Prediction Of Postoperative Pulmonary Complications Research Articles

ARISCAT and LAS VEGAS risk scores for predicting postoperative pulmonary complications after cardiac surgery: a cohort study.

Postoperative pulmonary complications (PPCs) could lead to morbidity, mortality, and prolonged hospital stay. Different risk-scoring systems are used to predict the identification of patients at risk of developing PPCs. The diagnostic accuracies of the Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) and Local Assessment of Ventilatory Management During General Anaesthesia for Surgery (LAS VEGAS) risk scores are compared in prediction of PPCs taking pulmonary complication as the gold standard in cardiac surgery. A prospective cohort study with consecutive sampling technique. A total of 181 patients were included. Quantitative data is presented as simple descriptive statistics giving mean and standard deviation, and qualitative variables are presented as frequency and percentages. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracies are also calculated. Total 181 post-cardiac surgery patients were analyzed. The median [interquartile range] of age, height, weight, and BMI were 60.0 [52.0-67.0] years, 163.0 [156.0-168.0] cm, 71.0 [65.0-80.0] kg and 27.3 [24.2-30.4] kg/m2. 127 (70.2%) were male, and 54 (29.8%) were female. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of ARISCAT for the prediction of PPCs were (94.9%, 4.65%, 76.1%, 22.9% and 73.4%), whereas LAS VEGAS were (97.1%, 4.65%, 76.5%, 33.3% and 75.1%), respectively. Both the ARISCAT and LAS VEGAS risk scores are of limited value in cardiac surgery patients for the prediction of postoperative pulmonary complications, based on the predicted scores in this study.

Preoperative three-dimensional lung volumetry predicts respiratory complications in patients undergoing major liver resection for colorectal metastases

Colorectal liver metastases (CRLM) are the predominant factor limiting survival in patients with colorectal cancer and liver resection with complete tumor removal is the best treatment option for these patients. This study examines the predictive ability of three-dimensional lung volumetry (3DLV) based on preoperative computerized tomography (CT), to predict postoperative pulmonary complications in patients undergoing major liver resection for CRLM. Patients undergoing major curative liver resection for CRLM between 2010 and 2021 with a preoperative CT scan of the thorax within 6 weeks of surgery, were included. Total lung volume (TLV) was calculated using volumetry software 3D-Slicer version 4.11.20210226 including Chest Imaging Platform extension (http://www.slicer.org). The area under the curve (AUC) of a receiver-operating characteristic analysis was used to define a cut-off value of TLV, for predicting the occurrence of postoperative respiratory complications. Differences between patients with TLV below and above the cut-off were examined with Chi-square or Fisher’s exact test and Mann–Whitney U tests and logistic regression was used to determine independent risk factors for the development of respiratory complications. A total of 123 patients were included, of which 35 (29%) developed respiratory complications. A predictive ability of TLV regarding respiratory complications was shown (AUC 0.62, p = 0.036) and a cut-off value of 4500 cm3 was defined. Patients with TLV < 4500 cm3 were shown to suffer from significantly higher rates of respiratory complications (44% vs. 21%, p = 0.007) compared to the rest. Logistic regression analysis identified TLV < 4500 cm3 as an independent predictor for the occurrence of respiratory complications (odds ratio 3.777, 95% confidence intervals 1.488–9.588, p = 0.005). Preoperative 3DLV is a viable technique for prediction of postoperative pulmonary complications in patients undergoing major liver resection for CRLM. More studies in larger cohorts are necessary to further evaluate this technique.

