and rate of unnecessary use of antibiotics were lower than that reported in literature.

Development and validation of the predictive score for pediatric COVID-19 pneumonia: A nationwide, multicenter study.

BACKGROUND: Due to the possibility of asymptomatic pneumonia in children with COVID-19 leading to overexposure to radiation and problems in limited-resource settings, we conducted a nationwide, multi-center study to determine the risk factors of pneumonia in children with COVID-19 in order to create a pediatric pneumonia predictive score, with score validation. METHODS: This was a retrospective cohort study done by chart review of all children aged 0-15 years admitted to 13 medical centers across Thailand during the study period. Univariate and multivariate analyses as well as backward and forward stepwise logistic regression were used to generate a final prediction model of the pneumonia score. Data during the pre-Delta era was used to create a prediction model whilst data from the Delta one was used as a validation cohort. RESULTS: The score development cohort consisted of 1,076 patients in the pre-Delta era, and the validation cohort included 2,856 patients in the Delta one. Four predictors remained after backward and forward stepwise logistic regression: age < 5 years, number of comorbidities, fever, and dyspnea symptoms. The predictive ability of the novel pneumonia score was acceptable with the area under the receiver operating characteristics curve of 0.677 and a well-calibrated goodness-of-fit test (p = 0.098). The positive likelihood ratio for pneumonia was 0.544 (95% confidence interval (CI): 0.491-0.602) in the low-risk category, 1.563 (95% CI: 1.454-1.679) in the moderate, and 4.339 (95% CI: 2.527-7.449) in the high-risk. CONCLUSION: This study created an acceptable clinical prediction model which can aid clinicians in performing an appropriate triage for children with COVID-19.

Unmet needs in pneumonia research: a comprehensive approach by the CAPNETZ study group.

INTRODUCTION: Despite improvements in medical science and public health, mortality of community-acquired pneumonia (CAP) has barely changed throughout the last 15 years. The current SARS-CoV-2 pandemic has once again highlighted the central importance of acute respiratory infections to human health. The "network of excellence on Community Acquired Pneumonia" (CAPNETZ) hosts the most comprehensive CAP database worldwide including more than 12,000 patients. CAPNETZ connects physicians, microbiologists, virologists, epidemiologists, and computer scientists throughout Europe. Our aim was to summarize the current situation in CAP research and identify the most pressing unmet needs in CAP research. METHODS: To identify areas of future CAP research, CAPNETZ followed a multiple-step procedure. First, research members of CAPNETZ were individually asked to identify unmet needs. Second, the top 100 experts in the field of CAP research were asked for their insights about the unmet needs in CAP (Delphi approach). Third, internal and external experts discussed unmet needs in CAP at a scientific retreat. RESULTS: Eleven topics for future CAP research were identified: detection of causative pathogens, next generation sequencing for antimicrobial treatment guidance, imaging diagnostics, biomarkers, risk stratification, antiviral and antibiotic treatment, adjunctive therapy, vaccines and prevention, systemic and local immune response, comorbidities, and long-term cardio-vascular complications. CONCLUSION: Pneumonia is a complex disease where the interplay between pathogens, immune system and comorbidities not only impose an immediate risk of mortality but also affect the patients' risk of developing comorbidities as well as mortality for up to a decade after pneumonia has resolved. Our review of unmet needs in CAP research has shown that there are still major shortcomings in our knowledge of CAP.