Predicting risk of postoperative lung injury in high-risk surgical patients: a multicenter cohort study

Incidence, mortality, and predictive factors associated with acute respiratory distress syndrome in multiple trauma patients living in high-altitude areas: a retrospective study in Shigatse

Background

Acute respiratory distress syndrome (ARDS) is a severe complication that can lead to fatalities in multiple trauma patients. Nevertheless, the incidence rate and early prediction of ARDS among multiple trauma patients residing in high-altitude areas remain unknown.

Methods

This study included a total of 168 multiple trauma patients who received treatment at Shigatse People's Hospital Intensive Care Unit (ICU) between January 1, 2019 and December 31, 2021. The clinical characteristics of the patients and the incidence rate of ARDS were assessed. Univariable and multivariable logistic regression models were employed to identify potential risk factors for ARDS, and the predictive effects of these risk factors were analyzed.

Results

In the high-altitude area, the incidence of ARDS among multiple trauma patients was 37.5% (63/168), with a hospital mortality rate of 16.1% (27/168). Injury Severity Score (ISS) and thoracic injuries were identified as significant predictors for ARDS using the logistic regression model, with an area under the curve (AUC) of 0.75 and 0.75, respectively. Furthermore, a novel predictive risk score combining ISS and thoracic injuries demonstrated improved predictive ability, achieving an AUC of 0.82.

Conclusions

This study presents the incidence of ARDS in multiple trauma patients residing in the Tibetan region, and identifies two critical predictive factors along with a risk score for early prediction of ARDS. These findings have the potential to enhance clinicians' ability to accurately assess the risk of ARDS and proactively prevent its onset.

[Preoperative evaluation of adult patients before elective, non-cardiothoracic surgery : A joint recommendation of the German Society for Anesthesiology and Intensive Care Medicine, the German Society for Surgery and the German Society for Internal Medicine]

The 70 recommendations summarize the current status of preoperative risk evaluation of adult patients prior to elective non-cardiothoracic surgery. Based on the joint publications of the German scientific societies for anesthesiology and intensive care medicine (DGAI), surgery (DGCH), and internal medicine (DGIM), which were first published in 2010 and updated in 2017, as well as the European guideline on preoperative cardiac risk evaluation published in 2022, a comprehensive re-evaluation of the recommendation takes place, taking into account new findings, the current literature, and current guidelines of international professional societies. The revised multidisciplinary recommendation is intended to facilitate a structured and common approach to the preoperative evaluation of patients. The aim is to ensure individualized preparation for the patient prior to surgery and thus to increase patient safety. Taking into account intervention- and patient-specific factors, which are indispensable in the preoperative risk evaluation, the perioperative risk for the patient should be minimized and safety increased. The recommendations for action are summarized under "General Principles (A)," "Advanced Diagnostics (B)," and the "Preoperative Management of Continuous Medication (C)." For the first time, a rating of the individual measures with regard to their clinical relevance has been given in the present recommendation. A joint and transparent agreement is intended to ensure a high level of patient orientation while avoiding unnecessary preliminary examinations, to shorten preoperative examination procedures, and ultimately to save costs. The joint recommendation of DGAI, DGCH and DGIM reflects the current state of knowledge as well as the opinion of experts. The recommendation does not replace the individualized decision between patient and physician about the best preoperative strategy and treatment.

Predictive role of regional thigh tissue oxygen saturation monitoring during cardiopulmonary bypass in lung injury after cardiac surgery

Acute respiratory distress syndrome (ARDS) is a serious complication following cardiac surgery mainly associated with the use of cardiopulmonary bypass (CPB), which could increase the risk of mortality and morbidity. This study investigated the association of regional oxygen saturation (rSO2) during CPB with postoperative outcomes, including respiratory function. Patients who underwent cardiac surgery with CPB from 2015 to 2019 were included. Near-infrared spectroscopy was used to monitor rSO2 at the forehead, abdomen, and thighs throughout the surgery. Postoperative markers associated with CPB were assessed for correlations with PaO2/FiO2 (P/F) ratios at intensive care unit (ICU) admission. Postoperative lung injury (LI) was defined as moderate or severe ARDS based on the Berlin criteria, and its incidence was 29.9% (20/67). On multiple regression analysis, the following were associated with P/F ratios at ICU admission: vasoactive-inotropic scores at CPB induction (P = 0.03), thigh rSO2 values during CPB (P = 0.04), and body surface area (P < 0.001). A thigh rSO2 of 71% during CPB was significantly predictive of postoperative LI with an area under the curve of 0.71 (P = 0.03), sensitivity of 0.70, and specificity of 0.68. Patients with postoperative LI had longer ventilation time and ICU stays. Thigh rSO2 values during CPB were a potential predictor of postoperative pulmonary outcomes.

A Least Absolute Shrinkage and Selection Operator-Derived Predictive Model for Postoperative Respiratory Failure in a Heterogeneous Adult Elective Surgery Patient Population

BACKGROUND

Postoperative respiratory failure (PRF) is associated with increased hospital charges and worse patient outcomes. Reliable prediction models can help to guide postoperative planning to optimize care, to guide resource allocation, and to foster shared decision-making with patients.

RESEARCH QUESTION

Can a predictive model be developed to accurately identify patients at high risk of PRF?

STUDY DESIGN AND METHODS

In this single-site proof-of-concept study, we used structured query language to extract, transform, and load electronic health record data from 23,999 consecutive adult patients admitted for elective surgery (2014-2021). Our primary outcome was PRF, defined as mechanical ventilation after surgery of > 48 h. Predictors of interest included demographics, comorbidities, and intraoperative factors. We used logistic regression to build a predictive model and the least absolute shrinkage and selection operator procedure to select variables and to estimate model coefficients. We evaluated model performance using optimism-corrected area under the receiver operating curve and area under the precision-recall curve and calculated sensitivity, specificity, positive and negative predictive values, and Brier scores.

RESULTS

Two hundred twenty-five patients (0.94%) demonstrated PRF. The 18-variable predictive model included: operations on the cardiovascular, nervous, digestive, urinary, or musculoskeletal system; surgical specialty orthopedic (nonspine); Medicare or Medicaid (as the primary payer); race unknown; American Society of Anesthesiologists class ≥ III; BMI of 30 to 34.9 kg/m2; anesthesia duration (per hour); net fluid at end of the operation (per liter); median intraoperative FIO2, end title CO2, heart rate, and tidal volume; and intraoperative vasopressor medications. The optimism-corrected area under the receiver operating curve was 0.835 (95% CI,0.808-0.862) and the area under the precision-recall curve was 0.156 (95% CI, 0.105-0.203).

INTERPRETATION

This single-center proof-of-concept study demonstrated that a structured query language extract, transform, and load process, based on readily available patient and intraoperative variables, can be used to develop a prediction model for PRF. This PRF prediction model is scalable for multicenter research. Clinical applications include decision support to guide postoperative level of care admission and treatment decisions.

Critical evaluation of established risk prediction models for acute respiratory distress syndrome in adult patients: A systematic review and meta-analysis

AIM

To assess the performance of validated prediction models for acute respiratory distress syndrome (ARDS) by systematic review and meta-analysis.

METHODS

Eight databases (Medline, CINAHL, Embase, The Cochrane Library, CNKI, WanFang Data, Sinomed, and VIP) were searched up to March 26, 2023. Studies developed and validated a prediction model for ARDS in adult patients were included. Items on study design, incidence, derivation methods, predictors, discrimination, and calibration were collected. The risk of bias was assessed by the Prediction model Risk of Bias Assessment Tool. Models with a reported area under the curve of the receiver operating characteristic (AUC) metric were analyzed.

RESULTS

A total of 25 studies were retrieved, including 48 unique prediction models. Discrimination was reported in all studies, with AUC ranging from 0.701 to 0.95. Emerged AUC value of the logistic regression model was 0.837 (95% CI: 0.814 to 0.859). Besides, the value in the ICU group was 0.856 (95% CI: 0.812 to 0.899), the acute pancreatitis group was 0.863 (95% CI: 0.844 to 0.882), and the postoperation group was 0.835 (95% CI: 0.808 to 0.861). In total, 24 of the included studies had a high risk of bias, which was mostly due to the improper methods in predictor screening (13/24), model calibration assessment (9/24), and dichotomization of continuous predictors (6/24).

CONCLUSIONS

This study shows that most prediction models for ARDS are at high risk of bias, and the discrimination ability of the model is excellent. Adherence to standardized guidelines for model development is necessary to derive a prediction model of value to clinicians.

