A scoring system predicting the risk for intensive care unit admission for complications after major lung resection: a multicenter analysis

Preoperative quality of life predicts complications in thoracic surgery: a retrospective cohort study

OBJECTIVES

Patients undergoing thoracic surgery experience high complication rates. It is uncertain whether preoperative health-related quality of life (HRQOL) measurements can predict patients at higher risk for postoperative complications. The objective of this study was to determine the association between preoperative HRQOL and postoperative complications among patients undergoing thoracic surgery.

METHODS

This was a retrospective cohort study of prospectively collected data. Consecutive patients undergoing elective thoracic surgery at a Canadian tertiary care centre between January 2018 and January 2019 were included. Patient HRQOL was measured using the Euroqol-5 Dimension (EQ-5D) survey. Complications were recorded using the Ottawa Thoracic Morbidity and Mortality system. Uni- and multivariable analysis were performed.

RESULTS

Of 515 surgeries performed, 133 (25.8%) patients experienced at least 1 postoperative complication; 345 (67.0%) patients underwent surgery for malignancy. A range of 271 (52.7%) to 310 (60.2%) patients experienced pain/discomfort at each timepoint. On multivariable analysis, lower preoperative EQ-5D visual analogue scale scores were significantly associated with postoperative complications (adjusted odds ratio 0.97, 95% confidence interval 0.95-0.99; P = 0.01). Presence of malignancy was not independently associated with complications (P = 0.68).

CONCLUSIONS

Self-reported preoperative HRQOL can predict incidence of postoperative complications among patients undergoing thoracic surgery. Assessments of preoperative HRQOL may help identify patients at higher risk for developing complications. These findings could be used to direct preoperative risk-mitigation strategies in areas of HRQOL where patients suffer most, such as pain. The full perioperative trajectory of patient HRQOL should be discerned to identify subsets of patients who share common risk factors.

Intensive care unit admission criteria: a scoping review

Background

Effectively identifying deteriorated patients is vital to the development and validation of automated systems designed to predict clinical deterioration. Existing outcome measures used for this purpose have significant limitations. Published criteria for admission to high acuity inpatient areas may represent markers of patient deterioration and could inform the development of alternate outcome measures.

Objectives

In this scoping review, we aimed to characterise published criteria for admission of adult inpatients to high acuity inpatient areas including intensive care units. A secondary aim was to identify variables that are extractable from electronic health records (EHRs).

Data sources

Electronic databases PubMed and ProQuest EBook Central were searched to identify papers published from 1999 to date of search. We included publications which described prescriptive criteria for admission of adult inpatients to a clinical area with a higher level of care than a general hospital ward.

Charting methods

Data was extracted from each publication using a standardised data-charting form. Admission criteria characteristics were summarised and cross-tabulated for each criterion by population group.

Results

Five domains were identified: diagnosis-based criteria, clinical parameter criteria, organ-support criteria, organ-monitoring criteria and patient baseline criteria. Six clinical parameter-based criteria and five needs-based criteria were frequently proposed and represent variables extractable from EHRs. Thresholds for objective clinical parameter criteria varied across publications, and by disease subgroup, and universal cut-offs for criteria could not be elucidated.

Conclusions

This study identified multiple criteria which may represent markers of deterioration. Many of the criteria are extractable from the EHR, making them potential candidates for future automated systems. Variability in admission criteria and associated thresholds across the literature suggests clinical deterioration is a heterogeneous phenomenon which may resist being defined as a single entity via a consensus-driven process.

