ObjectiveTo systematically evaluate the risk factors for postoperative pulmonary infection in patients with lung cancer (PPILC), and to provide a theoretical reference for clinicians to prevent the occurrence of PPILC. Methods The databases of CNKI, Wanfang data, VIP, CBM, PubMed, EMbase and The Cochrane Library were searched by computer to collect researches on the risk factors for PPILC. The search period was from 2012 to 2021. Two clinicians independently screened literature and extracted data and assessed studies for risk of bias, cross-checked and agreed. Meta-analysis was performed using RevMan 5.3 software. Results A total of 25 studies were included, including 20 case-control studies, 1 cohort study, and 4 cross-sectional studies, covering 15 129 patients. Twenty case-control studies and 1 cohort study had Newcastle-Ottawa Scale (NOS) scores≥6 points, and 4 cross-sectional studies had the Agency for Health Care Quality and Research (AHRQ) scale scores≥6 points. The results of meta-analysis showed that the risk factors for PPILC included: (1) 4 patient's own factors: age≥60 years, male, smoking history, smoking index≥400; (2) 7 preoperative factors: suffering from diabetes, chronic heart failure and chronic obstructive pulmonary disease, the ratio of forced expiratory volume in 1 second to forced expiratory volume<70%, the ratio of forced expiratory volume in 1 second to the predicted value, preoperative airway colonization, non-standard use of prophylactic antibiotics before surgery; (3) 3 intraoperative factors: operation time≥3 h, thoracotomy, the number of resected lobe≥2; (4) 3 postoperative factors: postoperative pain, postoperative mechanical ventilation≥12 h, postoperative invasive operation. Large number of preoperative lymphocyte, intraoperative systematic lymph node dissection, TNM stage Ⅰ and Ⅱ, and enhanced recovery after surgery were protective factors for PPILC. Conclusion The current research evidence shows that multiple factors are associated with the risk of PPILC. However, considering the influence of the quality and quantity of the included literature, the results of this study urgently need to be further verified by more high-quality clinical studies.
Objective To explore the related factors of postoperative pulmonary infection (PPI) in patients undergoing laparoscopic colorectal cancer surgery, and analyze the perioperative management strategy of pulmonary infection combined with the concept of enhanced recovery after surgery (ERAS). Methods Total of 687 patients who underwent laparoscopic colorectal cancer surgery in the colorectal cancer professional treatment group of Gastrointestinal Surgery Center of West China Hospital of Sichuan University from January 2017 to May 2019 were retrospectively included. According to the occurrence of PPI, all the included cases were divided into infection group (n=97) and non-infection group (n=590). The related factors and prevention strategies of PPI were analyzed. Results The rate of PPI among patients underwent laparoscopic resection in our study was 14.1% (97/687). Compared with the non-infection group, the proportions of patients with preoperative complications other than cardiopulmonary, receiving preoperative neoadjuvant radiotherapy and/or chemotherapy, preoperative Eastern Cooperative Oncology Group (ECOG) score 1–2, preoperative Nutrition Risk Screening 2002 (NRS2002) score 1–3, tumor located in the left colon and rectum, combined organ resection, operative time >3 h and postoperative TNM stage Ⅱ patients in the infection group were higher (P<0.05). However, the proportions of patients who used intraoperative lung protective ventilation strategy and incision infiltration anesthesia in the infection group were lower than those in the non-infection group (P<0.05). In the infection group, the proportions of patients who received regular sputum excretion, atomization therapy, balloon blowing/breathing training, stomatology nursing after operation and postoperative analgesia were all significantly lower than those of the non-infection group (P<0.05), whereas the proportions of patients receiving antibiotics and intravenous nutrition after operation were significantly higher than those in the non-infection group (P<0.05). Logistic regression analysis showed that low preoperative NRS2002 score, intraoperative protective ventilation strategy, postoperative respiratory training, and postoperative regular sputum excretion were the protective factors of PPI, while preoperative cardiopulmonary complications, preoperative neoadjuvant chemotherapy, tumor located in the left colon and rectum, late TNM staging and postoperative antibiotics were risk factors for pulmonary infection.Conclusions Preoperative cardiopulmonary complications, preoperative neoadjuvant chemotherapy, tumor location in the left colon and rectum, late TNM staging and postoperative antibiotics are risk factors for pulmonary infection in patients with laparoscopic colorectal cancer. Preoperative good nutritional status, intraoperative protective ventilation strategy, postoperative respiratory training and regular sputum excretion may reduce the incidence of PPI to a certain extent.