Three subtypes of postoperative ARDS that showing different outcomes and responses to mechanical ventilation and fluid management: A machine learning and latent profile analysis

BACKGROUND

ARDS is a heterogeneous clinical syndrome, and operation and trauma are common indirect etiologies. The identification of postoperative ARDS subtypes may optimize individualized clinical management.

OBJECTIVES

To identify the subtypes of postoperative ARDS and explore the impact of therapy on outcomes.

METHODS

This retrospective study used data obtained from a database. Patients diagnosed with ARDS who underwent surgical procedures within 7 days were included in the study. Laboratory and clinical variables were used for latent profile analysis (LPA). XGBoost and multivariable logistic regression models were used to explore the association between therapy and outcomes.

RESULTS

A total of 1065 patients were included. The LPA identified three subtypes of postoperative ARDS: Patients in profile 1 were mainly accepted neurosurgery, while those in profile 2 and 3 were treated with orthopedic and vascular or thoracic surgery, respectively. The XGBoost model effectively predicted mortality with an AUC of 0.935, which was higher than SOFA (0.622), APACHE 2 (0.629), SLIP (0.579), and SLIP-2 (0.550).

CONCLUSIONS

This study identified three subtypes of postoperative ARDS with different clinical characteristics, mechanical support, and fluid resuscitation responses.

Development of an automated, general-purpose prediction tool for postoperative respiratory failure using machine learning: A retrospective cohort study

STUDY OBJECTIVE

Postoperative respiratory failure is a major surgical complication and key quality metric. Existing prediction tools underperform, are limited to specific populations, and necessitate manual calculation. This limits their implementation. We aimed to create an improved, machine learning powered prediction tool with ideal characteristics for automated calculation.

DESIGN, SETTING, AND PATIENTS

We retrospectively reviewed 101,455 anesthetic procedures from 1/2018 to 6/2021. The primary outcome was the Standardized Endpoints in Perioperative Medicine consensus definition for postoperative respiratory failure. Secondary outcomes were respiratory quality metrics from the National Surgery Quality Improvement Sample, Society of Thoracic Surgeons, and CMS. We abstracted from the electronic health record 26 procedural and physiologic variables previously identified as respiratory failure risk factors. We randomly split the cohort and used the Random Forest method to predict the composite outcome in the training cohort. We coined this the RESPIRE model and measured its accuracy in the validation cohort using area under the receiver operating curve (AUROC) analysis, among other measures, and compared this with ARISCAT and SPORC-1, two leading prediction tools. We compared performance in a validation cohort using score cut-offs determined in a separate test cohort.

MAIN RESULTS

The RESPIRE model exhibited superior accuracy with an AUROC of 0.93 (95% CI, 0.92-0.95) compared to 0.82 for both ARISCAT and SPORC-1 (P-for-difference < 0.0001 for both). At comparable 80-90% sensitivities, RESPIRE had higher positive predictive value (11%, 95% CI: 10-12%) and lower false positive rate (12%, 95% CI: 12-13%) compared to 4% and 37% for both ARISCAT and SPORC-1. The RESPIRE model also better predicted the established quality metrics for postoperative respiratory failure.

CONCLUSIONS

We developed a general-purpose, machine learning powered prediction tool with superior performance for research and quality-based definitions of postoperative respiratory failure.

Postoperative acute respiratory distress syndrome in randomized controlled trials

BACKGROUND

Acute respiratory distress syndrome is a potentially fatal postoperative complication. We aimed to estimate temporal trends of the representation of patients with postoperative acute respiratory distress syndrome in clinical trials, determine their distinct clinical features, and identify predictors of mortality.

METHODS

This is a secondary analysis of 7 randomized controlled clinical trials conducted by the Acute Respiratory Distress Syndrome Network and the Clinical Trials Network for the Prevention and Early Treatment of Acute Lung Injury. Patients with acute respiratory distress syndrome were classified into a postoperative acute respiratory distress syndrome group (ie, patients who had undergone elective surgery in the immediate period before trial enrollment) and a non-postoperative acute respiratory distress syndrome group.

RESULTS

Out of 5,316 patients with acute respiratory distress syndrome, 256 (4.8%) had postoperative acute respiratory distress syndrome. Representation of postoperative acute respiratory distress syndrome in trials gradually declined from 2000 to 2011, but it remained stable afterward at 2.7%. Postoperative acute respiratory distress syndrome was associated with lower 90-day mortality (24.6% vs 30.9%, P = .032) than non-postoperative acute respiratory distress syndrome, even after adjusting for age, acute respiratory distress syndrome severity, usage of vasopressors at baseline, and the study publication year (hazard ratio 0.63, 95% confidence interval 0.49-0.82). Age (odds ratio 1.07, 95% confidence interval 1.04-1.09), immunosuppression (odds ratio 4.12, 95% confidence interval 1.43-11.86), and positive fluid balance (odds ratio 1.09, 95% confidence interval 1.04-1.14) were associated with 90-day mortality among patients with postoperative acute respiratory distress syndrome.

CONCLUSION

Representation of postoperative acute respiratory distress syndrome in trials of the Acute Respiratory Distress Syndrome Network and the Clinical Trials Network for the Prevention and Early Treatment of Acute Lung Injury gradually declined from 2000 to 2011 but remained stable afterward. Postoperative acute respiratory distress syndrome was associated with lower mortality than non-postoperative acute respiratory distress syndrome. These findings may put both temporal trends and the prognosis of postoperative acute respiratory distress syndrome in perspective. Also, positive fluid balance was associated with the mortality of patients with postoperative acute respiratory distress syndrome.

Early plasma proteomic biomarkers and prediction model of acute respiratory distress syndrome after cardiopulmonary bypass: a prospective nested cohort study

BACKGROUND

Early recognition of the risk of acute respiratory distress syndrome (ARDS) after cardiopulmonary bypass (CPB) may improve clinical outcomes. The main objective of this study was to identify proteomic biomarkers and develop an early prediction model for CPB-ARDS.

METHODS

The authors conducted three prospective nested cohort studies of all consecutive patients undergoing cardiac surgery with CPB at Union Hospital of Tongji Medical College Hospital. Plasma proteomic profiling was performed in ARDS patients and matched controls (Cohort 1, April 2021-July 2021) at multiple timepoints: before CPB (T1), at the end of CPB (T2), and 24 h after CPB (T3). Then, for Cohort 2 (August 2021-July 2022), biomarker expression was measured and verified in the plasma. Furthermore, lung ischemia/reperfusion injury (LIRI) models and sham-operation were established in 50 rats to explore the tissue-level expression of biomarkers identified in the aforementioned clinical cohort. Subsequently, a machine learning-based prediction model incorporating protein and clinical predictors from Cohort 2 for CPB-ARDS was developed and internally validated. Model performance was externally validated on Cohort 3 (January 2023-March 2023).

RESULTS

A total of 709 proteins were identified, with 9, 29, and 35 altered proteins between ARDS cases and controls at T1, T2, and T3, respectively, in Cohort 1. Following quantitative verification of several predictive proteins in Cohort 2, higher levels of thioredoxin domain containing 5 (TXNDC5), cathepsin L (CTSL), and NPC intracellular cholesterol transporter 2 (NPC2) at T2 were observed in CPB-ARDS patients. A dynamic online predictive nomogram was developed based on three proteins (TXNDC5, CTSL, and NPC2) and two clinical risk factors (CPB time and massive blood transfusion), with excellent performance (precision: 83.33%, sensitivity: 93.33%, specificity: 61.16%, and F1 score: 85.05%). The mean area under the receiver operating characteristics curve (AUC) of the model after 10-fold cross-validation was 0.839 (95% CI: 0.824-0.855). Model discrimination and calibration were maintained during external validation dataset testing, with an AUC of 0.820 (95% CI: 0.685-0.955) and a Brier Score of 0.177 (95% CI: 0.147-0.206). Moreover, the considerably overexpressed TXNDC5 and CTSL proteins identified in the plasma of patients with CPB-ARDS, exhibited a significant upregulation in the lung tissue of LIRI rats.

CONCLUSIONS

This study identified several novel predictive biomarkers, developed and validated a practical prediction tool using biomarker and clinical factor combinations for individual prediction of CPB-ARDS risk. Assessing the plasma TXNDC5, CTSL, and NPC2 levels might identify patients who warrant closer follow-up and intensified therapy for ARDS prevention following major surgery.