The Impact of Postoperative Pulmonary Complications on Perioperative Outcomes in Patients Undergoing Pneumonectomy: A Multicenter Retrospective Cohort Study of the German Thorax Registry

Postoperative pulmonary complications have a deleterious impact in regards to thoracic surgery. Pneumonectomy is associated with the highest perioperative risk in elective thoracic surgery. The data from 152 patients undergoing pneumonectomy in this multicenter retrospective study were extracted from the German Thorax Registry database and presented after univariate and multivariate statistical processing. This retrospective study investigated the incidence of postoperative pulmonary complications (PPCs) and their impact on perioperative morbidity and mortality. Patient-specific, preoperative, procedural, and postoperative risk factors for PPCs and in-hospital mortality were analyzed. A total of 32 (21%) patients exhibited one or more PPCs, and 11 (7%) died during the hospital stay. Multivariate stepwise logistic regression identified a preoperative FEV1 < 50% (OR 9.1, 95% CI 1.9-67), the presence of medical complications (OR 7.4, 95% CI 2.7-16.2), and an ICU stay of more than 2 days (OR 14, 95% CI 3.9-59) as independent factors associated with PPCs. PPCs (OR 13, 95% CI 3.2-52), a preoperative FEV1 < 60% in patients with previous pulmonary infection (OR 21, 95% CI 3.2-52), and continued postoperative mechanical ventilation (OR 8.4, 95% CI 2-34) were independent factors for in-hospital mortality. Our data emphasizes that PPCs are a significant risk factor for morbidity and mortality after pneumonectomy. Intensified perioperative care targeting the underlying risk factors and effects of PPCs, postoperative ventilation, and preoperative respiratory infections, especially in patients with reduced pulmonary reserve, could improve patient outcomes.

Risk Factors for Postoperative Pulmonary Complications Leading to Increased Morbidity and Mortality in Patients Undergoing Thoracic Surgery for Pleural Empyema

OBJECTIVES

Surgery for pleural empyema carries a high burden of morbidity and mortality. The authors investigated the incidence of postoperative pulmonary complications (PPCs) and their effects on perioperative morbidity and mortality. Patient-specific, preoperative, procedural, and postoperative risk factors for PPCs were analyzed.

DESIGN

Retrospective observational study.

SETTING

A single, large university hospital.

PARTICIPANTS

A total of 250 adult patients were included who underwent thoracic surgery for pleural empyema between January 2017 and December 2021.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A total of 250 patients with pleural empyema underwent thoracic surgery by video-assisted thoracoscopic surgery (49%; n = 122) or open thoracotomy (51%; n = 128). A proportion (42% [105]) of patients had ≥1 PPCs; 28% (n = 70) had to undergo resurgery; and 10% (n = 25) were re-admitted unexpectedly to the ICU. Preoperative respiratory failure (odds ratio [OR]: 5.8, 95% CI: 2.4-13.1), general anesthesia without regional analgesia techniques (OR: 2.9, 95% CI: 1.4-5.8), open thoracotomy and subsequent resurgery (OR: 3.9, 95% CI 1.5-9.9), surgery outside the regular working hours (OR: 3.1, 95% CI 1.2-8.2), and postoperative sepsis (OR: 2.6, 95% CI 1.1-6.8) were identified as independent risk factors for PPCs. Postoperative pulmonary complications were independent factors for unplanned intensive care unit admission (OR: 10.5, 95% CI 2.1-51 for >1 PPC), death within 360 days (OR: 4.5, 95% CI 2.2-12.3 for ≥2 PPCs), and death within 30 days for ≥1 PPCs (OR: 1.2, 95% CI 1.1-1.3).

CONCLUSIONS

The incidence of PPCs is a significant risk factor for morbidity and mortality after surgery for pleural empyema. Targeting the risk factors identified in this study could improve patient outcomes.

The Impact of Initial Postoperative Destination on Unplanned Critical Care Admissions After Lung Resection

OBJECTIVES

Despite an increasing proportion of patients undergoing lung resection being managed postoperatively in a ward-based environment, studies analyzing the impact of initial postoperative destination (IPD) on perioperative outcomes and unplanned critical care admission (UCCA) are lacking.

DESIGN

A single-center retrospective review.

SETTING

A cardiothoracic surgery center in the Northwest of England.

PARTICIPANTS

A total of 3,841 patients between 2012 and 2018.

