A nomogram predicting pneumonia after cardiac surgery: a retrospective modeling study.

BACKGROUND: Postoperative pneumonia (POP) is the most prevalent of all nosocomial infections in patients who underwent cardiac surgery. The aim of this study was to identify independent risk factors for pneumonia after cardiac surgery, from which we constructed a nomogram for prediction. METHODS: The clinical data of patients admitted to the Department of Cardiothoracic Surgery of Nanjing Drum Tower Hospital from October 2020 to September 2021 who underwent cardiac surgery were retrospectively analyzed, and the patients were divided into two groups according to whether they had POP: POP group (n=105) and non-POP group (n=1083). Preoperative, intraoperative, and postoperative indicators were collected and analyzed. Logistic regression was used to identify independent risk factors for POP in patients who underwent cardiac surgery. We constructed a nomogram based on these independent risk factors. Model discrimination was assessed via area under the receiver operating characteristic curve (AUC), and calibration was assessed via calibration plot. RESULTS: A total of 105 events occurred in the 1188 cases. Age (>55 years) (OR: 1.83, P=0.0225), preoperative malnutrition (OR: 3.71, P<0.0001), diabetes mellitus(OR: 2.33, P=0.0036), CPB time (Cardiopulmonary Bypass Time) > 135 min (OR: 2.80, P<0.0001), moderate to severe ARDS (Acute Respiratory Distress Syndrome )(OR: 1.79, P=0.0148), use of ECMO or IABP or CRRT (ECMO: Extra Corporeal Membrane Oxygenation; IABP: Intra-Aortic Balloon Pump; CRRT: Continuous Renal Replacement Therapy )(OR: 2.60, P=0.0057) and MV( Mechanical Ventilation )> 20 hours (OR: 3.11, P<0.0001) were independent risk factors for POP. Based on those independent risk factors, we constructed a simple nomogram with an AUC of 0.82. Calibration plots showed good agreement between predicted probabilities and actual probabilities. CONCLUSION: We constructed a facile nomogram for predicting pneumonia after cardiac surgery with good discrimination and calibration. The model has excellent clinical applicability and can be used to identify and adjust modifiable risk factors to reduce the incidence of POP as well as patient mortality.

Predictive significance of systemic immune-inflammation index combined with prealbumin for postoperative pneumonia following lung resection surgery.

BACKGROUND: We aimed to determine whether systemic immune-inflammation index (SII) combined with prealbumin can provide better predictive power for postoperative pneumonia in patients undergoing lung resection surgery. METHODS: We identified eligible patients undergoing lung resection surgery at the Affiliated Hospital of Nantong University from March 2021 to March 2022. Demographic characteristics, clinical data, and laboratory information were collected and reviewed from the electronic medical records of the patients. To test the effect of the combined detection of SII and prealbumin, we made an equation using logistic regression analysis. The receiver operating characteristic curve (ROC) was plotted to evaluate the predictive powers, sensitivity, and specificity of prealbumin, SII, and SII combined with prealbumin. Decision curve analysis (DCA) was used to determine the clinical validity and net benefit of different methods of detection. RESULTS: Totally 386 eligible patients were included with a median age of 62.0 years (IQR: 55.0, 68.0), and 57 (14.8%) patients presented with postoperative pneumonia within 7 days after surgery. The multivariate regression analysis showed that preoperative SII as continuous variable was associated with an increased risk of postoperative pneumonia (OR: 1.38, 95% CI: 1.19-2.83, P = 0.011), whereas the prealbumin as continuous variable remained as an independent protective predictor of postoperative pneumonia in the adjusted analysis (OR: 0.80, 95% CI: 0.37-0.89, P = 0.023). Compared to SII or prealbumin, the combined detection of preoperative SII and prealbumin showed a higher predictive power with area under curve of 0.79 (95% CI: 0.71-0.86, P < 0.05 for all). Additionally, DCA indicated that the combined detection was superior over preoperative SII or prealbumin alone in clinical validity and net benefit. CONCLUSION: Both preoperative SII and prealbumin are independent influencing factors for postoperative pneumonia after lung resection surgery. The combined detection of preoperative SII and prealbumin can significantly improve prediction capability to identify potential postoperative pneumonia-susceptible patients, facilitating early interventions to improve postoperative quality of life for surgical lung resection patients.

Neglected Mycobacterium Avium Complex Infection in a Patient with Prolonged Pneumonia.

