BACKGROUND: Whether adherence to a healthy lifestyle is associated with a lower risk of developing pneumonia and a better long-term prognosis remains unclear. This study aimed to investigate associations of individual and combined lifestyle factors (LFs) with the incidence risk and long-term prognosis of pneumonia hospitalization. METHODS: Using data from the China Kadoorie Biobank study, we used the multistate models to investigate the role of five high-risk LFs, including smoking, excessive alcohol drinking, unhealthy dietary habits, physical inactivity, and unhealthy body shape, alone or in combination in the transitions from a generally healthy state at baseline to pneumonia hospitalization or cardiovascular disease (CVD, regarded as a reference outcome), and subsequently to mortality. RESULTS: Most of the five high-risk LFs were associated with increased risks of transitions from baseline to pneumonia and from pneumonia to death, but with different risk estimates. The greater the number of high-risk LFs, the higher the risk of developing pneumonia and long-term mortality risk after pneumonia, with the strength of associations comparable to that of LFs and CVD. Compared to participants with 0-1 high-risk LF, the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for transitions from baseline to pneumonia and from pneumonia to death in those with five high-risk LFs were 1.43 (1.28-1.60) and 1.98 (1.61-2.42), respectively. Correspondingly, the respective HRs (95% CIs) for transitions from baseline to CVD and from CVD to death were 2.00 (1.89-2.11) and 1.44 (1.30-1.59), respectively. The risk estimates changed slightly when further adjusting for the presence of major chronic diseases. CONCLUSION In this Chinese population, unhealthy LFs were associated with an increased incidence and long-term mortality risk of pneumonia.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; China/epidemiology* ; Life Style ; Pneumonia/etiology* ; Prognosis ; Risk Factors ; Smoking

BACKGROUND: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA). METHODS: This retrospective study included 413 patients hospitalized at Xinhua Hospital diagnosed with SP from June 1, 2015 to May 30, 2020. AI quantification results of chest CT and their combination with additional clinical variables were used to develop LCA models in an SP population. The optimal subphenotypes were determined though evaluating statistical indicators of all the LCA models, and clinical implications of them such as guiding ventilation strategies were further explored by statistical methods. RESULTS: The two-class LCA model based on AI quantification results of chest CT can describe the biological characteristics of the SP population well and hence yielded the two clinical subphenotypes. Patients with subphenotype-1 had milder infections ( P <0.001) than patients with subphenotype-2 and had lower 30-day ( P <0.001) and 90-day ( P <0.001) mortality, and lower in-hospital ( P = 0.001) and 2-year ( P <0.001) mortality. Patients with subphenotype-1 showed a better match between the percentage of non-infected lung volume (used to quantify ventilation) and oxygen saturation (used to reflect gas exchange), compared with patients with subphenotype-2. There were significant differences in the matching degree of lung ventilation and gas exchange between the two subphenotypes ( P <0.001). Compared with patients with subphenotype-2, those with subphenotype-1 showed a relatively better match between CT-based AI metrics of the non-infected region and oxygenation, and their clinical outcomes were effectively improved after receiving invasive ventilation treatment. CONCLUSIONS A two-class LCA model based on AI quantification results of chest CT in the SP population particularly revealed clinical heterogeneity of lung function. Identifying the degree of match between ventilation and gas-exchange may help guide decisions about assisted ventilation.
Humans ; Tomography, X-Ray Computed/methods* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Artificial Intelligence ; Aged ; Pneumonia/diagnosis* ; Latent Class Analysis ; Adult

BACKGROUND AND OBJECTIVE

COVID-19 contributes significantly to global morbidity and mortality. Age-related comorbidities elevate the risk of severe cases. Studies have recently demonstrated that widely available medications, including tocilizumab (TCZ), can manage severe symptoms. However, its effectiveness is unclear, particularly among the older population. Therefore, this review aimed to evaluate TCZ’s efficacy in managing severe pneumonia in individuals aged 50 and older.

