BACKGROUND: This study aimed to evaluate the impact of preoperative inflammatory indices and postoperative pneumonia (POP) on postoperative atrial fibrillation (POAF) in non-small cell lung cancer (NSCLC) patients.
METHODS: All consecutive patients who underwent pulmonary resection at our hospital (January 2016-October 2019) were enrolled. Preoperative inflammatory indices, demographic data, surgical details, and postoperative conditions were analyzed. Univariate and multivariate analyses of risk factors associated with POAF were also conducted.
RESULTS: Among the 382 patients included in the study, 32 (8.38%) developed POAF. Compared to non-POAF patients, POAF patients had greater incidence of POP (P = 0.09). Approximately 31 patients (96.9%) developed atrial fibrillation within three days after surgery. The POAF group had a significantly greater mean age (68.94 years) than did the non-POAF group (63 years) (P = 0.002). Additionally, compared to non-POAF patients, POAF patients exhibited an increased number of resected mediastinal lymph nodes (P < 0.001) and mediastinal lymph node stations (P < 0.001).The POAF group also had a greater intraoperative blood volume (P = 0.006), longer surgical duration (P = 0.022), and greater drainage volume (P = 0.003). IA/B stage (P < 0.001) and IIIA/B stage(P < 0.001), and lobectomy resection (P = 0.008) and wedge resection (P = 0.023) were also associated with POAF. Compared to those in the non-POAF group, the POAF group had longer postoperative hospital stays (10.54 days vs. 9 days; P = 0.001) and longer drainage times (7 days vs. 5 days; P = 0.004). Multivariate analysis revealed age, POP, and stage IIIA/B as independent influencing factors of POAF in NSCLC patients.
CONCLUSIONS: Preoperative inflammatory indices were not significantly associated with POAF, but age, POP, and stage IIIA/B were identified as independent influencing factors. Advanced-stage NSCLC patients may have a greater susceptibility to POAF than early-stage patients, although further validation is needed. Additionally, POAF was linked to a longer postoperative hospital stay.

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.
CONCLUSIONS: 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.

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.
CONCLUSIONS: 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.

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.
CONCLUSIONS: 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.

UNASSIGNED: To develop and validate a risk prediction model by identifying the preoperative factors associated with an increased risk of pneumonia after spinal surgery.
UNASSIGNED: This study included patients with spinal disease from two hospitals between January 2021 and June 2023. The patients were divided into the training and validation sets, which were categorized as postoperative pneumonia (POP) or non-POP, respectively. This study identified the independent risk variables for POP using a multivariate logistic regression analysis. A nomogram prediction model was developed and validated using risk factors, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) to assess predictive performance.
UNASSIGNED: Following exclusion, 2223 patients from Changzheng Hospital were enrolled in the training set and 357 patients from the No. 905 Hospital of PLA Navy were enrolled in the validation set. Univariate and multivariate logistic regression analyses revealed that operation time, American Society of Anesthesiologists (ASA) grade, smoking, non-wearing of medical masks, lack of preoperative respiratory training, chronic obstructive pulmonary disease (COPD), underlying diseases, and spinal section were risk factors for POP development in patients with spinal diseases. The area under the ROC curve of the training set was 0.950, whereas that of the validation set was 0.879. The model calibration curves demonstrated good agreement, and the DCA indicated a high expected net benefit value.
UNASSIGNED: The POP risk prediction model has high accuracy and efficiency in predicting POP in patients with spinal diseases. POP development is influenced by factors such as operation length, ASA grade, smoking, non-wearing of medical masks, lack of preoperative respiratory training, COPD, underlying diseases, and lumbar surgery.

UNASSIGNED: Postoperative pneumonia (POP) is one of the primary complications after aneurysmal subarachnoid hemorrhage (aSAH) and is associated with postoperative mortality, extended hospital stay, and increased medical fee. Early identification of pneumonia and more aggressive treatment can improve patient outcomes. We aimed to develop a model to predict POP in aSAH patients using machine learning (ML) methods.
UNASSIGNED: This internal cohort study included 706 patients with aSAH undergoing intracranial aneurysm embolization or aneurysm clipping. The cohort was randomly split into a train set (80%) and a testing set (20%). Perioperative information was collected from participants to establish 6 machine learning models for predicting POP after surgical treatment. The area under the receiver operating characteristic curve (AUC), precision-recall curve were used to assess the accuracy, discriminative power, and clinical validity of the predictions. The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database.
UNASSIGNED: In this study, 15.01% of patients in the training set and 12.06% in the testing set with POP after underwent surgery. Multivariate logistic regression analysis showed that mechanical ventilation time (MVT), Glasgow Coma Scale (GCS), Smoking history, albumin level, neutrophil-to-albumin Ratio (NAR), c-reactive protein (CRP)-to-albumin ratio (CAR) were independent predictors of POP. The logistic regression (LR) model presented significantly better predictive performance (AUC: 0.91) than other models and also performed well in the external validation set (AUC: 0.89).
UNASSIGNED: A machine learning model for predicting POP in aSAH patients was successfully developed using a machine learning algorithm based on six perioperative variables, which could guide high-risk POP patients to take appropriate preventive measures.