Lung ultrasound aeration score for prediction of postoperative pulmonary complications after major abdominal surgery: Secondary analysis of a randomized controlled trial

Lung ultrasound aeration score for prediction of postoperative pulmonary complications after major abdominal surgery: Secondary analysis of a randomized controlled trial

Concordance between ARISCAT risk score and cardiopulmonary exercise test values in risk prediction of postoperative pulmonary complications of major abdominal surgeries in a tertiary cancer hospital: A cross‐sectional study

AbstractBackground and AimsPulmonary complications are common after surgery. They include vascular thrombosis, pneumonia, respiratory failure (RF), and pain‐related atelectasis. There are a number of models to predict the risk of postoperative respiratory events other than thrombosis. The aim of this study was to explore the correlation of assess respiratory risk in surgical patients in Catalonia (ARISCAT) scoring and cardiopulmonary exercise test (CPET) values in prediction of postoperative pulmonary complications (PPCs).MethodsCancer patients referred to a tertiary hospital for elective major abdominal surgeries were studied. Patients were evaluated by ARISCAT score and then CPET was performed to determine the risk of surgery based on maximal oxygen consumption (VO2) value. Patients were followed for RF occurrence up to 72 h after surgery. Finally, the concordance of ARISCAT score and CPET values was evaluated in risk prediction of PPCs.ResultsThe results showed that parameters VO2, ARISCAT score, and anaerobic threshold could predict postoperative RF. Of these parameters, ARISCAT showed the highest sensitivity (100%) and the highest specificity (90.5%) compared with other parameters (Youden's J statistic = 0.905). However, VO2 value showed the highest validity. The percentage of agreement between different subgroups (low, medium, and high) of both criteria (VO2 and ARISCAT) was equal to 81.45% (p &lt; 0.001) and the ϰ coefficient of the given weight was equal to 0.54 (p &lt; 0.001), indicating a good agreement between these two criteria.ConclusionARISCAT scoring showed high sensitivity and specificity to PPCs in cancer patients and good correlation with CPET value for prediction of PPCs. Therefore, it is a reliable and robust risk prediction tool in major abdominal surgeries on cancer patients.

Harnessing Machine Learning for Prediction of Postoperative Pulmonary Complications: Retrospective Cohort Design.

Postoperative pulmonary complications (PPCs) are significant causes of postoperative morbidity and mortality. This study presents the utilization of machine learning for predicting PPCs and aims to identify the important features of the prediction models. This study used a retrospective cohort design and collected data from two hospitals. The dataset included perioperative variables such as patient characteristics, preexisting diseases, and intraoperative factors. Various algorithms, including logistic regression, random forest, light-gradient boosting machines, extreme-gradient boosting machines, and multilayer perceptrons, have been employed for model development and evaluation. This study enrolled 111,212 adult patients, with an overall incidence rate of 8.6% for developing PPCs. The area under the receiver-operating characteristic curve (AUROC) of the models was 0.699-0.767, and the f1 score was 0.446-0.526. In the prediction models, except for multilayer perceptron, the 10 most important features were obtained. In feature-reduced models, including 10 important features, the AUROC was 0.627-0.749, and the f1 score was 0.365-0.485. The number of packed red cells, urine, and rocuronium doses were similar in the three models. In conclusion, machine learning provides valuable insights into PPC prediction, significant features for prediction, and the feasibility of models that reduce the number of features.

Prediction of postoperative pulmonary complications in older patients undergoing lobectomy for lung cancer based on skeletal muscle mass.