We systematically search several databases and gray literature including Web of Science, CINAHL, Academic Search Complete, PsycINFO, PsycArticles, SocINDEX, CENTRAL/Cochrane Library, PubMed/MEDLINE for original research articles in English across several study designs published in the year 2020-2022. A narrative synthesis was conducted to summarize the evidence. We employed the NIH quality assessment tool for observational cohort studies to evaluate risk of bias. Additionally, we utilized GRADE to appraise the certainty of evidence.

Among 539 screened articles, only five studies met the selection criteria. Tocilizumab's impact on severe COVID-19 pneumonia revealed a diverse effect on mortality rate, with 29% in the TCZ group, and 40% in the controls died within 30 days of intubation (OR 0.61; 95% CI, 0.27-1.36). It is also reported that TCZ was not associated with mortality, despite faster decline in pulmonary function and prolonged fever. Hospital mortality in the TCZ group was significantly lower than in the controls, and age over 60 was the only significant risk factor. Moreover, administering TCZ reduced mechanical ventilation needs, with 82% extubated compared to 53% in controls. However, 45% in TCZ group was associated with a higher ventilator-associated pneumonia rate than in the untreated group which was 20% (P CONCLUSIONS

The effects of tocilizumab on reducing mortality risk and improving the survival rate of COVID-19 patients with pneumonia remained inconclusive. Yet, the majority of results suggested that giving tocilizumab leads to shorter hospital stays, lowers the requirement for mechanical ventilation, and decreases the likelihood of ICU transfer. Tocilizumab is linked to the incidence of secondary infections; hence, this medication should be closely monitored for side effects.

BACKGROUND AND OBJECTIVES

The etiology of pneumonia in the pediatric population varies by age group. Among patients one month to 59 months old, viral pathogens are the most common cause of lower respiratory infections. The study aims to determine the frequency distribution of antibiotic prescription among patients one month to 59 months old and to determine the adherence of primary care facilities to local guidelines with recommended antibiotics.

A descriptive retrospective study using electronic medical records was conducted at two primary care sites. Patients aged 1 month to 59 months old seeking consult via telemedicine or face-to-face diagnosed with community acquired pneumonia from April 2019-March 2020 in the rural facility and May 2019-April 2020 in the remote facility were included in the study. The primary outcome was to determine the patterns of antibiotic use in pneumonia in remote and rural areas and adherence to the recommended antibiotics by the 2016 Philippine Academy of Pediatric Pulmonologists pediatric community-acquired pneumonia clinical practice guidelines (CPG).

There were 30 pediatric patients diagnosed with pneumonia in the rural facility and 213 in the remote facility. Of these patients with pneumonia, 96.7% and 94.8% were prescribed antibiotics in the rural and remote sites, respectively. The most commonly prescribed antibiotic in the rural facility was co-amoxiclav (26.7%), while amoxicillin (51.6%) was the most common in the remote facility. Adherence to the CPG in the rural site was lower at 23.3% (n=8/30) compared to the remote site which was 55.9% (n=119/213).

Primary care physicians prescribed antibiotics in over 90% of the time upon the diagnosis of pneumonia in children aged one month to 59 months old, despite viral pneumonia being the more common in primary care setting. Adherence to recommended antibiotics was higher in the remote setting than in the rural setting. Use of EMR to monitor quality of care can improve patient outcomes and safety, pointing out the importance of improving the quality of documentation in the study sites.