Development of the Modern Cardiothoracic Intensive Care Unit and Current Management

The modern cardiothoracic intensive care unit (CTICU) developed as a result of advances in critical care, cardiology, and cardiac surgery. Patients undergoing cardiac surgery today are sicker, frailer, and have more complex cardiac and noncardiac morbidities. CTICU providers need to understand postoperative implications of different surgical procedures, complications that can occur in CTICU patients, resuscitation protocols for cardiac arrest, and diagnostic and therapeutic interventions such as transesophageal echocardiography and mechanical circulatory support. Optimum CTICU care requires a multidisciplinary team with collaboration between cardiac surgeons and critical care physicians with training and experience in the care of CTICU patients.

Risk factors and predictive model for pulmonary complications in patients transferred to ICU after hepatectomy

OBJECTIVE

Postoperative pulmonary complications (PPCs) seriously harm the recovery and prognosis of patients undergoing surgery. However, its related risk factors in critical patients after hepatectomy have been rarely reported. This study aimed at analyzing the factors related to PPCs in critical adult patients after hepatectomy and create a nomogram for prediction of the PPCs.

METHODS

503 patients' data were collected form the Peking University People's Hospital. Multivariate logistic regression analysis was used to identify independent risk factors to derive the nomogram. Nomogram's discriminatory ability was assessed using the area under the receiver operating characteristic curve (AUC), and calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test and calibration curve.

RESULTS

The independent risk factor for PPCs are advanced age (odds ratio [OR] = 1.026; P = 0.008), higher body mass index (OR = 1.139; P < 0.001), lower preoperative serum albumin level (OR = 0.961; P = 0.037), and intensive care unit first day infusion volume (OR = 1.152; P = 0.040). And based on this, we created a nomogram to predict the occurrence of PPCs. Upon assessing the nomogram's predictive ability, the AUC for the model was 0.713( 95% CI: 0.668-0.758, P<0.001). The Hosmer-Lemeshow test (P = 0.590) and calibration curve showed good calibration for the prediction of PPCs.

CONCLUSIONS

The prevalence and mortality of postoperative pulmonary complications in critical adult patients after hepatectomy are high. Advanced age, higher body mass index, lower preoperative serum albumin and intensive care unit first day infusion volume were found to be significantly associated with PPCs. And we created a nomogram model which can be used to predict the occurrence of PPCs.

Performance Comparison of Pulmonary Risk Scoring Systems in Lung Resection

OBJECTIVE

To validate and compare the performance of different pulmonary risk scoring systems to predict postoperative pulmonary complications (PPCs) in lung resection surgery.

DESIGN

Retrospective cohort study SETTING: A historic single-center cohort of lung resection surgeries PARTICIPANTS: Adult patients undergoing lung resection surgery under 1-lung ventilation.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The accuracy of the following pulmonary risk scoring systems were used to predict pulmonary complications: the ARISCAT (Assess respiratory RIsk in Surgical patients in CATalonia), the LAS VEGAS (Local Assessment of VEntilatory management during General Anesthesia for Surgery), the SPORC (Score for Prediction of Postoperative Respiratory Complications), and a recent thoracic-specific risk score, named CARDOT. Discrimination and calibration were assessed using the concordance (c) index and the intercept of LOESS (locally estimated scatterplot)-smoothed curves, respectively. Additional models were constructed that incorporated predicted postoperative forced expiratory volume (ppoFEV1) into each scoring system. Of the 2,104 patients undergoing lung surgery, 123 developed postoperative pulmonary complications (PPCs; 5.9%). All scoring systems had poor discriminatory power to predict PPCs (ARISCAT c-index 0.60, 95% confidence interval [CI] 0.55-0.65; LAS VEGAS c-index 0.68, 95% CI 0.63-0.73; SPORC c-index 0.63, 95% CI 0.59-0.68; CARDOT c-index 0.64, 95% CI 0.58-0.70), but the inclusion of ppoFEV1 slightly improved the performance of LAS VEGAS (c-index 0.70, 95% CI 0.66-0.75) and CARDOT (c-index 0.68, 95% CI 0.62-0.73). Analysis of calibration showed a slight overestimation when using ARISCAT (intercept -0.28) and LAS VEGAS (intercept -0.27).

CONCLUSIONS

None of the scoring systems appeared to have adequate discriminatory power to predict PPCs among patients undergoing lung resection. An alternative risk score is necessary to better predict patients at risk of PPCs after thoracic surgery.

Model for predicting early and late-onset postoperative pulmonary complications in perioperative patients receiving neuromuscular blockade: a secondary analysis

Pulmonary complications continue to be the most common adverse event after surgery. The main objective was to carry out two independent predictive models, both for early pulmonary complications in the Post-Anesthesia Care Unit and late-onset pulmonary complications after 30 postoperative days. The secondary objective was to determine whether presenting early complications subsequently causes patients to have other late-onset events. This is a secondary analysis of a cohort study. 714 patients were divided into four groups depending on the neuromuscular blocking agent, and spontaneous or pharmacological reversal. Incidence of late-onset complications if we have not previously had any early complications was 4.96%. If the patient has previously had early complications the incidence of late-onset complications was 22.02%. If airway obstruction occurs, the risk of atelectasis increased from 6.88 to 22.58% (p = 0.002). If hypoxemia occurs, the incidence increased from 5.82 to 21.79% (p < 0.001). Based on our predictive models, we conclude that diabetes mellitus and preoperative anemia are two risk factors for early and late-onset postoperative pulmonary complications, respectively. Hypoxemia and airway obstruction in Post-Anesthesia Care Unit increased four times the risk of the development of pneumonia and atelectasis at 30 postoperative days.

Protocol for the derivation and external validation of a 30-day postoperative pulmonary complications (PPCs) risk prediction model for elderly patients undergoing thoracic surgery: a cohort study in southern China

INTRODUCTION

Postoperative pulmonary complications (PPCs) occur after up to 60% of non-cardiac thoracic surgery (NCTS), especially for multimorbid elderly patients. Nevertheless, current risk prediction models for PPCs have major limitations regarding derivation and validation, and do not account for the specific risks of NCTS patients. Well-founded and externally validated models specific to elderly NCTS patients are warranted to inform consent and treatment decisions.

METHODS AND ANALYSIS

We will develop, internally and externally validate a multivariable risk model to predict 30-day PPCs in elderly NCTS patients. Our cohort will be generated in three study sites in southern China with a target population of approximately 1400 between October 2021 and December 2023. Candidate predictors have been selected based on published data, clinical expertise and epidemiological knowledge. Our model will be derived using the combination of multivariable logistic regression and bootstrapping technique to lessen predictors. The final model will be internally validated using bootstrapping validation technique and externally validated using data from different study sites. A parsimonious risk score will then be developed on the basis of beta estimates derived from the logistic model. Model performance will be evaluated using area under the receiver operating characteristic curve, max-rescaled Brier score and calibration slope. In exploratory analysis, we will also assess the net benefit of Probability of PPCs Associated with THoracic surgery in elderly patients score in the complete cohort using decision curve analysis.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the Institutional Review Board of the Affiliated Cancer Hospital and Institute of Guangzhou Medical University, the Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine and the University of Hongkong-Shenzhen Hospital, respectively. The final risk prediction model will be published in an appropriate journal and further disseminated as an online calculator or nomogram for clinical application. Approved and anonymised data will be shared.

TRIAL REGISTRATION NUMBER

ChiCTR2100051170.

Novel models for early prediction and prevention of acute respiratory distress syndrome in patients following hepatectomy: A clinical translational study based on 1,032 patients

Background

Acute respiratory distress syndrome (ARDS) is a serious organ failure and postoperative complication. However, the incidence rate, early prediction and prevention of postoperative ARDS in patients undergoing hepatectomy remain unidentified.

Methods

A total of 1,032 patients undergoing hepatectomy between 2019 and 2020, at the Eastern Hepatobiliary Surgery Hospital were included. Patients in 2019 and 2020 were used as the development and validation cohorts, respectively. The incidence rate of ARDS was assessed. A logistic regression model and a least absolute shrinkage and selection operator (LASSO) regression model were used for constructing ARDS prediction models.

Results

The incidence of ARDS was 8.8% (43/490) in the development cohort and 5.7% (31/542) in the validation cohort. Operation time, postoperative aspartate aminotransferase (AST), and postoperative hemoglobin (Hb) were all critical predictors identified by the logistic regression model, with an area under the curve (AUC) of 0.804 in the development cohort and 0.752 in the validation cohort. Additionally, nine predictors were identified by the LASSO regression model, with an AUC of 0.848 in the development cohort and 0.786 in the validation cohort.