This retrospective study was designed to evaluate preoperative pulmonary function test (PFT) results and skeletal muscle mass, represented by the erector spinae muscle (EM), as predictors of postoperative pulmonary complications (PPCs) in older patients undergoing lobectomy for lung cancer. The medical records, including preoperative PFT, chest computed tomography (CT) and PPCs, of patients older than 65 years undergoing lobectomy for lung cancer were retrospectively examined at Konkuk University Medical Center from January 2016 to December 2021. The sum of cross-sectional areas (CSAs) of the right and left EMs at the level of the spinous process with the 12th thoracic vertebra was used as the skeletal muscle mass (CSABoth). Data from a total of 197 patients were included in the analyses. In total, 55 patients had PPCs. The preoperative functional vital capacity (FVC) and forced expiratory volume in 1 second (FEV1) showed significantly poorer values and the CSABoth had significantly lower values in patients with than in those without PPCs. The preoperative FVC and FEV1 showed significant positive correlations with CSABoth. Multiple logistic regression analysis identified age, diabetes mellitus (DM), preoperative FVC and CSABoth as risk factors for PPCs. The areas under the curves for FVC and CSABoth were 0.727 (95% CI, 0.650-0.803; P<0.001) and 0.685 (95% CI, 0.608-0.762; P<0.001), respectively. The optimal threshold values of FVC and CSABoth to predict PPCs based on a receiver operating characteristic curve analysis were 2.685 L (sensitivity =64.1% and specificity =61.8%) and 28.47 mm2 (sensitivity =62.0% and specificity =61.5%), respectively. PPCs in older patients undergoing lobectomy for lung cancer were associated with lower preoperative FVC and FEV1 values and a lower skeletal muscle mass. Skeletal muscle mass, represented by the EM, was significantly correlated with the preoperative FVC and FEV1. Therefore, skeletal muscle mass may be useful for the prediction of PPCs in patients undergoing lobectomy for lung cancer.

Prediction of Postoperative Pulmonary Complications in Patients Undergoing Functional Endoscopic Sinus Surgery: A Cohort Study

Introduction: Considering the pathophysiology of nasal obstruction, changes in certain parameters such as Peripheral Blood Eosinophil Count (PBEC), bedside pulmonary function test, Peak Expiratory Flow Rate (PEFR), and Electrocardiography (ECG) may have some correlation with postoperative pulmonary complications such as upper airway obstruction, loss of pharyngeal muscle tone, and postobstructive pulmonary oedema. Aim: To observe and analyse the changes in PBEC, bedside pulmonary function test, PEFR, and ECG in patients undergoing Functional Endoscopic Sinus Surgery (FESS). Materials and Methods: A prospective cohort study was conducted at Bharati Hospital, Pune, Maharashtra, India over a two-year duration from December 2020 to October 2022. A total of 50 patients aged above 18 years undergoing FESS surgery were included in the study. The statistical analysis was performed using the Chi-square test and student’s t-test. After thorough preoperative evaluation, the aforementioned predictors were recorded. General anaesthesia management for FESS surgery was done according to the standard protocol. Vigilant intraoperative monitoring of vital parameters including peak airway pressure and plateau pressure was performed. After shifting the patients to the recovery room, they were observed for: 1) Hypoxia; 2) Hypercarbia; 3) Laryngospasm; 4) Bronchospasm; and 5) Pulmonary oedema. Results: A total of 50 patients aged between 18 years and 65 years with the mean age was 41.7±15.4 years were included in the study, with 32 males and 18 females. Only 24% of the study population showed postoperative hypoxia, while the rest of the complications were not observed in any patient. Changes in eosinophil count, PEFR, and ECG did not have any correlation with postoperative hypoxia and were statistically insignificant. Bedside pulmonary function tests, including the Sabrasez breath-holding test and the Sabrasez single breath count test, showed changes in 30% and 76% of patients, respectively. Forced Expiratory test change was seen in 72% of patients. Among these, 19.4% showed hypoxia. Out of the 12 cases showing postoperative hypoxia, seven had a disease duration of less than six months. Conclusion: The Sabrasez breath-holding test and Sabrasez single breath count are good predictors for postoperative hypoxia in patients undergoing FESS surgery. Shorter duration of nasal obstruction also showed postoperative hypoxia.

Ventilatory efficiency is superior to peak oxygen uptake for prediction of lung resection cardiovascular complications.