Adenosine, a critical molecule regulating cellular function both inside and outside cells, is controlled by two human adenosine deaminases: ADA1 and ADA2. While ADA1 primarily resides in the cytoplasm, ADA2 can be transported to lysosomes within cells or secreted outside the cell. Patients with ADA2 deficiency (DADA2) often suffer from systemic vasculitis due to elevated levels of TNF-α in their blood. Monocytes from DADA2 patients exhibit excessive TNF-α secretion and differentiate into pro-inflammatory M1-type macrophages. Our findings demonstrate that ADA2 localizes to endolysosomes within macrophages, and its intracellular concentration decreases in cells secreting TNF-α. This suggests that ADA2 may function as a lysosomal adenosine deaminase, regulating TNF-α expression by the cells. Interestingly, pneumonia patients exhibit higher ADA2 concentrations in their bronchoalveolar lavage (BAL), correlating with elevated pro-inflammatory cytokine levels. Conversely, cord blood has low ADA2 levels, creating a more immunosuppressive environment. Additionally, secreted ADA2 can bind to apoptotic cells, activating immune cells by reducing extracellular adenosine levels. These findings imply that ADA2 release from monocytes during inflammation, triggered by growth factors, may be crucial for cell activation. Targeting intracellular and extracellular ADA2 activities could pave the way for novel therapies in inflammatory and autoimmune disorders.
Humans ; Adenosine Deaminase/deficiency* ; Monocytes/cytology* ; Cell Differentiation ; Intercellular Signaling Peptides and Proteins/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Biomarkers/metabolism* ; Macrophages/metabolism* ; Pneumonia/metabolism*

OBJECTIVE: To investigate the predictive value of early lactate/albumin ratio (LAR) combined with quick sequential organ failure assessment (qSOFA) for the 28-day prognosis of patients with sepsis caused by emergency community-acquired pneumonia (CAP). METHODS: The clinical data of patients with sepsis caused by CAP admitted to the department of emergency of Beijing Haidian Hospital from June 2021 to August 2022 were retrospectively analyzed, including gender, age, comorbidities, lactic acid (Lac), serum albumin (Alb), LAR, procalcitonin (PCT) within 1 hour, and 28-day prognosis. Patients were divided into two groups based on 28-day prognosis, and risk factors affecting patients' prognosis were analyzed using univariate and multivariate Cox regression methods. Patients were divided into two groups according to the best cut-off value of LAR, and Kaplan-Meier survival curves were used to analyze the 28-day cumulative survival of patients in each group. Time-dependent receiver operator characteristic curve (ROC curve) were plotted to analyze the predictive value of sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II (APACHE II), and qSOFA+LAR score on the prognosis of patients with sepsis caused by CAP at 28 days. The area under the curve (AUC) was calculated and compared. RESULTS: A total of 116 patients with sepsis caused by CAP were included, of whom 80 survived at 28 days and 36 died, 28-day mortality of 31.0%. There were no statistically significant differences in age, gender, comorbidities, pH, platelet count, and fibrinogen between the survival and death groups, and there were significantly differences in blood urea nitrogen (BUN), white blood cell count (WBC), hemoglobin, Lac, Alb, PCT, D-dimer, LAR, as well as qSOFA score, SOFA score, and APACHE II score. Univariate Cox regression analyses showed that BUN, WBC, pH, Lac, Alb, PCT, LAR, qSOFA score, SOFA score, and APACHE II score were associated with mortality outcome. Multifactorial Cox regression analysis of the above variables showed that BUN, WBC, PCT, and APACHE II score were independent risk factors for 28-day death in the emergency department in patients with sepsis caused by CAP [hazard ratio (HR) were 1.081, 0.892, 1.034, and 1.135, respectively, all P < 0.05]. The best cut-off value of early LAR for predicting the 28-day prognosis of sepsis patients was 0.088, the Kaplan-Meier survival curve showed that the 28-day cumulative survival rate of sepsis patients in the LAR ≤ 0.088 group was significantly higher than that in the LAR > 0.088 group [82.9% (63/76) vs. 42.5% (17/40), Log-Rank test: χ² = 22.51, P < 0.001]. The qSOFA+LAR score was calculated based on the LAR cut-off value and qSOFA score, and ROC curve analysis showed that the AUCs of SOFA score, APACHE II score, and qSOFA+LAR score for predicting 28-day death of patients with sepsis caued by CAP were 0.741, 0.774, and 0.709, respectively, with the AUC of qSOFA+LAR score slightly lower than those of SOFA score and APACHE II score, but there were no significantly differences. When the best cut-off value of qSOFA+LAR score was 1, the sensitivity was 63.9% and the specificity was 80.0%. CONCLUSION The qSOFA+LAR score has predictive value for the 28-day prognosis of patients with sepsis caused by CAP in the emergency department, its predictive value is comparable to the SOFA score and the APACHE II score, and it is more convenient for early use in the emergency department.
Emergency Service, Hospital/statistics & numerical data* ; Sepsis/etiology* ; Prognosis ; Community-Acquired Pneumonia/mortality* ; Organ Dysfunction Scores ; Predictive Value of Tests ; Lactic Acid/blood* ; Serum Albumin, Human/analysis* ; Biomarkers/blood* ; Retrospective Studies ; Hospital Mortality ; Kaplan-Meier Estimate ; APACHE ; Procalcitonin/blood* ; ROC Curve ; Area Under Curve ; Humans