Conclusion

We reported the incidence of ARDS in patients undergoing hepatectomy and developed two simple and practical prediction models for early predicting postoperative ARDS in patients undergoing hepatectomy. These tools may improve clinicians' ability to early estimate the risk of postoperative ARDS and timely prevent its emergence.

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

BACKGROUND

Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications.

METHODS

We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC).

FINDINGS

In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]).

INTERPRETATION

In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required.

FUNDING

British Journal of Surgery Society.

Effect of high-frequency oscillatory ventilation combined with prone positioning in infants with acute respiratory distress syndrome after congenital heart surgery: A prospective randomized controlled trial

Objectives

This study aimed to evaluate the effect of high-frequency oscillatory ventilation, (HFOV) combined with prone positioning, on oxygenation and pulmonary ventilation in infants with acute respiratory distress syndrome (ARDS) after congenital heart surgery.

Design

A randomized controlled trial.

Setting

A single-center study at a tertiary teaching hospital.

Participants

Patients with postoperative ARDS after congenital heart disease were divided randomly into the following 2 groups: HFOV combined with prone position (HFOV-PP), and HFOV combined with supine position (HFOV-SP).

Interventions

The primary outcomes were the PaO₂/F_IO₂ ratio and the oxygenation index after the intervention, and the secondary outcomes were respiratory variables, hemodynamics, complications, and other short-term outcomes.

Results

Sixty-five eligible infants with ARDS were randomized to either the HFOV-PP (n = 32) or HFOV-SP (n = 33) group. No significant difference in baseline data was found between the 2 groups (p > 0.05). Oxygenation was improved in both groups after HFOV intervention. Compared with the HFOV-SP group, the HFOV-PP group had significantly increased PaO₂/F_IO₂ and oxygenation index and a shorter duration of invasive ventilation and length of cardiac intensive care unit stay. No serious complications occurred in the 2 groups.

Conclusion

HFOV-PP significantly improved oxygenation in infants with ARDS after cardiac surgery and had no serious complications.

Acute Respiratory Distress Syndrome in the Perioperative Period of Cardiac Surgery: Predictors, Diagnosis, Prognosis, Management Options, and Future Directions

Acute respiratory distress syndrome (ARDS) after cardiac surgery is reported with a widely variable incidence (from 0.4%-8.1%). Cardiac surgery patients usually are affected by several comorbidities, and the development of ARDS significantly affects their prognosis. Herein, evidence regarding the current knowledge in the field of ARDS in cardiac surgery is summarized and is followed by a discussion on therapeutic strategies, with consideration of the peculiar aspects of ARDS after cardiac surgery. Prevention of lung injury during and after cardiac surgery remains pivotal. Blood product transfusions should be limited to minimize the risk, among others, of lung injury. Open lung ventilation strategy (ventilation during cardiopulmonary bypass, recruitment maneuvers, and the use of moderate positive end-expiratory pressure) has not shown clear benefits on clinical outcomes. Clinicians in the intraoperative and postoperative ventilatory settings carefully should consider the effect of mechanical ventilation on cardiac function (in particular the right ventricle). Driving pressure should be kept as low as possible, with low tidal volumes (on predicted body weight) and optimal positive end-expiratory pressure. Regarding the therapeutic options, management of ARDS after cardiac surgery challenges the common approach. For instance, prone positioning may not be easily applicable after cardiac surgery. In patients who develop ARDS after cardiac surgery, extracorporeal techniques may be a valid choice in experienced hands. The use of neuromuscular blockade and inhaled nitric oxide can be considered on a case-by-case basis, whereas the use of aggressive lung recruitment and oscillatory ventilation should be discouraged.

Role of Intensified Lung Physiotherapy Bundle on the Occurrence of Pneumonia After Cardiac Surgery

Objective

The role of intensified lung physiotherapy bundle after cardiac surgery was investigated.

Methods

A before- and after-surgery comparison was conducted between the study from January 1, 2018 to December 31, 2019 (control group), when traditional lung physiotherapy bundle was used, and from January 1, 2020 to May 1, 2021 (study group), when the intensified bundle was used. The baseline data, clinical features, incidence of postoperative pneumonia, and prognoses of all the enrolled cardiac surgery patients were analyzed.

Results

In accordance with the study criteria, 358 patients were enrolled. The incidence rate of postoperative pneumonia was significantly lower in the study group than in the control group (14.2 vs. 22.7%, P = 0.037), as was in-hospital mortality (1.5 vs. 5.2%, P = 0.043). Patients receiving the intensified lung physiotherapy bundle had much shorter mechanical ventilation time (92 vs. 144 h, P < 0.0001), much shorter intensive care unit (ICU) stay (5 vs. 7 days, P < 0.001), and much shorter hospital stay (17 vs. 18.5 days, P = 0.022). The intensified lung physiotherapy bundle was an independent protective factor enabling the reduced occurrence of pneumonia (P = 0.007). On univariate analysis, this bundle significantly improved in-hospital mortality (P = 0.043).

Conclusions

Our intensified lung physiotherapy bundle potentially reduces the rate of postoperative pneumonia after cardiac surgery. This bundle might also be adopted as a suitable reference guide for the prevention of other postoperative pulmonary complications.

Multiple Machine Learning Approaches Based on Postoperative Prediction of Pulmonary Complications in Patients With Emergency Cerebral Hemorrhage Surgery

Objective

This study aimed to create a prediction model of postoperative pulmonary complications for the patients with emergency cerebral hemorrhage surgery.

Methods

Patients with hemorrhage surgery who underwent cerebral hemorrhage surgery were included and divided into two groups: patients with or without pulmonary complications. Patient characteristics, previous history, laboratory tests, and interventions were collected. Univariate and multivariate logistic regressions were used to predict postoperative pulmonary infection. Multiple machine learning approaches have been used to compare their importance in predicting factors, namely K-nearest neighbor (KNN), stochastic gradient descent (SGD), support vector classification (SVC), random forest (RF), and logistics regression (LR), as they are the most successful and widely used models for clinical data.

Results

Three hundred and fifty four patients with emergency cerebral hemorrhage surgery between January 1, 2017 and December 31, 2020 were included in the study. 53.7% (190/354) of the patients developed postoperative pulmonary complications (PPC). Stepwise logistic regression analysis revealed four independent predictive factors associated with pulmonary complications, including current smoker, lymphocyte count, clotting time, and ASA score. In addition, the RF model had an ideal predictive performance.

Conclusions

According to our result, current smoker, lymphocyte count, clotting time, and ASA score were independent risks of pulmonary complications. Machine learning approaches can also provide more evidence in the prediction of pulmonary complications.

Preoperative Pulmonary Risk Assessment

Postoperative pulmonary complications have a significant impact on perioperative morbidity and mortality and contribute substantially to health care costs. Surgical stress and anesthesia lead to changes in respiratory physiology, altering lung volumes, respiratory drive, and muscle function that can cumulatively increase the risk of postoperative pulmonary complications. Preoperative medical evaluation requires a structured approach to identify patient-, procedure-, and anesthesia-related risk factors for postoperative pulmonary complications. Validated risk prediction models can be used for risk stratification and to help tailor the preoperative investigation. Optimization of pulmonary comorbidities, smoking cessation, and correction of anemia are risk-mitigation strategies. Lung-protective ventilation, moderate PEEP application, and conservative use of neuromuscular blocking drugs are intra-operative preventive strategies. Postoperative early mobilization, chest physiotherapy, oral care, and appropriate analgesia speed up recovery. High-risk patients should receive inspiratory muscle training prior to surgery, and there should be a focus to minimize surgery time.

Airway Pressure Release Ventilation Mode Improves Circulatory and Respiratory Function in Patients After Cardiopulmonary Bypass, a Randomized Trial

Importance

Postoperative pulmonary complications and cardiovascular complications are major causes of morbidity, mortality, and resource utilization in cardiac surgery patients.

Objectives

To investigate the effects of airway pressure release ventilation (APRV) on respiration and hemodynamics in post cardiac surgery patients.

Main Outcomes and Measures

A single-center randomized control trial was performed. In total, 138 patients undergoing cardiopulmonary bypass were prospectively screened. Ultimately 39 patients met the inclusion criteria and were randomized into two groups: 19 patients were managed with pressure control ventilation (PCV) and 20 patients were managed with APRV. Respiratory mechanics after 4 h, hemodynamics within the first day, and Chest radiograph score (CRS) and blood gasses within the first three days were recorded and compared.