Ventilatory efficiency (VE/VCO2 slope) has been shown superior to peak oxygen consumption (VO2) for prediction of post-operative pulmonary complications in patients undergoing thoracotomy. VE/VCO2 slope is determined by ventilatory drive and ventilation/perfusion mismatch whereas VO2 is related to cardiac output and arteriovenous oxygen difference. We hypothesized pre-operative VO2 predicts post-operative cardiovascular complications in patients undergoing lung resection. Lung resection candidates from a published study were evaluated by post-hoc analysis. All of the patients underwent preoperative cardiopulmonary exercise testing. Post-operative cardiovascular complications were assessed during the first 30 post-operative days or hospital stay. One-way analysis of variance or the Kruskal-Wallis test, and multivariate logistic regression were used for statistical analysis and data summarized as median (IQR). Of 353 subjects, 30 (9%) developed pulmonary complications only (excluded from further analysis), while 78 subjects (22%) developed cardiovascular complications and were divided into two groups for analysis: cardiovascular only (n = 49) and cardiovascular with pulmonary complications (n = 29). Compared to patients without complications (n = 245), peak VO2 was significantly lower in the cardiovascular with pulmonary complications group [19.9 ml/kg/min (16.5-25) vs. 16.3 ml/kg/min (15-20.3); P<0.01] but not in the cardiovascular only complications group [19.9 ml/kg/min (16.5-25) vs 19.0 ml/kg/min (16-23.1); P = 0.18]. In contrast, VE/VCO2 slope was significantly higher in both cardiovascular only [29 (25-33) vs. 31 (27-37); P = 0.05] and cardiovascular with pulmonary complication groups [29 (25-33) vs. 37 (34-42); P<0.01)]. Logistic regression analysis showed VE/VCO2 slope [OR = 1.06; 95%CI (1.01-1.11); P = 0.01; AUC = 0.74], but not peak VO2 to be independently associated with post-operative cardiovascular complications. VE/VCO2 slope is superior to peak VO2 for prediction of post-operative cardiovascular complications in lung resection candidates.

Pulmonary Function Tests for the Prediction of Postoperative Pulmonary Complications.

Pulmonary function tests (PFTs) such as spirometry and blood gas analysis have been claimed to improve preoperative risk assessment. This systematic review summarizes the available scientific literature regarding the ability of PFTs to predict postoperative pulmonary complications (PPC) in non-thoracic surgery. We systematically searched MEDLINE, CINAHL, and the Cochrane Library for pertinent original research articles (PROSPERO CRD42020215502), framed by the PIT-criteria (PIT, participants, index test, target conditions), respecting the PRISMA-DTA recommendations (DTA, diagnostic test accuracy). 46 original research studies were identified that used PFT-findings as index tests and PPC as target condition. QUADAS-2 quality assessment revealed a high risk of bias regarding patient selection, blinding, and outcome definitions. Qualitative synthesis of prospective studies revealed inconclusive study findings: 65% argue for and 35% against preoperative spirometry, and 43% argue for blood gas analysis. A (post-hoc) subgroup analysis in prospective studies with low-risk of selection bias identified a possible benefit in upper abdominal surgery (three studies with 959 participants argued for and one study with 60 participants against spirometry). As the existing literature is inconclusive it is currently unknown if PFTs improve risk assessment before non-thoracic surgery. Spirometry should be considered in individuals with key indicators for chronic obstructive pulmonary disease (COPD) scheduling for upper abdominal surgery.

A Prediction Model for Postoperative Pulmonary Complication in Pulmonary Function-Impaired Patients Following Lung Resection