OBJECTIVE: To analyze the pathogens distribution in patients with ventilator-associated pneumonia (VAP), and their association with anti-β-glucan receptor-1 (Dectin-1)/spleen tyrosine kinase (Syk) signaling pathway, and to provide scientific basis for formulating more effective treatment strategies and preventive measures. METHODS: A prospective study was conducted. 160 patients with VAP admitted to the department of critical care medicine of Xingtai People's Hospital from January 2021 to March 2023 were enrolled. The respiratory secretions of patients were collected for Candida colonization analysis, and then the bacteria in the respiratory secretions were identified by automatic microbial identification instrument. The expression levels of Dectin-1 and Syk in peripheral blood mononuclear cells were detected by fluorescent immunopolymerase chain reaction. Clinical pulmonary infection score (CPIS) was performed based on imaging, clinical and microbiological criteria. The basic data, pathogen distribution, Dectin-1 and Syk expression levels and CPIS score of the two groups were compared. Spearman test was used to analyze the correlation between the expression levels of Dectin-1 and Syk and respiratory Candida colonization and CPIS score. RESULTS: 160 VAP patients, 97 were Candida colonized (colonized group) and 63 were not (non-colonized group). There were significantly differences in gender (males: 57.73% vs. 41.27%, P = 0.042) and age (years: 57.98±12.46 vs. 62.09±10.61, P = 0.029) between the colonized group and the non-colonized group, while there were no significantly differences in the data of duration of mechanical ventilation, underlying diseases and primary diseases. The distribution of pathogenic bacteria showed that the infection rate of Staphylococcus aureus in the colonized group was significantly higher than that in the non-colonized group (24.74% vs. 7.94%, P < 0.05), and there was no significantly difference in the infection rate of other G-positive and G-negative bacteria between the two groups. The CPIS score in the colonized group was significantly higher than that in the non-colonized group (8.73±0.43 vs. 7.31±0.39, P < 0.01), and the expression levels of Dectin-1 and Syk in peripheral blood mononuclear cells were significantly higher than those in the non-colonized group (Dectin-1/U6: 0.86±0.22 vs. 0.47±0.16, Syk/U6: 0.77±0.18 vs. 0.42±0.11, both P < 0.01). The expression levels of Dectin-1 and Syk in peripheral blood mononuclear cells of VAP patients were significantly positively correlated with the colonization of respiratory Candida (r values were 0.754 and 0.631, respectively, both P < 0.05), and were significantly positively correlated with CPIS score (r values were 0.594 and 0.618, respectively, both P < 0.05). CONCLUSION The proportion of Staphylococcus aureus in VAP patients with respiratory Candida colonization is higher, and Dectin-1/Syk signaling pathway is significantly positively correlated with respiratory Candida colonization and CPIS score.
Humans ; Syk Kinase ; Lectins, C-Type/metabolism* ; Signal Transduction ; Pneumonia, Ventilator-Associated/metabolism* ; Prospective Studies ; Male ; Female ; Middle Aged ; Candida ; Aged