BACKGROUND: Non-tuberculous mycobacterial pulmonary infections (NTM-PD) are becoming increasingly common in clinical practice, and early detection and accurate determination of the infecting pathogen is crucial for subsequent treatment. We report a case of NTM-PD in a healthy middle-aged female with Mycobacterium tuberculosis complex group (MAC) infection confirmed by mNGS examination. METHODS: Appropriate laboratory tests, chest CT scan, bronchoscopic alveolar lavage fluid (BALF) examination, and macrogenomic next-generation sequencing (mNGS) were performed to establish the diagnosis. RESULTS: Chest CT showed multiple inflammatory lesions in the right middle lobe, and BALF sent for mNGS finally confirmed the diagnosis of MAC infection. After symptomatic treatment with azithromycin combined with ethambutol and rifampicin, the patient improved and was discharged from the hospital. CONCLUSIONS: In patients with pulmonary infections, pathogens should be clarified early to determine the diagnosis. mNGS of BALF samples have high specificity in detecting pathogens of infectious diseases, especially complex mixed infectious disease pathogens.

Weil's disease with multiple organ dysfunction, community-acquired pneumonia and septic shock: The role of rapid diagnosis and management.

Leptospirosis is an uncommon infectious illness - a spirochetal zoonosis - caused by Leptospira species and the primary cause of human leptospirosis is exposure to the urine of infected rodents. Clinical manifestations of human leptospirosis are diverse, ranging from asymptomatic infection to severe life-threatening with multiorgan dysfunction. The severe condition is known as Weil's disease, which is characterized by feverish illness with jaundice, acute kidney damage, and bleeding. The aim of this case report was to present a Weil's disease which occurred simultaneously with a community-acquired pneumonia (CAP) resulting in serious complications. A 41-year-old man with Weil's disease, as well as CAP caused by Streptococcus pneumoniae, and septic shock was presented. The patient was treated accordingly after establishing the diagnosis through history taking, physical examination, and laboratory tests. In this instance, the score for diagnosing leptospirosis based on Modified Faine's Criteria was calculated resulting possible diagnoses; and therefore, therapeutic management was initiated. Despite presenting with severe symptoms, the patient recovered completely after receiving antibiotics and supportive care. This study highlights that when a patient has Weil's disease and a CAP infection, which could cause unfavorable consequence, a prompt diagnosis and proper treatment could result satisfied patient recovery.

Evaluation and clinical significance of serum neurospecific enolase in children with pneumonia: a case-control study.

BACKGROUND: Neurospecific Enolase (NSE), a multifunctional protein, is present in various tissues of the body and plays an important role in many disease processes, such as infection, inflammation, tumours, injury, and immunity. In recent years, the application of NSE in respiratory diseases has become increasingly widespread and a research hotspot. OBJECTIVE: This study aims to explore the relationship between NSE and childhood pneumonia, providing assistance for the diagnosis and assessment of pneumonia. METHODS: Using prospective research and case-control methods, We selected 129 children with pneumonia hospitalised in Weifang People's Hospital from September 2020 to April 2022 as the case group. Among them were 67 cases of Mycoplasma pneumoniae pneumonia (MP+), 62 cases of non-Mycoplasma pneumoniae pneumonia (MP -), and 21 cases of severe pneumonia. At the same time, 136 children who underwent outpatient health examinations were selected as the control group. The levels of NSE, ESR, CRP in cases group and NSE in control group were measured separately. RESULT: The NSE levels in the MP + group were 17.86 (14.29-22.54) ng/mL, while those in the MP- group were 17.89 (14.10-21.66) ng/mL, both of which were higher than the control group's NSE levels of 13.26(12.18,14.44) ng/mL (H = 46.92, P = 0.000). There was no statistically significant difference in NSE levels between the MP + and MP - groups (P > 0.05). The NSE level in the severe pneumonia group was 27.38 (13.95-34.06) ng/mL, higher than that in the mild pneumonia group, which was 17.68 (14.27-21.04) ng/mL, (P = 0.024). The AUC values for diagnosing pneumonia are NSE0.714, CRP0.539, and ESR0.535, with NSE having the highest diagnostic value. CONCLUSION: Serum NSE can serve as an inflammatory indicator for paediatric pneumonia, which has important clinical guidance significance for the diagnosis, condition evaluation, and prognosis of paediatric pneumonia.

Pulmonary Infection.

Pneumonia is a significant cause of morbidity and mortality in the community and hospital settings. Bacterial, viral, mycobacterial, and fungal pathogens are all potential causative agents of pulmonary infection. Chest radiographs and computed tomography are frequently utilized in the assessment of pneumonia. Learning the imaging patterns of different potential organisms allows the radiologist to formulate an appropriate differential diagnosis. An organism-based approach is used to discuss the imaging findings of different etiologies of pulmonary infection.