ObjectiveTo observe the relationship between ventilator-associated pneumonia (VAP) and changes in bronchial mucosa and sputum in critically ill patients. A prediction model for SEH score was developed according to the abnormal degrees of airway sputum , mucosal edema and mucosal hyperemia , as well as to analyze the diagnostic value of the SEH scores for VAP during bronchoscopy. MethodsA collection of general data and initial bronchoscopy results was conducted for patients admitted to the department of intensive care unit at West China Hospital from March 1, 2024, to July 1, 2024. Patients were divided into infection group (n=138) and non-infection group (n=227) according to diagnostic criteria for VAP based on the date of their first bronchoscopy. T-tests were used to compare baseline data between groups, while analysis of variance was employed to assess differences in airway mucosal and sputum lesions. A binary logistic regression model was constructed using the SEH scores for predicting VAP risk, with receiver operating characteristic curve area under the curve (AUC) utilized to evaluate model accuracy. ResultsA total of 365 patients were included in this study, among which 138 cases (37.8%) were diagnosed with VAP. The AUC for using SEH scores in diagnosing VAP was found to be 0.81 [95% confidence interval (CI) 0.76-0.85], with an optimal cutoff value set at 6.5. The sensitivity and specificity of SEH scores for diagnosing VAP were determined as 79.7% (95% CI: 72.2%-85.6%) and 73.1% (95% CI:67.0%-78.5%). Patients with SEH scores over 6.5 exhibited a significantly higher rate of VAP infection (64.3% vs.14.4%, P<0.0001), elevated white blood cell count levels (WBC) [(13.3±7.5 vs.1.8±6.2), P=0.04], as well as increased hospital mortality rates (39.8 % vs.24.2 %, P=0.002). ConclusionsThe SEH scores has a certain efficacy in the diagnosis of VAP in patients with mechanical ventilation. Compared with the traditional VAP diagnostic criteria, SEH scores is easier to obtain in clinical practice, and has certain clinical application value.
ObjectiveTo study the application of non-real-time ultrasound bronchoscopy combined with Metagenomic Next-Generation Sequencing (mNGS) for diagnosis in focal pulmonary infectious diseases. MethodsProspective inclusion of patients with focal pulmonary infection were randomly divided into two groups, the experimental group used non-real-time ultrasound bronchoscopy positioning to collect bronchial alveolar lavage fluid (BALF), while the control group used chest CT position. BALF was subjected to mNGS and traditional microbial detection including traditional culture, the fungal GM test and Xpert (MTB/RIF). ResultThe positive rate of traditional culture (39.58% vs. 16.67%, P=0.013) and mNGS (89.58% vs. 72.92%, P=0.036) in experimental group was higher. The positive rate of Xpert MTB/RIF (4.17% vs. 2.08%, P=1) and fungal GM test (6.25% vs. 4.17%, P=0.765) was similar. The positive rate of bacteria and fungi detected by mNGS was higher than traditional culture (61.46% vs. 28.13%, P<0.001). Mycobacterium tuberculosis was similar to Xpert MTB/RIF (8.33% vs. 3.13%, P=0.21). Aspergillus was similar to GM test (7.29% vs. 5.21%, P=0.77). The total positive rate of traditional microbial methods was 36.46%, but 81.25% in mNGS (P<0.001). mNGS showed that 35 cases were positive and 13 kinds of pathogens were detected in control group, but 43 patients and 17 kinds of pathogens were detected in experimental group. The average hospitalization time [(12.92±3.54) days vs. (16.35±7.49) days] and the cost [CNY (12209.17±3956.17) vs. CNY (19044.10±17350.85)] of experimental group was less (P<0.001). ConclusionsNon-real-time ultrasound bronchoscopy combined with mNGS can improve the diagnostic rate of focal pulmonary infectious diseases which is worthy of popularization and application in clinical practice.