INTERVENTIONS

All patients underwent lung resection. Patients were classified as either IPD ward or IPD critical care.

MEASUREMENTS AND MAIN RESULTS

Outcomes assessed included in-hospital and 90-day mortality and UCCA. Differences in mortality rates between groups were assessed using the chi-square test. Multivariate logistic regression analyses were performed to identify variables independently associated with 90-day mortality and UCCA. In total, 23.8% (n = 913) of patients went to critical care as their IPD. Overall in-hospital mortality was 1.6% (n = 62), and 90-day mortality was 2.9% (n = 112). The rate of UCCA was 10.5% (n = 404) and was significantly higher for IPD ward patients compared to IPD critical care patients (11.9% v 6.2%, p < 0.001). The 90-day mortality rates after UCCA were 5.2% (IPD ward) and 19.3% (IPD critical care) (p < 0.001). Advanced age, worse pulmonary function, IPD ward, and timing of surgery were all independently associated with UCCA.

CONCLUSIONS

Most patients undergoing lung resection can be managed safely postoperatively in a ward-based environment. Short-term mortality is higher after UCCA, with patients who experience readmission to critical care at the highest risk of death. Patients should receive additional monitoring immediately following discharge from critical care.

Development and Validation of a Multivariable Prediction Model for Postoperative Intensive Care Unit Stay in a Broad Surgical Population

IMPORTANCE

Despite limited capacity and expensive cost, there are minimal objective data to guide postoperative allocation of intensive care unit (ICU) beds. The Surgical Risk Preoperative Assessment System (SURPAS) uses 8 preoperative variables to predict many common postoperative complications, but it has not yet been evaluated in predicting postoperative ICU admission.

OBJECTIVE

To determine if the SURPAS model could accurately predict postoperative ICU admission in a broad surgical population.

DESIGN, SETTING, AND PARTICIPANTS

This decision analytical model was a retrospective, observational analysis of prospectively collected patient data from the 2012 to 2018 American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database, which were merged with individual patients' electronic health record data to capture postoperative ICU use. Multivariable logistic regression modeling was used to determine how the 8 preoperative variables of the SURPAS model predicted ICU use compared with a model inputting all 28 preoperatively available NSQIP variables. Data included in the analysis were collected for the ACS NSQIP at 5 hospitals (1 tertiary academic center, 4 academic affiliated hospitals) within the University of Colorado Health System between January 1, 2012, and December 31, 2018. Included patients were those undergoing surgery in 9 surgical specialties during the 2012 to 2018 period. Data were analyzed from May 29 to July 30, 2021.

EXPOSURE

Surgery in 9 surgical specialties, including general, gynecology, orthopedic, otolaryngology, plastic, thoracic, urology, vascular, and neurosurgery.

MAIN OUTCOMES AND MEASURES

Use of ICU care up to 30 days after surgery.

RESULTS

A total of 34 568 patients were included in the analytical data set: 32 032 (92.7%) in the cohort without postoperative ICU use and 2545 (7.4%) in the cohort with postoperative ICU use (no ICU use: mean [SD] age, 54.9 [16.6] years; 18 188 women [56.8%]; ICU use: mean [SD] age, 60.3 [15.3] years; 1333 men [52.4%]). For the internal chronologic validation of the 7-variable SURPAS model, data from 2012 to 2016 were used as the training data set (n = 24 250, 70.2% of the total sample size of 34 568) and data from 2017 to 2018 were used as the test data set (n = 10 318, 29.8% of the total sample size of 34 568). The C statistic improved in the test data set compared with the training data set (0.933; 95% CI, 0.924-0.941 vs 0.922; 95% CI, 0.917-0.928), whereas the Brier score was slightly worse in the test data set compared with the training data set (0.045; 95% CI, 0.042-0.048 vs 0.045; 95% CI, 0.043-0.047). The SURPAS model compared favorably with the model inputting all 28 NSQIP variables, with both having good calibration between observed and expected outcomes in the Hosmer-Lemeshow graphs and similar Brier scores (model inputting all variables, 0.044; 95% CI, 0.043-0.048; SURPAS model, 0.045; 95% CI, 0.042-0.046) and C statistics (model inputting all variables, 0.929; 95% CI, 0.925-0.934; SURPAS model, 0.925; 95% CI, 0.921-0.930).