OBJECTIVE: To identify early potential risk factors for hospital-acquired pneumonia (HAP) in patients with mild traumatic brain injury (mTBI), construct a risk prediction model, and evaluate its predictive efficacy. METHODS: A case-control study was conducted using clinical data from mTBI patients admitted to the neurosurgery department of Changzhou Second People's Hospital from September 2021 to September 2023. The patients were divided into two groups based on whether they developed HAP. Clinical data within 48 hours of admission were statistically analyzed to identify factors influencing HAP occurrence through univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection to identify the most influential variables. The dataset was divided into training and validation sets in a 7:3 ratio. A multivariate Logistic regression analysis was then performed using the training set to construct the prediction model, exploring the risk factors for HAP in mTBI patients and conducting internal validation in the validation set. Receiver operator characteristic curve (ROC curve), decision curve analysis (DCA), and calibration curve were utilized to assess the sensitivity, specificity, decision value, and predictive accuracy of the prediction model. RESULTS: A total of 677 mTBI patients were included, with 257 in the HAP group and 420 in the non-HAP group. The significant differences were found between the two groups in terms of age, maximum body temperature (MaxT), maximum heart rate (MaxHR), maximum systolic blood pressure (MaxSBP), minimum systolic blood pressure (MinSBP), maximum respiratory rate (MaxRR), cause of injury, and laboratory indicators [C-reactive protein (CRP), procalcitonin (PCT), neutrophil count (NEUT), erythrocyte sedimentation rate (ESR), fibrinogen (FBG), fibrinogen equivalent units (FEU), prothrombin time (PT), activated partial thromboplastin time (APTT), total cholesterol (TC), lactate dehydrogenase (LDH), prealbumin (PAB), albumin (Alb), blood urea nitrogen (BUN), serum creatinine (SCr), hematocrit (HCT), hemoglobin (Hb), platelet count (PLT), glucose (Glu), K⁺, Na⁺], suggesting they could be potential risk factors for HAP in mTBI patients. After LASSO regression analysis, the key risk factors were enrolled in the multivariate Logistic regression analysis. The results revealed that the cause of injury being a traffic accident [odds ratio (OR) = 2.199, 95% confidence interval (95%CI) was 1.124-4.398, P = 0.023], NEUT (OR = 1.330, 95%CI was 1.214-1.469, P < 0.001), ESR (OR = 1.053, 95%CI was 1.019-1.090, P = 0.003), FBG (OR = 0.272, 95%CI was 0.158-0.445, P < 0.001), PT (OR = 0.253, 95%CI was 0.144-0.422, P < 0.001), APTT (OR = 0.689, 95%CI was 0.578-0.811, P < 0.001), Alb (OR = 0.734, 95%CI was 0.654-0.815, P < 0.001), BUN (OR = 0.720, 95%CI was 0.547-0.934, P = 0.016), and Na⁺ (OR = 0.756, 95%CI was 0.670-0.843, P < 0.001) could serve as main risk factors for constructing the prediction model. Calibration curves demonstrated good calibration of the prediction model in both training and validation sets with no evident over fitting. ROC curve analysis showed that the area under the ROC curve (AUC) of the prediction model in the training set was 0.943 (95%CI was 0.921-0.965, P < 0.001), with a sensitivity of 83.6% and a specificity of 91.5%. In the validation set, the AUC was 0.917 (95%CI was 0.878-0.957, P < 0.001), with a sensitivity of 90.1% and a specificity of 85.0%. DCA indicated that the prediction model had a high net benefit, suggesting practical clinical applicability. CONCLUSIONS The cause of injury being a traffic accident, NEUT, ESR, FBG, PT, APTT, Alb, BUN, and Na⁺ are identified as major risk factors influencing the occurrence of HAP in mTBI patients. The prediction model constructed using these parameters effectively assesses the likelihood of HAP in mTBI patients.
Humans ; Risk Factors ; Case-Control Studies ; Logistic Models ; Healthcare-Associated Pneumonia/epidemiology* ; Brain Injuries, Traumatic/complications* ; Male ; Female ; ROC Curve ; Pneumonia/etiology* ; Middle Aged ; Adult