Snoring-generated fluid droplets as a potential mechanistic link between sleep-disordered breathing and pneumonia.

The soft palate and back of the throat represent vulnerable early infection sites for SARS-CoV-2, influenza, streptococci, and many other pathogens. We demonstrate that snoring causes aerosolization of pharyngeal fluid that covers these surfaces, which previously has escaped detection because the inspired airstream carries the micron-sized droplets into the lung, inaccessible to traditional aerosol detectors. While many of these droplets will settle in the lower respiratory tract, a fraction of the respirable smallest droplets remains airborne and can be detected in exhaled breath. We distinguished these exhaled droplets from those generated by the underlying breathing activity by using a chemical tracer, thereby proving their existence. The direct transfer of pharyngeal fluids and their pathogens into the deep lung by snoring represents a plausible mechanistic link between the previously recognized association between sleep-disordered breathing and pneumonia incidence.

Highly diverse sputum microbiota correlates with the disease severity in patients with community-acquired pneumonia: a longitudinal cohort study.

BACKGROUND: Community-acquired pneumonia (CAP) is a common and serious condition that can be caused by a variety of pathogens. However, much remains unknown about how these pathogens interact with the lower respiratory commensals, and whether any correlation exists between the dysbiosis of the lower respiratory microbiota and disease severity and prognosis. METHODS: We conducted a retrospective cohort study to investigate the composition and dynamics of sputum microbiota in patients diagnosed with CAP. In total, 917 sputum specimens were collected consecutively from 350 CAP inpatients enrolled in six hospitals following admission. The V3-V4 region of the 16 S rRNA gene was then sequenced. RESULTS: The sputum microbiota in 71% of the samples were predominately composed of respiratory commensals. Conversely, 15% of the samples demonstrated dominance by five opportunistic pathogens. Additionally, 5% of the samples exhibited sterility, resembling the composition of negative controls. Compared to non-severe CAP patients, severe cases exhibited a more disrupted sputum microbiota, characterized by the highly dominant presence of potential pathogens, greater deviation from a healthy state, more significant alterations during hospitalization, and sparser bacterial interactions. The sputum microbiota on admission demonstrated a moderate prediction of disease severity (AUC = 0.74). Furthermore, different pathogenic infections were associated with specific microbiota alterations. Acinetobacter and Pseudomonas were more abundant in influenza A infections, with Acinetobacter was also enriched in Klebsiella pneumoniae infections. CONCLUSION: Collectively, our study demonstrated that pneumonia may not consistently correlate with severe dysbiosis of the respiratory microbiota. Instead, the degree of microbiota dysbiosis was correlated with disease severity in CAP patients.

Community-acquired pneumonia: use of clinical characteristics of acutely admitted patients for the development of a diagnostic model - a cross-sectional multicentre study.

OBJECTIVES: This study aimed to describe the clinical characteristics of adults with suspected acute community-acquired pneumonia (CAP) on hospitalisation, evaluate their prediction performance for CAP and compare the performance of the model to the initial assessment of the physician. DESIGN: Cross-sectional, multicentre study. SETTING: The data originated from the INfectious DisEases in Emergency Departments study and were collected prospectively from patient interviews and medical records. The study included four Danish medical emergency departments (EDs) and was conducted between 1 March 2021 and 28 February 2022. PARTICIPANTS: A total of 954 patients admitted with suspected infection were included in the study. PRIMARY AND SECONDARY OUTCOME: The primary outcome was CAP diagnosis assessed by an expert panel. RESULTS: According to expert evaluation, CAP had a 28% prevalence. 13 diagnostic predictors were identified using least absolute shrinkage and selection operator regression to build the prediction model: dyspnoea, expectoration, cough, common cold, malaise, chest pain, respiratory rate (>20 breaths/min), oxygen saturation (<96%), abnormal chest auscultation, leucocytes (<3.5×109/L or >8.8×109/L) and neutrophils (>7.5×109/L). C reactive protein (<20 mg/L) and having no previous event of CAP contributed negatively to the final model. The predictors yielded good prediction performance for CAP with an area under the receiver-operator characteristic curve (AUC) of 0.85 (CI 0.77 to 0.92). However, the initial diagnosis made by the ED physician performed better, with an AUC of 0.86 (CI 84% to 89%). CONCLUSION: Typical respiratory symptoms combined with abnormal vital signs and elevated infection biomarkers were predictors for CAP on admission to an ED. The clinical value of the prediction model is questionable in our setting as it does not outperform the clinician's assessment. Further studies that add novel diagnostic tools and use imaging or serological markers are needed to improve a model that would help diagnose CAP in an ED setting more accurately. TRIAL REGISTRATION NUMBER: NCT04681963.