Objective To explore independent risk factors for 30-day mortality in critical patients with pulmonary infection and sepsis, and build a prediction model. Methods Patients diagnosed with pulmonary infection and sepsis in the MIMIC-Ⅲ database were analyzed. The CareVue database was the training cohort (n=934), and the Metavision database was the external validation cohort (n=687). A COX proportional hazards regression model was established to screen independent risk factors and draw a nomogram. We conducted internal cross-validation and external validation of the model. Using the receiver operator characteristic (ROC) curve, Calibration chart, and decision curve analysis, we detected the discrimination, calibration, and benefit of the model respectively, comparing with the SOFA scoring model. Results Age, SOFA score, white blood cell count≤4×109/L, neutrophilic granulocyte percentage (NEU%)>85%, platelet count (PLT)≤100×109/L, PLT>300×109/L, red cell distribution width >15%, blood urea nitrogen, and lactate dehydrogenase were independent risk factors. The areas under the ROC curve of the model were 0.747 (training cohort) and 0.708 (external validation cohort), respectively, which was superior to the SOFA scoring model in terms of discrimination, calibration, and benefit. Conclusion The model established in this study can accurately and effectively predict the risk of the disease mortality, and provide a visual assessment method for early identification of high-risk patients.
ObjectiveTo analyze the risk factors for post-thymectomy myasthenic crisis (PTMC) and prolonged mechanical ventilation, in myasthenia gravis patients who underwent extended thymectomy.
MethodsWe retrospectively analyzed the clinical data of 79 patients including 38 males and 41 females who experienced PTMC and required mechanical ventilation in Daping Hospital between June 2008 and November 2014. Single factor analysis and multivariate analysis were conducted.
ResultsMorbidity of PTMC was 20.6% (79/384). Result of single-factor analysis showed that postoperative pneumonia was one of the main reasons of prolonged mechanical ventilation (P < 0.05). Result of multiple-factor analysis showed that the operation time was positively correlated with mechanical ventilation time (P < 0.05). The risk factor of prolonged mechanical ventilation time in PTMC was not associated with sex, age, disease history, myasthenic crisis history, Osserman classification, dosage of pyridostigmine before and after the operation, surgical approach, bleeding volume, other therapies besides mechanical ventilation (P > 0.05).
ConclusionMechanical ventilation is one the main therapy of PTMC, operation time, and postoperative pneumonia are the main factors to prolong mechanical ventilation time. In order to decrease morbidity of PTMC and shorten mechanical ventilation time, the operation time should be controlled and pulmonary infection should be avoided.
ObjectiveTo explore the effect of metabolic syndrome (MS) on postoperative pulmonary infection in patients with colorectal cancer (CRC) and to construct a risk prediction model for postoperative pulmonary infection in CRC patients. MethodsRetrospective collection of clinical data from 291 CRC patients who underwent surgical treatment at Department of General Surgery, Suzhou Ninth People’s Hospital in the period of January 2020 to August 2024. To explore the risk factors of postoperative pulmonary infection in patients with CRC and to establish a nomogram model. ResultsAmong the 291 CRC patients enrolled, there were 58 MS patients (19.93%) and 233 non-MS patients (80.07%). Compared with patients without MS, CRC patients with MS had longer surgery time (P<0.001) and higher incidence of postoperative pulmonary infection (P<0.001). The results of multiple logistic regression analysis showed that smoking history [OR=2.184, 95%CI (1.097, 4.345), P=0.026], body mass index (BMI)≥25 kg/m2 [OR=2.662, 95%CI (1.241, 5.703), P=0.012], MS [OR=2.770, 95%CI (1.415, 5.425), P=0.003], increased surgical time [OR=4.039, 95%CI (1.774, 9.197), P<0.001] and increased intraoperative bleeding [OR=2.398, 95%CI (1.246, 4.618), P=0.009] were all risk factors for postoperative pulmonary infection in CRC patients. Based on these risk factors, a nomogram model was constructed. The area under the curve (AUC) was 0.845 [95%CI (0.769, 0.906)], and the sensitivity and specificity were 84.2% and 87.5% respectively. The internal verification of Bootstrap test showed that the simulated curve and the actual curve had good consistency. The clinical decision curve analysis showed that when the threshold probability was in the range of 8%–84%, the net benefit of the model for patient diagnosis was higher. ConclusionsMS increases the risk of postoperative pulmonary infection in CRC patients. At the same time, smoking history, BMI≥25 kg/m2, long operation time, and more intraoperative blood loss are also risk factors for postoperative pulmonary infection in patients with CRC. Building a model based on this can effectively evaluate the risk of postoperative pulmonary infection in CRC patients.