PurposeMost patients with lung cancer have impaired pulmonary function. Single pulmonary function parameters have been suggested as good indices for predicting postoperative pulmonary complications (PPC). The purpose of this retrospective study was to construct a prediction model, including more than one pulmonary function parameter, for better prediction of PPC in patients with lung cancer and impaired pulmonary function.Patients and MethodsOur database of patients who underwent lung resection for non-small cell lung cancer was reviewed and those with impaired pulmonary function were enrolled. Clinical data, including PPC, were recorded. Univariate and logistic regression analyses were applied to explore potential predictors and a prediction model constructed based on the results of logistic regression.ResultsPatients with impaired pulmonary function (n = 124) were enrolled. Most patients were male, current smokers, >60 years old, and had adenocarcinoma and mild ventilatory dysfunction or diffusion dysfunction. In univariate analysis, we identified six pulmonary function parameters that differed significantly between the PPC and non-PPC groups. Receiver operating characteristic curves were used to determine the best cutoff values. In logistic regression, only forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC%), peak expiratory flow (PEF%), and post predictive operation (ppo)-FEV1% remained significant. Based on these results, we constructed a prediction model for PPC including FEV1/FVC%, PEF%, and ppo-FEV1%, which had an good diagnostic performance of, with 76.7% sensitivity and 67.6% specificity.ConclusionOur prediction model, including the pulmonary function parameters, FEV1/FVC%, PEF%, and ppo-FEV1%, shows excellent performance for predicting PPC in patients with lung cancer and impaired pulmonary function following resection, and has potential for wide application in clinical practice.

Effect of intraoperative blood loss on postoperative pulmonary complications in patients undergoing video-assisted thoracoscopic surgery.

Background We aimed to investigate the impact of intraoperative blood loss on postoperative pulmonary complications in patients who underwent video-assisted thoracoscopic lobectomy for nonsmall cell lung cancer. Methods Data of a total of 409 patients (227 males, 182 females; median age: 62 years; range, 20 to 86 years) who underwent lung resection for Stage I-IIIa non-small cell lung cancer in our clinic between July 2017 and April 2018 were retrospectively analyzed. The receiver operating characteristic analysis was used to confirm the threshold value of intraoperative blood loss for the prediction of postoperative pulmonary complications. Propensity score matching was performed to compare between high-intraoperative blood loss and low-intraoperative blood loss groups. A post-matching conditional logistic regression was conducted to determine the independent risk factors for postoperative pulmonary complications. Results Of the patients, 86 (21.03%) developed postoperative pulmonary complications. In the propensity score matching analysis, intraoperative blood loss was shown to be a predictive factor of postoperative pulmonary complications (3.992; 95% confidence interval [CI]: 1.54-10.35; p=0.004). The rate of postoperative pulmonary complications in high-intraoperative blood loss group was significantly higher than that the low-intraoperative blood loss group (37.5% vs. 13.9%, respectively; p=0.003). The postoperative length of stay and duration of postoperative antibiotic use were significantly prolonged in the high-intraoperative blood loss group. Conclusion Intraoperative blood loss serves as a significant risk factor for postoperative pulmonary complications after lung resection for non-small cell lung cancer. Surgeons should strive to reduce intraoperative blood loss for better surgical outcomes.

The role of ultrasonographic lung aeration score in the prediction of postoperative pulmonary complications: an observational study

BackgroundPostoperative pulmonary complications (PPCs) are important contributors to mortality and morbidity after surgery. The available predicting models are useful in preoperative risk assessment, but there is a need for validated tools for the early postoperative period as well. Lung ultrasound is becoming popular in intensive and perioperative care and there is a growing interest to evaluate its role in the detection of postoperative pulmonary pathologies.ObjectivesWe aimed to identify characteristics with the potential of recognizing patients at risk by comparing the lung ultrasound scores (LUS) of patients with/without PPC in a 24-h postoperative timeframe.MethodsObservational study at a university clinic. We recruited ASA 2–3 patients undergoing elective major abdominal surgery under general anaesthesia. LUS was assessed preoperatively, and also 1 and 24 h after surgery. Baseline and operative characteristics were also collected. A one-week follow up identified PPC+ and PPC- patients. Significantly differing LUS values underwent ROC analysis. A multi-variate logistic regression analysis with forward stepwise model building was performed to find independent predictors of PPCs.ResultsOut of the 77 recruited patients, 67 were included in the study. We evaluated 18 patients in the PPC+ and 49 in the PPC- group. Mean ages were 68.4 ± 10.2 and 66.4 ± 9.6 years, respectively (p = 0.4829). Patients conforming to ASA 3 class were significantly more represented in the PPC+ group (66.7 and 26.5%; p = 0.0026). LUS at baseline and in the postoperative hour were similar in both populations. The median LUS at 0 h was 1.5 (IQR 1–2) and 1 (IQR 0–2; p = 0.4625) in the PPC+ and PPC- groups, respectively. In the first postoperative hour, both groups had a marked increase, resulting in scores of 6.5 (IQR 3–9) and 5 (IQR 3–7; p = 0.1925). However, in the 24th hour, median LUS were significantly higher in the PPC+ group (6; IQR 6–10 vs 3; IQR 2–4; p < 0.0001) and it was an independent risk factor (OR = 2.6448 CI95% 1.5555–4.4971; p = 0.0003). ROC analysis identified the optimal cut-off at 5 points with high sensitivity (0.9444) and good specificity (0.7755).ConclusionPostoperative LUS at 24 h can identify patients at risk of or in an early phase of PPCs.