Results

A higher cardiac index (3.1 ± 0.7 vs. 2.8 ± 0.8 L⋅min^–1⋅m²; p < 0.05), and shock volume index (35.4 ± 9.2 vs. 33.1 ± 9.7 ml m^–2; p < 0.05) were also observed in the APRV group after 4 h as well as within the first day (p < 0.05). Compared to the PCV group, the PaO2/FiO₂ was significantly higher after 4 h in patients of APRV group (340 ± 97 vs. 301 ± 82, p < 0.05) and within the first three days (p < 0.05) in the APRV group. CRS revealed less overall lung injury in the APRV group (p < 0.001). The duration of mechanical ventilation and ICU length of stay were not significantly (p = 0.248 and 0.424, respectively).

Conclusions and Relevance

Compared to PCV, APRV may be associated with increased cardiac output improved oxygenation, and decreased lung injury in postoperative cardiac surgery patients.

Pulmonary effects of dexmedetomidine infusion in thoracic aortic surgery under hypothermic circulatory arrest: a randomized placebo-controlled trial

Dexmedetomidine has emerged as a promising organ protective agent. We performed prospective randomized placebo-controlled trial investigating effects of perioperative dexmedetomidine infusion on pulmonary function following thoracic aortic surgery with cardiopulmonary bypass and moderate hypothermic circulatory arrest. Fifty-two patients were randomized to two groups: the dexmedetomidine group received 1 µg/kg of dexmedetomidine over 20 min after induction of anesthesia, followed by 0.5 µg/kg/h infusion until 12 h after aortic cross clamp (ACC)-off, while the control group received the same volume of normal saline. The primary endpoints were oxygenation indices including arterial O₂ partial pressure (PaO₂) to alveolar O₂ partial pressure ratio (a/A ratio), (A-a) O₂ gradient, PaO₂/FiO₂ and lung mechanics including peak inspiratory and plateau pressures and compliances, which were assessed after anesthesia induction, 1 h, 6 h, 12 h, and 24 h after ACC-off. The secondary endpoints were serum biomarkers including interleukin-6, tumor necrosis factor-α, superoxide dismutase, and malondialdehyde (MDA). As a result, dexmedetomidine did not confer protective effects on the lungs, but inhibited elevation of serum MDA level, indicative of anti-oxidative stress property, and improved urine output and lower requirements of vasopressors.

Risk Factors Associated With Early Postoperative Respiratory Failure: A Matched Case-Control Study

BACKGROUND

Postoperative respiratory failure is the most common serious postoperative pulmonary complication, yet little is known about factors that can reduce its incidence. We sought to elucidate modifiable factors associated with respiratory failure that developed within the first 5 d after an elective operation.

MATERIALS AND METHODS

Matched case-control study of adults who had an operation at five academic medical centers between October 1, 2012 and September 30, 2015. Cases were identified using administrative data and confirmed via chart review by critical care clinicians. Controls were matched 1:1 to cases based on hospital, age, and surgical procedure.

RESULTS

Our total sample (n = 638) was 56.4% female, 71.3% white, and had a median age of 62 y (interquartile range 51, 70). Factors associated with early postoperative respiratory failure included male gender (odds ratio [OR] 1.72, 95% confidence interval [CI] 1.12-2.63), American Society of Anesthesiologists class III or greater (OR 2.85, 95% CI 1.74-4.66), greater number of preexisting comorbidities (OR 1.14, 95% CI 1.004-1.30), increased operative duration (OR 1.14, 95% CI 1.06-1.22), increased intraoperative positive end-expiratory pressure (OR 1.23, 95% CI 1.13-1.35) and tidal volume (OR 1.13, 95% CI 1.004-1.27), and greater net fluid balance at 24 h (OR 1.17, 95% CI 1.07-1.28).

CONCLUSIONS

We found greater intraoperative ventilator volume and pressure and 24-h fluid balance to be potentially modifiable factors associated with developing early postoperative respiratory failure. Further studies are warranted to independently verify these risk factors, explore their role in development of early postoperative respiratory failure, and potentially evaluate targeted interventions.

Acute Respiratory Distress Syndrome Prediction Score: Derivation and Validation

BACKGROUND

Despite advances in treatment strategies, acute respiratory distress syndrome (ARDS) after cardiac surgery remains associated with high morbidity and mortality. A method of screening patients for risk of ARDS after cardiac surgery is needed.

OBJECTIVES

To develop and validate an ARDS prediction score designed to identify patients at high risk of ARDS after cardiac or aortic surgery.

METHODS

An ARDS prediction score was derived from a retrospective derivation cohort and validated in a prospective cohort. Discrimination and calibration of the score were assessed with area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test, respectively. A sensitivity analysis was conducted to assess model performance at different cutoff points.

RESULTS

The retrospective derivation cohort consisted of 201 patients with and 602 patients without ARDS who had undergone cardiac or aortic surgery. Nine routinely available clinical variables were included in the ARDS prediction score. In the derivation cohort, the score distinguished patients with versus without ARDS with area under the curve of 0.84 (95% CI, 0.81-0.88; Hosmer-Lemeshow P = .55). In the validation cohort, 46 of 1834 patients (2.5%) had ARDS develop within 7 days after cardiac or aortic surgery. Area under the curve was 0.78 (95% CI, 0.71-0.85), and the score was well calibrated (Hosmer-Lemeshow P = .53).

CONCLUSIONS

The ARDS prediction score can be used to identify high-risk patients from the first day after cardiac or aortic surgery. Patients with a score of 3 or greater should be closely monitored. The score requires external validation before clinical use.

Analytics with artificial intelligence to advance the treatment of acute respiratory distress syndrome

Artificial intelligence (AI) has found its way into clinical studies in the era of big data. Acute respiratory distress syndrome (ARDS) or acute lung injury (ALI) is a clinical syndrome that encompasses a heterogeneous population. Management of such heterogeneous patient population is a big challenge for clinicians. With accumulating ALI datasets being publicly available, more knowledge could be discovered with sophisticated analytics. We reviewed literatures with big data analytics to understand the role of AI for improving the caring of patients with ALI/ARDS. Many studies have utilized the electronic medical records (EMR) data for the identification and prognostication of ARDS patients. As increasing number of ARDS clinical trials data is open to public, secondary analysis on these combined datasets provide a powerful way of finding solution to clinical questions with a new perspective. AI techniques such as Classification and Regression Tree (CART) and artificial neural networks (ANN) have also been successfully used in the investigation of ARDS problems. Individualized treatment of ARDS could be implemented with a support from AI as we are now able to classify ARDS into many subphenotypes by unsupervised machine learning algorithms. Interestingly, these subphenotypes show different responses to a certain intervention. However, current analytics involving ARDS have not fully incorporated information from omics such as transcriptome, proteomics, daily activities and environmental conditions. AI technology is assisting us to interpret complex data of ARDS patients and enable us to further improve the management of ARDS patients in future with individual treatment plans.

The Association between Prehospital Vulnerability, ARDS Development, and Mortality among At-Risk Adults. Results from the LIPS-A Clinical Trial

Rationale: No previous studies have examined the role of prehospital vulnerability in acute respiratory distress syndrome (ARDS) development and mortality in an acutely ill adult population.Objectives: To describe the association between prehospital vulnerability and 1) the development of ARDS, 2) 28-day mortality, and 3) 1-year mortality.Methods: This was a longitudinal prospective cohort study nested within the multicenter LIPS-A (Lung Injury Prevention Study-Aspirin) trial. We analyzed 301 participants who completed Vulnerable Elders Survey (VES) at baseline. Multivariable logistic regression and Cox regression analyses were used to describe the association between vulnerability and short-term outcomes (ARDS and 28-day mortality) and long-term outcomes (1-year mortality), respectively.Results: The VES score ranged from 0 to 10 (median [interquartile range], 2.0 [0-6]); 143 (47.5%) fit criteria for prehospital vulnerability (VES ≥ 3). Vulnerability was not significantly associated with ARDS development (10 [7.0%] vulnerable patients developed ARDS as per LIPS-A study criteria vs. 20 [12.7%] without vulnerability; P = 0.10; adjusted odds ratio [95% confidence interval (CI)], 0.54 [0.24-1.24]; P = 0.15). Nor was vulnerability associated with 28-day mortality (15 [10.5%] vulnerable patients were dead by Day 28 vs. 11 [7.0%] nonvulnerable patients; P = 0.28; adjusted odds ratio [95% CI], 0.95 [0.39-2.26]; P = 0.90). Vulnerability was significantly associated with 1-year mortality in hospital survivors (35 [26.9%] vs. 13 [9.3%]; adjusted hazard ratio [95% CI], 2.20 [1.10-4.37]; P = 0.02).Conclusions: In a population of adults recruited for their high risk of ARDS, prehospital vulnerability, measured by VES, was highly prevalent and strongly associated with 1-year mortality.