ObjectiveTo analyze the pathogenic bacteria distribution, structure and characteristics of drug resistance in patients with acute stroke complicated with pulmonary infection, in order to provide reference for the prevention of hospital infection and rational use of antimicrobial agents.
MethodsA total of 864 clinical specimens of acute stroke complicated with pulmonary infection were chosen for study between January 2012 and December 2014. Separation and cultivation were done in accordance with the operation procedures regulated by the Ministry of Health. Drug sensitivity examination was done by Kirby-Bauer (k-b). Super-extensive spectrum β lactamase (ESBL) and methicillin resistant staphylococcus aureus (MRSA) were detected to analyze the bacterial species and resistance transition.
ResultsA total of 864 samples were cultivated, in which G-bacteria accounted for 61.2%. The main pathogenic bacteria was Klebsiella pneumoniae bacteria, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumanmii and Staphylococcus aureus. Imipenem had high antimicrobial activity to G-bacilli, especially to Escherichia coli and Klebsiella pneumoniae bacteria. Linezolid, vancomycin and teicoplanin had high antibacterial activity to staphylococcus aureus. Vancomycin resistant Staphylococcus aureus was not found. Ciprofloxacin had high antibacterial activity to Pseudomonas aeruginosa, while imipenem had low antibacterial activity to Pseudomonas aeruginosa. Amikacin had high antibacterial activity to acinetobacter.
ConclusionG-bacilli are predominant in acute stroke complicated with pulmonary infection. ESBLs and MRSA detection rate is high, and we should pay attention to the rational use of antibiotics to reduce drug resistance.
ObjectiveTo investigate the epidemiology, etiology and prognosis of pneumonia in lung transplantation recipients.
MethodsWe retrospectively analyzed the follow-up data of 42 case times (40 patients) of allogenic lung transplantation between March 2005 and August 2014. There were 29 males and 11 females with a mean age of 52.4±13.8 years. There were 32 case times with double lung transplantation, and 10 case times with single lung transplantation. Two patients underwent lung transplantation twice at an interval of 6.5 years and 4.0 years, respectively.
ResultsIn 42 case times of lung transplantation, 26 case times had forty-two episodes of pneumonia throughout the follow-up period of median 146 days (range 3 to 2 704 days). Microbiological etiology was established in 36 case times of pneumonia. Bacterial pneumonia (68.1%) was more frequent than fungal (10.6%) and viral pneumonia (8.5%). The cumulative risk of a pneumonia episode increased sharply in the first 30 days after transplantation. A percentage of 38.1% of total pneumonia episodes occurred within 30 days after transplantation, predominately due to Gram negative bacilli. While pneumonia of gram-negative bacilli occurred earliest with a median of 20 days (range 8-297 days). pneumonia caused by viruses (283 days, range 186-482 days) appeared significantly later than gram-negative bacilli, and unknown etiology (44.5 days, range 3-257 days) (P=0.001 and P=0.019, respectively). The survival rate in 1 year, 3 years, and 5 years was 66.1%, 56.3%, and 36.2%, respectively. pneumonia episode within 30 days after lung transplantation was associated remarkably with mortality risk (P=0.03) in lung transplantation recipients. The total blood loss during transplantation procedure and post-transplantation intubation time were associated significantly with early onset of pneumonia (≤30 days) by univariate analysis.
ConclusionRecognition of epidemiology, etiology and chronology of post-transplantaion pneumonia has implications relevant for appropriate management and optimal antibiotic prescription in lung transplantation recipients.
In order to identify the incidence of nosocomial pulmonary infection in surgical critical care patients in our hospital, we studied 800 patients discharged from surgical intensive care unit between May 1992 to Dec. 1994. One hundred and six episodes of pulmonary infection were found in 96 cases, in which 20 cases had been re-infected. The infection rate was 12.0%. The age of patients, APACHE- Ⅱ score and duration in ICU were closely related to the incidence of pulmonary infection. Tracheal intubation, tracheotomy and mechanical ventilation were the predisposing factors. The prevalent pathogens were pseudomonas aeruginosa, acinetobacter, staphylococcus aureus and candida albicans. 54.7% of cases were infected with more than one pathogens, and 36.8% of cases had fungal infection. The prevention and treatment are also discussed.