With the continuous advancement and innovation in medical equipment technology, the transition between high-flow oxygen therapy, non-invasive ventilation, and invasive ventilation can be easily achieved by adjusting the ventilation mode of ventilators. During the weaning phase for tracheotomized patients, it is necessary to disconnect the ventilator circuit, change the ventilator mode, and gradually extend the weaning time to achieve complete ventilator liberation. During the weaning process, due to patients' excessive dependence on the ventilator, there may be situations where respiratory endpoints and Y-connectors of the ventilator are reconnected for invasive ventilation. However, during the weaning process, the Y-connector and expiratory end connectors are exposed to the air, which cannot ensure the tightness of the ventilator circuit, easily increasing the probability of ventilator circuit contamination and subsequently the risk of ventilator-associated pneumonia (VAP). To overcome these issues, the research team of department of critical care medicine of Zhongda Hospital Southeast University has designed a ventilator circuit interface protective device for weaning and has obtained a National Utility Model Patent of China (ZL 2023 2 1453385.8). The main body of the protective device is a Y-connector plug, consisting of multiple components, including a sealing piece, a protective cover, a sealing plug, an interface 1 (connects with the patient's tracheal tube), an interface 2 (connects with the respiratory branch of the ventilator), and an interface 3 (connects with the expiratory branch of the ventilator), featuring a unique design and easy operation. During the patient's weaning training process, the interface 1 and interface 2 is disconnected from the patient's tracheal tube and respiratory branch, respectively. The interface 1 is plugged with a stopper, and the interface 2 is covered with a protective cover to ensure the tightness of the expiratory branch and Y-connector of the ventilator. During the period when the patient is using the ventilator, the protective cover and plug are removed, and connecting them together ensures the tightness of the device itself, reducing the incidence of VAP caused by ventilator circuit contamination, avoiding nosocomial infections, and shortening the prolonged use of invasive ventilation, increased complication rate, extended hospital stay, and increased medical cost associated with weaning.
Humans ; Ventilator Weaning/methods* ; Equipment Design ; Ventilators, Mechanical ; Respiration, Artificial/instrumentation* ; Pneumonia, Ventilator-Associated/prevention & control*