Incorporating preoperative frailty to assist in early prediction of postoperative pneumonia in elderly patients with hip fractures: an externally validated online interpretable machine learning model.

BACKGROUND: This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians. METHODS: Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model. RESULTS: The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841-0.949) and 0.835 (95%CI: 0.740-0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821-0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP. CONCLUSION: Our model's good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

LncRNA RP11-773H22.4 is upregulated in severe pneumonia and may be a diagnostic and prognostic marker for severe pneumonia.

The incidence of pneumonia has become increasingly prevalent, and its severity has been continuously escalating, bringing significant damage and stress to people's lives. The regulatory role of RP11-773H22.4 in the onset and development of severe pneumonia is emerging as an important factor, however, the exact mechanisms controlling its effects have not been fully elucidated. ROC curve and Kaplan-Meier curve were employed to assess the diagnostic and prognostic significance of RP11-773H22.4 in severe pneumonia. qRT-PCR was employed to assess the RP11-773H22.4 and miR-1287-5p expression. The CCK-8 was employed to assess cell viability. The rate of apoptosis was measured utilizing flow cytometric. The concentration of inflammatory factors was detected by ELISA kit. The interaction between RP11-773H22.4 and miR-1287-5p was verified by dual luciferase reporter gene assay. In individuals afflicted with severe pneumonia, there was an observed up-regulation in RP11-773H22.4 expression and a corresponding decline in miR-1287-5p expression. RP11-773H22.4 demonstrated diagnostic and prognostic significance for severe pneumonia. RP11-773H22.4 augmented the viability of MRC-5 cells with LPS treatment by modulating miR-1287-5p, leading to a reduction in apoptosis and lower levels of inflammatory cytokines. RP11-773H22.4 was highly expressed in severe pneumonia and may serve as a diagnostic and prognostic marker for severe pneumonia. miR-1287-5p was downregulated in severe pneumonia, and RP11-773H22.4 participated in the pathogenesis of severe pneumonia by regulating the expression of miR-1287-5p.

Expression and significance of procalcitonin, leukotriene B4, serum amyloid A, and C-reactive protein in children with different types of pneumonia: An observational study.

This study aimed to investigate the expression and significance of serum procalcitonin (PCT), leukotriene B4 (LTB4), Serum amyloid A (SAA), and C-reactive protein (CRP) in children with different types of pneumonia caused by different pathogenic infections. One hundred and one children with pneumonia admitted to The Fifth People Hospital of Zhuhai from July 2019 to June 2020 were enrolled and divided into 38 cases in the bacterial group, 30 cases in the mycoplasma group, and 33 cases in the virus group according to the different types of pathogens. The patients were divided into 42 cases in the noncritical group, 33 cases in the critical group, and 26 cases in the very critical group according to the pediatric clinical illness score (PCIS), and 30 healthy children were selected as the control group during the same period. Comparison of serum PCT, SAA: bacterial group > mycoplasma group > viral group > control group with significant differences (P < .05). Receiver operator characteristic (ROC) analysis showed that the area under the curves (AUCs) of serum PCT, LTB4, SAA, and CRP for the diagnosis of bacterial pneumonia were 1.000, 0.531, 0.969, and 0.833, respectively, and the AUCs for the diagnosis of mycoplasma pneumonia were 0.653, 0.609, 0.547, and 0.652, respectively, and the AUCs for the diagnosis of viral pneumonia were 0.888, 0.570, 0.955, and 1.000, respectively. Comparison of serum PCT, LTB4, SAA: very critical group > critical group > noncritical group > control group, with significant differences (P < .05). Serum PCT, LTB4, and SAA were negatively correlated with PCIS score by Pearson analysis (P < .05). Serum PCT and SAA showed diagnostic value for bacterial pneumonia, and serum SAA and CRP showed diagnostic value for viral pneumonia; serum PCT, LTB4, and SAA correlate with severity of disease and show higher expression with worsening of the condition.

C-reactive protein and procalcitonin: As predictor biomarkers of severity and outcome in children with community-acquired pneumonia.

Our cohort study aimed to compare serum C-reactive protein (CRP) and procalcitonin (PCT) levels in children with community-acquired pneumonia defined by WHO. The former differentiated between pneumonia and severe pneumonia while the latter was better for the outcome of 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.

Community-acquired pneumonia: a US perspective on the guideline gap.