Central Sleep Apnea Predicts Pulmonary Complications After Cardiac Surgery

BACKGROUND

Postoperative major pulmonary complications (MPCs) continue to be leading causes of increased morbidity and death after cardiac surgery. Although various risk factors have been identified, reports on the association between sleep-disordered breathing (SDB) and postoperative MPCs remain inconclusive.

RESEARCH QUESTION

What is the incidence of the composite end point postoperative MPCs? What are predictors for postoperative MPCs in patients without SDB, with OSA, and with central sleep apnea (CSA) who undergo cardiac surgery?

STUDY DESIGN AND METHODS

In this subanalysis of the ongoing prospective observational study "Impact of Sleep-disordered breathing on Atrial Fibrillation and Perioperative complications in Patients undergoing Coronary Artery Bypass grafting Surgery (CONSIDER AF)," preoperative risk factors for postoperative MPCs were examined in 250 patients who underwent cardiac surgery. Postoperative MPCs (including respiratory failure, acute respiratory distress syndrome, pneumonia, or pulmonary embolism) were registered prospectively within the first seven postoperative days. Presence and type of SDB were assessed the night prior to surgery with the use of portable SDB-monitoring.

RESULTS

Patients with SDB experienced significantly more often postoperative MPCs than patients without SDB (24% vs 7%; P < .001). Multivariable logistic regression analysis showed that CSA (OR, 4.68 [95% CI, 1.78-12.26]; P = .002), heart failure (OR, 2.65 [95% CI, 1.11-6.31]; P = .028), and a history of transient ischemic attack or stroke (OR, 2.73 [95% CI, 1.07-6.94]; P = .035) were associated significantly with postoperative MPCs. Compared with patients without MPCs, those with postoperative MPCs had a significantly longer hospital stay (median days, 9 [25th/75th percentile, 7/13] vs 19 [25th/75th percentile, 11/38]; P < .001).

INTERPRETATION

Among established risk factors for postoperative MPCs, CSA, heart failure, and history of transient ischemic attack or stroke were associated significantly with postoperative MPCs. Our findings contribute to the identification of patients who are at high-risk for postoperative MPCs.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT02877745.

Postoperative respiratory failure: An update on the validity of the Agency for Healthcare Research and Quality Patient Safety Indicator 11 in an era of clinical documentation improvement programs

BACKGROUND

Administrative data can be used to identify cases of postoperative respiratory failure (PRF). We aimed to determine if recent changes to the Agency for Healthcare Research and Quality Patient Safety Indicator 11 (PSI 11) and adoption of clinical documentation improvement programs have improved the validity of PSI 11. We also analyzed reasons why PSI 11 was falsely triggered.

STUDY DESIGN

Cross-sectional study of all eligible discharges using health record data from five academic medical centers between October 1, 2012 and September 30, 2015.

RESULTS

Of 437 flagged records, 434 (99.3%) were accurately coded and 414 (94.7%) represented true clinical PRF. None of the false positive records involved respiratory failure present on admission. Most (78.3%) false positive records required airway protection but did not have respiratory failure.

CONCLUSION

The validity of PSI 11 has improved with recent changes to the code criterion and adoption of clinical documentation improvement programs.

Higher incidence of acute respiratory distress syndrome in cardiac surgical patients with elevated serum procalcitonin concentration: a prospective cohort study

BACKGROUND

Inflammatory response is activated during cardiopulmonary bypass (CPB), which may lead to acute respiratory distress syndrome (ARDS) and procalcitonin (PCT) increases during this inflammatory response. The objective of the study was to validate whether patients with higher serum PCT concentrations have a higher incidence of ARDS.

METHODS

The study was a prospective, single-center, observational cohort study. All patients who received cardiac surgery with CPB were screened for study eligibility. Patients were assigned to the PCT-elevated cohort or the control cohort according to serum PCT concentration on the first postoperative day with a cut-off value of 7.0 ng/mL. Patients were followed up until the 7th postoperative day. The primary endpoint was the incidence of ARDS, which was diagnosed according to the Berlin definition.

RESULTS

A total of 296 patients were enrolled, 64 patients were assigned to the PCT-elevated cohort and 232 patients were assigned to the control cohort. PCT concentration was 16.23 ± 5.9 ng/mL in the PCT-elevated cohort, and 2.70 ± 1.43 ng/mL in the control cohort (p < 0.001). The incidence of ARDS was significantly higher in the PCT-elevated cohort than in the control cohort (21.9% versus 5.6%, p < 0.001). The incidence of moderate-to-severe ARDS was also significantly higher in the PCT-elevated cohort than in the control cohort (10.9% versus 0.4%, p < 0.001). The hazard ratio of ARDS at 7 days in the PCT-elevated cohort, as compared with the control cohort, was 6.8 (95% confidence interval 2.7 to 17.4). The hazard ratio of moderate-to-severe ARDS in the PCT-elevated cohort was 57.3 (95% confidence interval 10.4 to 316.3). The positive predictive value of PCT for ARDS and moderate-to-severe ARDS were 0.242 and 0.121, respectively; the negative predictive value of PCT for ARDS and moderate-to-severe ARDS were 0.952 and 1.0, respectively.

CONCLUSION

Cardiac surgical patients with elevated PCT concentration have a higher incidence of ARDS. Elevated PCT may serve as a warning signal of postoperative ARDS in patients undergoing cardiac surgery with CPB. Study registration Chinese Clinical Trial Registry (ChiCTR-OCH-14005076).

Patient-ventilator asynchrony in conventional ventilation modes during short-term mechanical ventilation after cardiac surgery: randomized clinical trial

INTRODUCTION AND AIM

Studies regarding asynchrony in patients in the cardiac postoperative period are still only a few. The main objective of our study was to compare asynchronies incidence and its index (AI) in 3 different modes of ventilation (volume-controlled ventilation [VCV], pressure-controlled ventilation [PCV] and pressure-support ventilation [PSV]) after ICU admission for postoperative care.

METHODS

A prospective parallel randomised trialin the setting of a non-profitable hospital in Brazil. The participants were patients scheduled for cardiac surgery. Patients were randomly allocated to VCV or PCV modes of ventilation and later both groups were transitioned to PSV mode.

RESULTS

All data were recorded for 5 minutes in each of the three different phases: T1) in assisted breath, T2) initial spontaneous breath and T3) final spontaneous breath, a marking point prior to extubation. Asynchronies were detected and counted by visual inspection method by two independent investigators. Reliability, inter-rater agreement of asynchronies, asynchronies incidence, total and specific asynchrony indexes (AIt and AIspecific) and odds of AI ≥10% weighted by total asynchrony were analysed. A total of 17 patients randomly allocated to the VCV (n=9) or PCV (n=8) group completed the study. High inter-rated agreement for AIt (ICC 0.978; IC95%, 0,963-0.987) and good reliability (r=0.945; p<0.001) were found. Eighty-two % of patients presented asynchronies, although only 7% of their total breathing cycles were asynchronous. Early cycling and double triggering had the highest rates of asynchrony with no difference between groups. The highest odds of AI ≥10% were observed in VCV regardless the phase: OR 2.79 (1.36-5.73) in T1 vs T2, p=0.005; OR 2.61 (1.27-5.37) in T1 vs T3, p=0.009 and OR 4.99 (2.37-10.37) in T2 vs T3, p<0.001.

CONCLUSIONS

There was a high incidence of breathing asynchrony in postoperative cardiac patients, especially when initially ventilated in VCV. VCV group had a higher chance of AI ≥10% and this chance remained high in the following PSV phases.

Association of Perioperative Variables and the Acute Respiratory Distress Syndrome in Liver Transplant Recipients

Background

The assessment of perioperative risk factors for the development of acute respiratory distress syndrome (ARDS) has been described in various surgical populations. However, there are only limited data among patients undergoing liver transplantation (LT), particularly regarding the influence of intraoperative ventilation parameters. We sought to identify the perioperative risk factors associated with the development of ARDS in LT recipients.

Methods

This is a single-center, retrospective cohort study of adult patients who underwent LT at a tertiary academic medical center between January 1, 2006, and January 31, 2016. Postoperative ARDS was identified using the Berlin definition. Multivariable logistic regression analysis was used to identify perioperative risk factors for ARDS.