A study of post operative pleuropulmonary complications of abdominal surgeries attending in a tertiary care hospital at Kakinada

Introduction: Postoperative pulmonary complications (PPCs) following abdominal surgery are frequent and associated with increased morbidity and mortality and hospital length of stay. Incidence rates vary dramatically, ranging from 2% to 40%. The incidence of pleuro-pulmonary complications shows wide variations & has the diversity of various influencing factors, including patient existing lung conditions, habitual history, selection of surgery, anaesthetic risks and post-surgical recovery. Material and Methods: 100 patients are selected from in & out patient department & causality in GGH, Kakinada attending for abdominal surgical conditions. It is a prospective- observational, cross sectional study. Results: In the studied group of 100 person’s total of 27 persons affected with pulmonary complications in overlapped manner. Following pulmonary complications observed with incidence rates respectively in the order of ATELECTASIS (74.07%), PLEURAL EFFUSION (62.96%), PNEUMONIA (62.96%), RESPIRATORY FAILURE (11.11%). Conclusion: The incidence of postoperative pleuropulmonary complications of abdominal surgeries in our study in GGH, Kakinada is 27%, which includes atelecasis as the predominant one (74%) followed by pleural effusion and pneumonia each carrying equal incidence (62.96%) and finally respiratory failure that occupied least. Early prediction of postoperative pulmonary complications is possible to have the early interventions to reduce the post op morbidity, hospital length of stay and cost. Keywords: Atelectasis, Pleural effusion, Pneumonia, Respiratory failure.

Prediction of postoperative pulmonary complications using preoperative controlling nutritional status (CONUT) score in patients with resectable non-small cell lung cancer

Postoperative pulmonary complications (PPCs) significantly impact surgical outcome. We investigated the predictive ability of controlling nutritional status (CONUT) for PPC after lung resection in patients with non-small cell lung cancer (NSCLC). We retrospectively reviewed data of 922 patients with NSCLC who underwent complete resection from January 2016–December 2017. We analyzed the frequency and characteristics of PPCs and compared receiver operating characteristic (ROC) curves of various prognostic models to predict PPCs. A CONUT score higher than 1 was considered as a high CONUT score. Total incidence of PPCs was 8.6% (n = 79). The proportion of pneumonia was significantly larger in the high CONUT group (P < 0.05). The CONUT consistently had a higher area under curve (AUC) value (0.64) than other prognostic models (prognostic nutritional index (PNI): AUC = 0.61, Glasgow prognostic score (GPS): AUC = 0.57, and assessment of respiratory risk in surgical patients in Catalonia (ARISCAT): AUC = 0.54). Multivariate analysis identified underweight [Odds ratio (OR) = 4.57, P = 0.002] and high CONUT score (OR = 1.91, P = 0.009) as independent PPCs prognostic factors. One-year mortality rate for high CONUT score was significantly higher (hazard ratio = 7.97; 95% confidence interval, 1.78–35.59). Preoperative CONUT score is an independent predictor of PPCs and 1-year mortality in patients with resectable NSCLC.