Community-acquired pneumonia continues to be one of the most common causes of morbidity and mortality due to infectious disease. The aetiologies, clinical presentations, diagnostic modalities and therapeutic options are changing and outpacing the creation of management guidelines. This educational article summarizes a roundtable activity sponsored by an unrestricted educational grant by Paratek that included US experts discussing these changes and identifying gaps in the current guidelines.

Myeloid-derived suppressor cells in pleural effusion as a diagnostic marker for early discrimination of pulmonary tuberculosis from pneumonia.

Introduction: Tuberculous pleural effusion (TPE) stands as one of the primary forms of extrapulmonary tuberculosis (TB) and frequently manifests in regions with a high prevalence of TB, consequently being a notable cause of pleural effusion in such areas. However, the differentiation between TPE and parapneumonic pleural effusion (PPE) presents diagnostic complexities. This study aimed to evaluate the potential of myeloid-derived suppressor cells (MDSCs) in the pleural fluid as a potential diagnostic marker for distinguishing between TPE and PPE. Methods: Adult patients, aged 18 years or older, who presented to the emergency room of a tertiary referral hospital and received a first-time diagnosis of pleural effusion, were prospectively enrolled in the study. Various immune cell populations, including T cells, B cells, natural killer (NK) cells, and MDSCs, were analyzed in both pleural fluid and peripheral blood samples. Results: In pleural fluid, the frequency of lymphocytes, including T, B, and NK cells, was notably higher in TPE compared to PPE. Conversely, the frequency of polymorphonuclear (PMN)-MDSCs was significantly higher in PPE. Notably, compared to traditional markers such as the neutrophil-to-lymphocyte ratio and adenosine deaminase level, the frequency of PMN-MDSCs emerged as a more effective discriminator between PPE and TPE. PMN-MDSCs demonstrated superior positive and negative predictive values and exhibited a higher area under the curve in the receiver operating characteristic curve analysis. PMN-MDSCs in pleural effusion increased the levels of reactive oxygen species and suppressed the production of interferon-gamma from T cells following nonspecific stimulation. These findings suggest that MDSC-mediated immune suppression may contribute to the pathology of both TPE and PPE. Discussion: The frequency of PMN-MDSCs in pleural fluid is a clinically useful indicator for distinguishing between TPE and PPE.

A simplified pneumonia severity index (PSI) for clinical outcome prediction in COVID-19.

BACKGROUND: The Pneumonia Score Index (PSI) was developed to estimate the risk of dying within 30 days of presentation for community-acquired pneumonia patients and is a strong predictor of 30-day mortality after COVID-19. However, three of its required 20 variables (skilled nursing home, altered mental status and pleural effusion) are not discreetly available in the electronic medical record (EMR), resulting in manual chart review for these 3 factors. The goal of this study is to compare a simplified 17-factor version (PSI-17) to the original (denoted PSI-20) in terms of prediction of 30-day mortality in COVID-19. METHODS: In this retrospective cohort study, the hospitalized patients with confirmed SARS-CoV-2 infection between 2/28/20-5/28/20 were identified to compare the predictive performance between PSI-17 and PSI-20. Correlation was assessed between PSI-17 and PSI-20, and logistic regressions were performed for 30-day mortality. The predictive abilities were compared by discrimination, calibration, and overall performance. RESULTS: Based on 1,138 COVID-19 patients, the correlation between PSI-17 and PSI-20 was 0.95. Univariate logistic regression showed that PSI-17 had performance similar to PSI-20, based on AUC, ICI and Brier Score. After adjusting for confounding variables by multivariable logistic regression, PSI-17 and PSI-20 had AUCs (95% CI) of 0.85 (0.83-0.88) and 0.86 (0.84-0.89), respectively, indicating no significant difference in AUC at significance level of 0.05. CONCLUSION: PSI-17 and PSI-20 are equally effective predictors of 30-day mortality in terms of several performance metrics. PSI-17 can be obtained without the manual chart review, which allows for automated risk calculations within an EMR. PSI-17 can be easily obtained and may be a comparable alternative to PSI-20.

Anasarca as the first presentation of anti-synthetase syndrome.

A woman in her 70s presented with anasarca and exertional dyspnoea. Investigation showed severe hypoalbuminaemia with no urinary or gastrointestinal protein losses. CT thorax reported lung consolidations, and transbronchial lung biopsy demonstrated organising pneumonia. Autoimmune myositis serology was positive for anti-Jo-1, anti-Ro-52, and anti-PM/Scl-100 antibodies. She was diagnosed with anti-synthetase syndrome with organising pneumonia. She was treated with oral prednisolone and oral mycophenolate mofetil with a good clinical response.