Results

Of 817 eligible patients who underwent an LT during the study period, 20 (2.45%) developed postoperative ARDS. In the preoperative model, ongoing dialysis (odds ratio, 6.41; P < 0.01) was identified as an independent risk factor of ARDS post-LT. A higher mean peak inspiratory pressure per increase of 1 cm H₂O (odds ratio, 1.31; P < 0.01) was the only independent risk factor in the intraoperative model. Patients who developed ARDS postoperatively had significantly greater intensive care unit and hospital stay compared to non-ARDS patients (P < 0.001). There were no significant differences in the 30-day (P = 0.16) and 1-year (P = 0.51) mortality between the groups.

Conclusions

Dialysis at the time of transplant and elevated intraoperative mean peak inspiratory pressure were associated with the development of ARDS. ARDS post LT was associated with increased intensive care unit and hospital length of stay, but not increased mortality.

Incidence and Risk Factors of Pulmonary Complications after Robot-Assisted Laparoscopic Prostatectomy: A Retrospective Observational Analysis of 2208 Patients at a Large Single Center

Robot-assisted laparoscopic prostatectomy (RALP) is a minimally invasive technique for the treatment of prostate cancer. RALP requires the patient to be placed in the steep Trendelenburg position, along with pneumoperitoneum, which may increase the risk of postoperative pulmonary complications (PPCs). This large single-center retrospective study evaluated the incidence and risk factors of PPCs in 2208 patients who underwent RALP between 2014 and 2017. Patients were divided into those with (PPC group) and without (non-PPC group) PPCs. Postoperative outcomes were evaluated, and univariate and multivariate logistic regression analyses were performed to assess risk factors of PPCs. PPCs occurred in 682 patients (30.9%). Risk factors of PPCs included age (odds ratio [OR], 1.023; p = 0.001), body mass index (OR, 1.061; p = 0.001), hypoalbuminemia (OR, 1.653; p = 0.008), and positive end-expiratory pressure (PEEP) application (OR, 0.283; p < 0.001). The incidence of postoperative complications, rate of intensive care unit (ICU) admission, and duration of ICU stay were significantly greater in the PPC group than in the non-PPC group. In conclusion, the incidence of PPCs in patients who underwent RALP under pneumoperitoneum in the steep Trendelenburg position was 30.9%. Factors associated with PPCs included older age, higher body mass index, hypoalbuminemia, and lack of PEEP.

How to optimize critical care resources in surgical patients: intensive care without physical borders

PURPOSE OF REVIEW

Timely identification of surgery patients at risk of postoperative complications is important to improve the care process, including critical care. This review discusses epidemiology and impact of postoperative complications; prediction scores used to identify surgical patients at risk of complications, and the role of critical care in the postoperative management. It also discusses how critical care may change, with respect to admission to the ICU.

RECENT FINDING

Optimization of postoperative outcome, next to preoperative and intraoperative optimization, consists of using risk scores to early identify patients at risk of developing complications. Critical care consultancy should be performed in the ward after surgery, if necessary. ICUs could work at different levels of intensity, but remain preferably multidisciplinary, combining care for surgical and medical patients. ICU admission should still be considered for those patients at very high risk of postoperative complications, and for those receiving complex or emergency interventions.

SUMMARY

To optimize critical care resources for surgery patients at high risk of postoperative complications, the care process should not only include critical care and monitoring in ICUs, but also strict monitoring in the ward. Prediction scores could help to timely identify patients at risk. More intense care (monitoring) outside the ICU could improve outcome. This concept of critical care without borders could be implemented in the near future to optimize the local resources and improve patient safety. Predict more, do less in ICUs, and more in the ward.

The LAS VEGAS risk score for prediction of postoperative pulmonary complications: An observational study

BACKGROUND

Currently used pre-operative prediction scores for postoperative pulmonary complications (PPCs) use patient data and expected surgery characteristics exclusively. However, intra-operative events are also associated with the development of PPCs.

OBJECTIVE

We aimed to develop a new prediction score for PPCs that uses both pre-operative and intra-operative data.

DESIGN

This is a secondary analysis of the LAS VEGAS study, a large international, multicentre, prospective study.

SETTINGS

A total of 146 hospitals across 29 countries.

PATIENTS

Adult patients requiring intra-operative ventilation during general anaesthesia for surgery.

INTERVENTIONS

The cohort was randomly divided into a development subsample to construct a predictive model, and a subsample for validation.

MAIN OUTCOME MEASURES

Prediction performance of developed models for PPCs.

RESULTS

Of the 6063 patients analysed, 10.9% developed at least one PPC. Regression modelling identified 13 independent risk factors for PPCs: six patient characteristics [higher age, higher American Society of Anesthesiology (ASA) physical score, pre-operative anaemia, pre-operative lower SpO2 and a history of active cancer or obstructive sleep apnoea], two procedure-related features (urgent or emergency surgery and surgery lasting ≥ 1 h), and five intra-operative events [use of an airway other than a supraglottic device, the use of intravenous anaesthetic agents along with volatile agents (balanced anaesthesia), intra-operative desaturation, higher levels of positive end-expiratory pressures > 3 cmH2O and use of vasopressors]. The area under the receiver operating characteristic curve of the LAS VEGAS risk score for prediction of PPCs was 0.78 [95% confidence interval (95% CI), 0.76 to 0.80] for the development subsample and 0.72 (95% CI, 0.69 to 0.76) for the validation subsample.

CONCLUSION

The LAS VEGAS risk score including 13 peri-operative characteristics has a moderate discriminative ability for prediction of PPCs. External validation is needed before use in clinical practice.

TRIAL REGISTRATION

The study was registered at Clinicaltrials.gov, number NCT01601223.

ARDS in Obese Patients: Specificities and Management

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2019. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2019. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Rationale and design of a prospective, multicentre, randomised, conventional treatment-controlled, parallel-group trial to evaluate the efficacy and safety of ulinastatin in preventing acute respiratory distress syndrome in high-risk patients

INTRODUCTION

Acute respiratory distress syndrome (ARDS) is challenging in the intensive care unit (ICU). Although pharmacotherapy for ARDS has gained increasing attention, most trials have yielded negative results. Patients with ARDS have usually been recruited as subjects; the inflammatory reaction has already expanded into a cascade at this point, and its severity is sufficient to damage the lung parenchyma. This raises the question of whether early treatment can prevent ARDS and the associated lung injury. We hypothesise that ARDS is preventable in high-risk patients by administration of ulinastatin as an anti-inflammatory drug before ARDS onset, and we are performing a study to test ulinastatin, a protease inhibitor, versus treatment-as-usual in a group of patients at increased risk for ARDS.

METHODS AND ANALYSIS

This report presents the protocol for a multicentre, randomised, conventional treatment-controlled, parallel group study to prevent the development of ARDS using ulinastatin in high-risk patients. The study population will comprise patients at risk of ARDS in the ICU (≥18 years of age and Lung Injury Prediction Score of >4); patients with confirmed ARDS and some other conditions (immunodeficiency, use of some drugs, etc.) will be excluded. The enrolled patients will be randomly allocated to an ulinastatin group (ulinastatin will be intravenously administered every 8 hours for a total of 600 000 U/day for five consecutive days) or control group. The efficacy of ulinastatin in preventing ARDS development will be evaluated by the incidence rate of ARDS as the primary outcome; the secondary outcomes include the severity of ARDS, clinical outcome, extrapulmonary organ function and adverse events incurred by ulinastatin. Based on the results of preliminary studies and presuming the incidence of ARDS will decrease by 9% in high-risk patients, 880 patients are needed to obtain statistical power of 80%.

ETHICS AND DISSEMINATION

This study has been approved by the Peking University Third Hospital Medical Science Research Ethics Committee. The findings will be published in peer-reviewed journals and presented at national and international conferences.

TRIAL REGISTRATION NUMBER

NCT03089957; Pre-results.

Postoperative remote lung injury and its impact on surgical outcome

Postoperative remote lung injury is a complication following various surgeries and is associated with short and long-term mortality and morbidity. The release of proinflammatory cytokines, damage-associated molecular patterns such as high-mobility group box-1, nucleotide-biding oligomerization domain (NOD)-like receptor protein 3 and heat shock protein, and cell death signalling activation, trigger a systemic inflammatory response, which ultimately results in organ injury including lung injury. Except high financial burden, the outcome of patients developing postoperative remote lung injury is often not optimistic. Several risk factors had been classified to predict the occurrence of postoperative remote lung injury, while lung protective ventilation and other strategies may confer protective effect against it. Understanding the pathophysiology of this process will facilitate the design of novel therapeutic strategies and promote better outcomes of surgical patients. This review discusses the cause and pathology underlying postoperative remote lung injury. Risk factors, surgical outcomes and potential preventative/treatment strategies against postoperative remote lung injury are also addressed.