CONCLUSIONS AND RELEVANCE

Results of this decision analytical model study revealed that the SURPAS prediction model accurately predicted postoperative ICU use across a diverse surgical population. These results suggest that the SURPAS prediction model can be used to help with preoperative planning and resource allocation of limited ICU beds.

Outcome following unplanned critical care admission after lung resection

OBJECTIVES

Patients undergoing lung resection are at risk of perioperative complications, many of which necessitate unplanned critical care unit admission in the postoperative period. We sought to characterize this population, providing an up-to-date estimate of the incidence of unplanned critical care admission, and to assess critical care and hospital stay, resource use, mortality, and outcomes.

METHODS

A multicenter retrospective cohort study of patients undergoing lung resection in participating UK hospitals over 2 years. A comprehensive dataset was recorded for each critical care admission (defined as the need for intubation and mechanical ventilation and/or renal replacement therapy), in addition to a simplified dataset in all patients undergoing lung resection during the study period. Multivariable regression analysis was used to identify factors independently associated with critical care outcome.

RESULTS

A total of 11,208 patients underwent lung resection in 16 collaborating centers during the study period, and 253 patients (2.3%) required unplanned critical care admission with a median duration of stay of 13 (4-28) days. The predominant indication for admission was respiratory failure (68.1%), with 77.8% of patients admitted during the first 7 days following surgery. Eighty-seven (34.4%) died in critical care. On multivariable regression, only the diagnosis of right ventricular dysfunction and the need for both mechanical ventilation and renal-replacement therapy were independently associated with critical care survival; this model, however, had poor predictive value.

CONCLUSIONS

Although resource-intensive and subject to prolonged stay, following unplanned admission to critical care after lung resection outcomes are good for many patients; 65.6% of patients survived to hospital discharge, and 62.7% were discharged to their own home.

Epidural Anesthesia-Analgesia and Recurrence-free Survival after Lung Cancer Surgery: A Randomized Trial

BACKGROUND

Regional anesthesia and analgesia reduce the stress response to surgery and decrease the need for volatile anesthesia and opioids, thereby preserving cancer-specific immune defenses. This study therefore tested the primary hypothesis that combining epidural anesthesia-analgesia with general anesthesia improves recurrence-free survival after lung cancer surgery.

METHODS

Adults scheduled for video-assisted thoracoscopic lung cancer resections were randomized 1:1 to general anesthesia and intravenous opioid analgesia or combined epidural-general anesthesia and epidural analgesia. The primary outcome was recurrence-free survival (time from surgery to the earliest date of recurrence/metastasis or all-cause death). Secondary outcomes included overall survival (time from surgery to all-cause death) and cancer-specific survival (time from surgery to cancer-specific death). Long-term outcome assessors were blinded to treatment.

RESULTS

Between May 2015 and November 2017, 400 patients were enrolled and randomized to general anesthesia alone (n = 200) or combined epidural-general anesthesia (n = 200). All were included in the analysis. The median follow-up duration was 32 months (interquartile range, 24 to 48). Recurrence-free survival was similar in each group, with 54 events (27%) with general anesthesia alone versus 48 events (24%) with combined epidural-general anesthesia (adjusted hazard ratio, 0.90; 95% CI, 0.60 to 1.35; P = 0.608). Overall survival was also similar with 25 events (13%) versus 31 (16%; adjusted hazard ratio, 1.12; 95% CI, 0.64 to 1.96; P = 0.697). There was also no significant difference in cancer-specific survival with 24 events (12%) versus 29 (15%; adjusted hazard ratio, 1.08; 95% CI, 0.61 to 1.91; P = 0.802). Patients assigned to combined epidural-general had more intraoperative hypotension: 94 patients (47%) versus 121 (61%; relative risk, 1.29; 95% CI, 1.07 to 1.55; P = 0.007).