Dental and oral management (DOM) is a long-established treatment modality. This scoping review aimed to narratively review previous studies, examine the effects of perioperative DOM, and identify the available evidence. A literature search was conducted using the PubMed electronic database for studies published between January 1, 2000, and March 8, 2022. The search yielded 43 studies, most of which were published in the last 10 years. The results of this study confirmed that improved perioperative oral hygiene is effective in preventing postoperative pneumonia. Our results also suggested that preoperative DOM is effective in preventing postoperative surgical site infections. Perioperative DOM is effective in reducing the incidence of postoperative pneumonia, SSI, and postsurgical complications. Further studies are needed to elucidate the various mechanism of DOM and to examine efficient intervention methods and timing.

OBJECTIVE: Postoperative pneumonia (POP) is the leading cause of death among patients with hip fractures. Simple and cost-effective markers can be used to assess the risk of these patients. This study aims to investigate the association between POP and preoperative albumin-globulin ratio (AGR) in patients with hip fractures.
METHODS: A retrospective analysis was conducted on data from 1417 hip fracture patients admitted to the Department of Orthopaedics at the hospital. Generalized additive and logistic regression models were used to determine both linear and non-linear associations between preoperative AGR and POP. A two-piece regression model was employed to determine the threshold effect.
RESULTS: The study included 1417 participants, with a mean age of 77.57 (8.53) years and 26.96% (382/1417) male patients. The prevalence of POP was 6.21%. Following full covariate adjustment, each unit increase in AGR was associated with a 79% reduction in the incidence of POP (OR, 0.23; 95% CI: 0.08-0.63; P = 0.0046). The inflection point was found to be 1.33 using a two-piecewise regression model. For each unit increase in AGR on the left side of the inflection point, the incidence of POP decreased by 93% (OR, 0.07; 95%CI: 0.02-0.34; P = 0.0010). However, there was no statistically significant correlation on the right side of the inflection point (OR, 0.84; 95% CI: 0.17-4.10; P = 0.8287).
CONCLUSIONS: There exists a non-linear association between preoperative AGR and the incidence of POP in elderly hip fracture patients. When AGR is less than 1.33, the incidence of POP is negatively correlated with AGR. However, there is no correlation when AGR is greater than 1.33.

BACKGROUND: Although frail patients are known to experience increased postoperative complications, this is unclear for postoperative pneumonia (POP). We investigated associations between frailty and POP in patients with gastric cancer (GC) undergoing gastrectomy.
METHODS: In this prospective study conducted between August 2016 and December 2022, we preoperatively assessed frailty in 341 patients with GC undergoing gastrectomy using a frailty index (FI). Patients were divided into high FI vs low FI groups to examine frailty and pneumonia rates after gastrectomy for GC.
RESULTS: Of 327 patients, 18 (5.5%) experienced POP after gastrectomy. Multivariate analyses showed that a high FI and total or proximal gastrectomy (TG/PG) were independent risk factors for POP (high FI: odds ratio [OR], 5.00; 95% CI, 1.77-15.54; TG/PG: OR, 3.07; 95% CI, 1.09-8.78). The proportion of patients with POP was 2.4% in those with nonhigh FI and non-TG/PG, 5.3% in those with nonhigh FI and TG/PG, 7.1% in those with high FI and non-TG/PG, and 28.0% in those with high FI and TG/PG (P < .001). The area under the receiver operating characteristic curve for this risk assessment for predicting POP was 0.740.
CONCLUSIONS: In patients with GC undergoing gastrectomy, POP was independently associated with preoperatively high FI and TG/PG. Our simple POP risk assessment method, which combines these factors, may effectively predict and prepare patients for POP.

BACKGROUND: Postoperative pneumonia is one of the common complications after video-assisted thoracoscopic surgery. There is no related study on the effect of lung isolation with different airway devices on postoperative pneumonia. Therefore, in this study, the propensity score matching method was used to retrospectively explore the effects of different lung isolation methods on postoperative pneumonia in patients undergoing video-assisted thoracoscopic surgery.
METHODS: This is A single-center, retrospective, propensity score-matched study. The information of patients who underwent VATS in Weifang People \'s Hospital from January 2020 to January 2021 was retrospectively included. The patients were divided into three groups according to the airway device used in thoracoscopic surgery: laryngeal mask combined with bronchial blocker group (LM + BB group), tracheal tube combined with bronchial blocker group (TT + BB group) and double-lumen endobronchial tube group (DLT group). The main outcome was the incidence of pneumonia within 7 days after surgery; the secondary outcome were hospitalization time and hospitalization expenses. Patients in the three groups were matched using propensity score matching (PSM) analysis.
RESULTS: After propensity score matching analysis, there was no significant difference in the incidence of postoperative pneumonia and hospitalization time among the three groups (P > 0.05), but there was significant difference in hospitalization expenses among the three groups (P < 0.05).
CONCLUSIONS: There was no significant difference in the effect of different intubation lung isolation methods on postoperative pneumonia in patients undergoing thoracoscopic surgery.