Approaches and techniques to avoid development or progression of acute respiratory distress syndrome

PURPOSE OF REVIEW

Despite major improvement in ventilation strategies, hospital mortality and morbidity of the acute respiratory distress syndrome (ARDS) remain high. A lot of therapies have been shown to be ineffective for established ARDS. There is a growing interest in strategies aiming at avoiding development and progression of ARDS.

RECENT FINDINGS

Recent advances in this field have explored identification of patients at high-risk, nonspecific measures to limit the risks of inflammation, infection and fluid overload, prevention strategies of ventilator-induced lung injury and patient self-inflicted lung injury, and pharmacological treatments.

SUMMARY

There is potential for improvement in the management of patients admitted to intensive care unit to reduce ARDS incidence. Apart from nonspecific measures, prevention of ventilator-induced lung injury and patient self-inflicted lung injury are of major importance.

Two-way Interaction Effects of Perioperative Complications on 30-Day Mortality in General Surgery

BACKGROUND

Multiple perioperative complications increase mortality risk, and certain complications synergistically increase this risk to a greater degree than might be expected if the complications were independent, but these effects are not well established.

METHODS

This is a retrospective cohort study of 422,827 intraabdominal general surgery patients (American College of Surgeons National Surgical Quality Improvement Program 2005-2011). Eight complications were evaluated: acute respiratory failure (ARF), acute kidney injury (AKI), sepsis/septic shock, stroke, cardiac arrest (CA), myocardial infarction (MI), deep vein thrombosis/pulmonary embolus, and transfusion. Each combination of two complications (28 total) was modeled using a Cox model for 30-day mortality, with adjustment for preoperative comorbidities and risk factors. Additive interaction was determined with the relative excess risk due to interaction (RERI). A positive RERI indicates that the mortality risk with both complications is greater than the sum of the individual mortality risks. Bonferroni correction was applied (α = 0.05/28 = 0.0018).

RESULTS

Seven combinations demonstrated positive interaction: sepsis-CA (RERI 88.1; p < 0.0001), ARF-AKI (RERI 50.5; p < 0.0001), AKI-sepsis (RERI 33.9; p < 0.0001), sepsis-stroke (RERI 33.9; p < 0.0001), ARF-stroke (RERI 32.3; p < 0.0001), AKI-MI (RERI 24.5; p = 0.0013), and ARF-sepsis (RERI 19.2; p < 0.0001). Two combinations demonstrated negative interaction: ARF-CA (RERI -65.1; p = 0.0017) and CA-transfusion (RERI -52.0, p < 0.0001).

CONCLUSIONS

Interaction effects exist between certain complications to increase the risk of short-term mortality. ARF, AKI, sepsis, and stroke were most likely to be involved in positive interactions. Further research into the mechanisms for these effects will be necessary to develop strategies to minimize the compounding effects of multiple complications in the perioperative period.

Frailty Characteristics Predict Respiratory Failure in Patients Undergoing Tracheobronchoplasty

BACKGROUND

Respiratory complications are the leading cause of morbidity in patients undergoing tracheobronchoplasty, yet risk stratification systems on this population are insufficient. We investigated the association between frailty and risk of major respiratory complications after tracheobronchoplasty.

METHODS

A retrospective review was made of 161 consecutive tracheobronchoplasties (October 2002 to September 2016). A frailty index was developed by the deficit-accumulation approach comprising 26 multidomain preoperative variables. The main outcome was a composite endpoint of major respiratory complications within 30 days of surgery. Odds ratio (OR) and 95% confidence interval (CI) were estimated using logistic regression.

RESULTS

The cohort consisted of 103 women (64%), median age of 58 years (interquartile range, 51 to 66) and median FI of 0.25 (interquartile range, 0.1 to 0.3). Forty-eight patients (30%) had respiratory complications, the most common being respiratory failure (n = 27, 16.8%) and pneumonia (n = 25, 15.5%). Severe frailty (frailty index ≥0.33) was strongly associated with major respiratory complications (73.8% versus 2.5%; OR 58.8, 95% CI: 9.6 to 358.3). The association with severe frailty appeared stronger for respiratory failure (47.6% versus 2.5%; OR 30, 95% CI: 4.7 to 189.9) than for pneumonia (40.5% versus 0%; OR 35.2. 95% CI: 2.0 to 599.8). Further adjustment for intraoperative crystalloid volume or forced expiratory volume in 1 second moderately attenuated the association between frailty with major respiratory complications (OR 17.4. 95% CI: 2.0 to 150.8), respiratory failure (OR 13.1, 95% CI: 1.7 to 95.8), and pneumonia (OR 20.1, 95% CI: 1.1 to 341.8).

CONCLUSIONS

Frailty, as indicated by frailty index, was associated with major respiratory complications, particularly respiratory failure after tracheobronchoplasty. Preoperative identification of frailty may help guide decision making for patients considering this effective, although arduous procedure.

Fifty Years of Research in ARDS. Is Acute Respiratory Distress Syndrome a Preventable Disease?

Despite significant advances in our understanding and management of patients with acute respiratory distress syndrome (ARDS), the morbidity and mortality from ARDS remains high. Given the limited number of effective treatments for established ARDS, the strategic focus of ARDS research has shifted toward identifying patients with or at high risk of ARDS early in the course of the underlying illness, when strategies to reduce the development and progression of ARDS and associated organ failures can be systematically evaluated. In this review, we summarize the rationale, current evidence, and future directions in ARDS prevention.

Postoperative Pulmonary Complications, Early Mortality, and Hospital Stay Following Noncardiothoracic Surgery: A Multicenter Study by the Perioperative Research Network Investigators

Importance

Postoperative pulmonary complications (PPCs), a leading cause of poor surgical outcomes, are heterogeneous in their pathophysiology, severity, and reporting accuracy.

Objective

To prospectively study clinical and radiological PPCs and respiratory insufficiency therapies in a high-risk surgical population.

Design, Setting, and Participants

We performed a multicenter prospective observational study in 7 US academic institutions. American Society of Anesthesiologists physical status 3 patients who presented for noncardiothoracic surgery requiring 2 hours or more of general anesthesia with mechanical ventilation from May to November 2014 were included in the study. We hypothesized that PPCs, even mild, would be associated with early postoperative mortality and use of hospital resources. We analyzed their association with modifiable perioperative variables.

Exposure

Noncardiothoracic surgery.

Main Outcomes and Measures

Predefined PPCs occurring within the first 7 postoperative days were prospectively identified. We used bivariable and logistic regression analyses to study the association of PPCs with ventilatory and other perioperative variables.

Results

This study included 1202 patients who underwent predominantly abdominal, orthopedic, and neurological procedures. The mean (SD) age of patients was 62.1 (13.8) years, and 636 (52.9%) were men. At least 1 PPC occurred in 401 patients (33.4%), mainly the need for prolonged oxygen therapy by nasal cannula (n = 235; 19.6%) and atelectasis (n = 206; 17.1%). Patients with 1 or more PPCs, even mild, had significantly increased early postoperative mortality, intensive care unit (ICU) admission, and ICU/hospital length of stay. Significant PPC risk factors included nonmodifiable (emergency [yes vs no]: odds ratio [OR], 4.47, 95% CI, 1.59-12.56; surgical site [abdominal/pelvic vs nonabdominal/pelvic]: OR, 2.54, 95% CI, 1.67-3.89; and age [in years]: OR, 1.03, 95% CI, 1.02-1.05) and potentially modifiable (colloid administration [yes vs no]: OR, 1.75, 95% CI, 1.03-2.97; preoperative oxygenation: OR, 0.86, 95% CI, 0.80-0.93; blood loss [in milliliters]: OR, 1.17, 95% CI, 1.05-1.30; anesthesia duration [in minutes]: OR, 1.14, 95% CI, 1.05-1.24; and tidal volume [in milliliters per kilogram of predicted body weight]: OR, 1.12, 95% CI, 1.01-1.24) factors.

Conclusions and Relevance

Postoperative pulmonary complications are common in patients with American Society of Anesthesiologists physical status 3, despite current protective ventilation practices. Even mild PPCs are associated with increased early postoperative mortality, ICU admission, and length of stay (ICU and hospital). Mild frequent PPCs (eg, atelectasis and prolonged oxygen therapy need) deserve increased attention and intervention for improving perioperative outcomes.