Lung Cancer Surgery in Patients with Chronic Obstructive Pulmonary Disease (COPD): Surgical Selection Challenges and Clinical Outcomes

Health care systems worldwide are commonly burdened with COPD and lung cancer and subsequently much has been studied and learnt of the interdependence between these two clinical entities. Lung cancer surgical treatment options in patients with severe COPD remain a clinical challenge for the multidisciplinary team. Appropriate patient selection and prediction of postoperative pulmonary complications aid in surgical decision making and informed patient consent. In this review, we present an overview of surgical selection tools (lung function parameters, risk stratification for postoperative pulmonary complications) and lung cancer clinical outcomes (recurrence, survival) in patients with COPD undergoing lung cancer surgery.

Existing Predictive Models for Postoperative Pulmonary Complications Perform Poorly in a Head and Neck Surgery Population.

Postoperative pulmonary complications (PPCs) are common following major surgical procedures. Risk stratification tools have been developed to identify patients at risk for PPCs. While otolaryngology cases were included in the development of common predictive tools, they comprised small percentages in each tool. It is unclear how these tools perform in patients undergoing major head and neck surgery with free flap reconstruction. This retrospective review studied all free flap reconstructions in head and neck surgery over a 12-year period at a single institutionin the southeastern US. Baseline demographic and medical information were included for each case. All cases were reviewed for development of major PPCs, including pneumonia and respiratory failure. The cohort underwent risk stratification using the ARISCAT and Gupta pulmonary risk indices. Performance of these predictive models for head and neck surgery was determined through receiver-operator curve comparison. 794 patients were identified with a median age of 62years (IQR 41-83). Sixty-five percent were male. Forty-three (5.4%) developed pneumonia, 23 patients developed respiratory failure (2.9%), and 38 patients developed both (4.8%), resulting in a total PPC proportion of 13.1% (n = 104). Both ARISCAT and Gupta pulmonary risk indices demonstrated low discrimination to predict PPCs in head and neck free flap reconstruction, with areas under the curve of 0.60 and 0.65, respectively. Two major indices for prediction of postoperative pulmonary complications do not accurately identify risk in patients undergoing major head and neck surgery. Further studies are needed to develop predictive tools for PPCs in this high-risk population.

Prediction of postoperative pulmonary complications

Prediction of postoperative pulmonary complications (PPCs) enables individually applied preventive measures and maybe even early treatment if a PPC eventually starts to develop. The purpose of this review is to describe crucial steps in the development and validation of prediction models, examine these steps in the current literature and describe what the future holds for PPC prediction. A systematic search of the medical literature identified 21 articles reporting on prediction models for PPCs. The studies were heterogeneous with regard to design, derivation cohort and whether or not a validation cohort was used. Furthermore, as definitions for PPCs varied substantially, PPC rates were quite different. One-third of the studies had a sufficient sample size for building a prediction model. In most articles, an internal validation step was reported, suggesting a good fit. In the four articles that reported an externally validation step, in three the prognostic model performed less well in external validation. The ARISCAT risk score was the only score that kept sufficient predictive power in external validation, albeit that the sample sizes of the cohorts used may have been too small. Analysis by machine learning could help building new prediction models, as unbiased cluster analyses could uncover clusters of patients with specific underlying pathophysiological mechanisms. Adding biomarkers to the model could optimize identification of biological phenotypes of risk groups. Many predictive models for PPCs have been reported on. Development of more robust PPC prediction models could be supported by machine learning.