OBJECTIVE: To investigate the interaction between α-amylase (α-AMS) and inflammatory response in patients with ventilator-associated pneumonia (VAP) and their predictive value for prognosis. METHODS: A prospective cohort study was conducted. Patients with mechanical ventilation who were treated in the intensive care unit (ICU) of the Second Hospital of Hebei Medical University from June 2020 to June 2023 were enrolled, and the patients were divided into VAP group and non-VAP group according to whether VAP occurred. VAP patients were stratified into mild [acute physiology and chronic health evaluation II (APACHE II) < 10 scores], moderate (APACHE II were 10-20 scores), and severe (APACHE II > 20 scores) groups based on the APACHE II. All patients were followed up for 28 days. In addition, healthy subjects who underwent health examination in our hospital at the same time were selected as the healthy control group. Baseline data including gender, age, mechanical ventilation mode, mechanical ventilation time, underlying diseases, drug use, and laboratory test indicators were collected. The serum levels of α-AMS, interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), C-reactive protein (CRP) and other inflammatory factors were analyzed and compared. Pearson correlation analysis was performed to analyze the correlation between serum α-AMS and inflammatory factors. Logistic regression was used to analyze the influencing factors of poor prognosis in patients with VAP. The receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive value of α-AMS on the poor prognosis of patients with VAP. RESULTS: A total of 100 mechanically ventilated patients were enrolled, including 60 cases in the VAP group and 40 cases in the non-VAP group. Among the patients with VAP, there were 24 cases in the mild group, 20 cases in the moderate group, and 16 cases in the severe group. A total of 44 patients survived at 28 days, while 16 died. Additionally, 100 healthy individuals were included as the healthy control group. Serum levels of α-AMS, IL-6, TNF-α and CRP in the VAP group were significantly higher than those in the non-VAP group and the healthy control group, while the levels of α-AMS, IL-6, TNF-α and CRP in the non-VAP group were significantly higher than those in the healthy control group. There were statistically significant differences in serum α-AMS, IL-6, TNF-α, CRP levels and APACHE II scores among VAP patients with different disease severities, and the levels of the above indicators in the severe group were significantly higher than those in the moderate group and mild group, and the levels of the above indicators in the moderate VAP group were significantly higher than those in the mild group. Pearson correlation analysis showed that serum α-AMS was positively correlated with IL-6, TNF-α, CRP, and APACHE II scores (r values were 0.404, 0.392 and 0.493, 0.493, all P < 0.01). Univariate analysis showed that age, mechanical ventilation, diabetes mellitus, ventilation time, ventilation position, prophylactic use of antimicrobial drugs, and serum α-AMS, IL-6, TNF-α, CRP, and APACHE II scores were correlated with the prognosis of VAP patients (all P < 0.05). Multivariate Logistic regression analysis identified age [odds ratio (OR) = 1.340, 95% confidence interval (95%CI) was 1.119-1.605], tracheostomy (OR = 3.050, 95%CI was 1.016-9.157), diabetes mellitus (OR = 1.379, 95%CI was 1.102-1.724), and ventilation time ≥ 7 days (OR = 2.557, 95%CI was 1.163-5.623) and serum α-AMS (OR = 1.428, 95%CI was 1.098-1.856), IL-6 (OR = 1.543, 95%CI was 1.005-2.371), TNF-α (OR = 2.228, 95%CI was 1.107-4.485), CRP (OR = 1.252, 95%CI was 1.131-1.387), APACHE II scores (OR = 1.422, 95%CI was 1.033-1.957) were independent influencing factors for the 28-day prognosis of patients with VAP (all P < 0.05). ROC curve analysis demonstrated that serum α-AMS, IL-6, TNF-α and CRP exhibited significant predictive performance on the prognosis of patients with VAP. The best cut-off value for α-AMS had a sensitivity of 81.3%, specificity of 75.0%, and an area under the ROC curve (AUC) of 0.791, which was significantly higher than those of inflammatory markers IL-6, TNF-α, and CRP (P < 0.05). The combined parameter diagnostic performance was significantly better than those of individual parameters (P < 0.05), with the highest diagnostic performance when combined, corresponding to an AUC of 0.868 (95%CI was 0.798-0.938), sensitivity of 87.5%, and specificity of 79.5%. CONCLUSIONS VAP in mechanically ventilated patients can lead to an increase in the levels of peripheral blood α-AMS and inflammatory factors, and there is an interaction between α-AMS and inflammatory markers in severe VAP patients. These markers are closely related to the severity of the disease and prognosis and have significant implications for predicting patient outcomes.
Humans ; Pneumonia, Ventilator-Associated/diagnosis* ; Prognosis ; Prospective Studies ; Respiration, Artificial ; alpha-Amylases/blood* ; Interleukin-6/blood* ; Male ; Female ; C-Reactive Protein/metabolism* ; APACHE ; Inflammation ; Middle Aged ; Intensive Care Units ; Tumor Necrosis Factor-alpha/blood* ; Aged