Prediction of Postoperative Pulmonary Complications Using Preoperative Controlling Nutritional Status (CONUT) Score in Patient with Resectable Non-small Cell Lung Cancer (P12-032-19)

ObjectivesPostoperative pulmonary complications (PPCs) significantly impact surgical outcome, but the clinical usefulness of various models used to predict PPCs is questionable. The controlling nutritional status (CONUT) score reflects nutritional deficiency and inflammation and is used to predict clinical outcomes in various malignancies. We aimed to investigate the ability of the CONUT score to predict PPCs after lung resection in patients with non-small cell lung cancer (NSCLC). MethodsWe retrospectively reviewed data of 922 patients with NSCLC who underwent complete resection at Severance Hospital in South Korea during January 2016–December 2017. We analyzed the predictability of the CONUT score for PPCs compared with other inflammatory prognostic markers and PPCs risk scoring systems (prognostic nutritional index [PNI], Glasgow prognostic score [GPS], and assessment of respiratory risk in surgical patients in Catalonia [ARISCAT] score) using receiver operating characteristic curves analysis. ResultsOf 922 study subjects, 522 (56.6%) were male; the mean age was 64.2 years. Lobectomy was the most common type of operation (n = 737, 79.9%). Total incidence of PPCs was 8.6% (n = 79). Prolonged air leak (44.3%) was the most common PPC, followed by pneumonia (32.9%) and pneumothorax (11.4%). The proportion of pneumonia was significantly larger in the high CONUT group (P < 0.05). The CONUT consistently had a higher area under curve (AUC) value (0.64) than other prognostic models (PNI: AUC = 0.61, GPS: AUC = 0.57, and ARISCAT: AUC = 0.54). Multivariate analysis identified male sex (odds ratio [OR] = 1.94), low body mass index (OR = 4.57), and high CONUT score (OR = 1.91) as independent PPCs prognostic factors. Kaplan-Meier analysis revealed a significantly higher 1-year mortality rate for the high CONUT group (hazard ratio = 7.97; 95% confidence interval, 1.78–35.59). ConclusionsPreoperative CONUT score is an independent predictor of PPCs and 1-year mortality in patients with NSCLC. Funding SourcesNone.

Usefulness of combining clinical and biochemical parameters for prediction of postoperative pulmonary complications after lung resection surgery.

Early detection of patients with a high risk of postoperative pulmonary complications (PPCs) could improve postoperative strategies. We investigated the role of monitoring systemic and lung inflammatory biomarkers during surgery and the early postoperative period to detect patients at high risk of PPCs after lung resection surgery (LRS). This is a substudy of a randomized control trial on the inflammatory effects of anaesthetic drugs during LRS. We classified patients into two groups, depending on whether or not they developed PPCs. We constructed three multivariate logistic regression models to analyse the power of the biomarkers to predict PPCs. Model 1 only included the usual clinical variables; Model 2 included lung and systemic inflammatory biomarkers; and Model 3 combined Models 1 and 2. Comparisons between mathematical models were based on the area under the receiver operating characteristic curve (AUROC) and tests of integrated discrimination improvement (IDI). Statistical significance was set at p < 0.05. PPCs were detected in 37 (21.3%) patients during admission. The AUROC for Models 1, 2, and 3 was 0.79 (95% CI 0.71-0.87), 0.80 (95% CI 0.72-0.88), and 0.93 (95% CI 0.88-0.97), respectively. Comparison of the AUROC between Models 1 and 2 did not reveal statistically significant values (p = 0.79). However, Model 3 was superior to Model 1 (p < 0.001). Model 3 had had an IDI of 0.29 (p < 0.001) and a net reclassification index of 0.28 (p = 0.007). A mathematical model combining inflammation biomarkers with clinical variables predicts PPCs after LRS better than a model that includes only clinical data. Clinical registration number Clinical Trial Registration NCT02168751; EudraCT 2011-002294-29.

Prediction of Postoperative Pulmonary Complications by Ultrasonic Assessment of Extravascular Lung Water in Pediatric Patients with Left to Right Shunt Lesions

Prediction of Postoperative Pulmonary Complications by Ultrasonic Assessment of Extravascular Lung Water in Pediatric Patients with Left to Right Shunt Lesions