CONCLUSIONS

Epidural anesthesia-analgesia for major lung cancer surgery did not improve recurrence-free, overall, or cancer-specific survival compared with general anesthesia alone, although the CI included both substantial benefit and harm.

EDITOR’S PERSPECTIVE

"Fit for Surgery? What's New in Preoperative Assessment of the High-Risk Patient Undergoing Pulmonary Resection"

Advances in perioperative assessment and diagnostics, together with developments in anesthetic and surgical techniques, have considerably expanded the pool of patients who may be suitable for pulmonary resection. Thoracic surgical patients frequently are perceived to be at high perioperative risk due to advanced age, level of comorbidity, and the risks associated with pulmonary resection, which predispose them to a significantly increased risk of perioperative complications, increased healthcare resource use, and costs. The definition of what is considered "fit for surgery" in thoracic surgery continually is being challenged. However, no internationally standardized definition of prohibitive risk exists. Perioperative assessment traditionally concentrates on the "three-legged stool" of pulmonary mechanical function, parenchymal function, and cardiopulmonary reserve. However, no single criterion should exclude a patient from surgery, and there are other perioperative factors in addition to the tripartite assessment that need to be considered in order to more accurately assess functional capacity and predict individual perioperative risk. In this review, the authors aim to address some of the more erudite concepts that are important in preoperative risk assessment of the patient at potentially prohibitive risk undergoing pulmonary resection for malignancy.

Recommendations from the Italian intersociety consensus on Perioperative Anesthesa Care in Thoracic surgery (PACTS) part 2: intraoperative and postoperative care

Introduction

Anesthetic care in patients undergoing thoracic surgery presents specific challenges that require a multidisciplinary approach to management. There remains a need for standardized, evidence-based, continuously updated guidelines for perioperative care in these patients.

Methods

A multidisciplinary expert group, the Perioperative Anesthesia in Thoracic Surgery (PACTS) group, was established to develop recommendations for anesthesia practice in patients undergoing elective lung resection for lung cancer. The project addressed three key areas: preoperative patient assessment and preparation, intraoperative management (surgical and anesthesiologic care), and postoperative care and discharge. A series of clinical questions was developed, and literature searches were performed to inform discussions around these areas, leading to the development of 69 recommendations. The quality of evidence and strength of recommendations were graded using the United States Preventive Services Task Force criteria.

Results

Recommendations for intraoperative care focus on airway management, and monitoring of vital signs, hemodynamics, blood gases, neuromuscular blockade, and depth of anesthesia. Recommendations for postoperative care focus on the provision of multimodal analgesia, intensive care unit (ICU) care, and specific measures such as chest drainage, mobilization, noninvasive ventilation, and atrial fibrillation prophylaxis.

Conclusions

These recommendations should help clinicians to improve intraoperative and postoperative management, and thereby achieve better postoperative outcomes in thoracic surgery patients. Further refinement of the recommendations can be anticipated as the literature continues to evolve.

The Modified Early Warning Score as a Predictive Tool During Unplanned Surgical Intensive Care Unit Admission

Background: The Modified Early Warning Score (MEWS) has been proposed to warn healthcare providers of potentially serious adverse events. We evaluated this scoring system during unplanned escalation of care in hospitalized surgical patients during a 1-year period.

Methods: Following institutional review board approval, all consecutive, unplanned surgical admissions into the surgical intensive care unit (SICU) during 2016 were entered into this study. MEWS and patient demographics during bedside evaluation for SICU admission were extracted from electronic medical records. Logistic regression was used to analyze the association of MEWS with the incidence of future mortality. P values were set at <0.01 for statistical significance.

Results: In this series of 263 consecutive patients, the incidence of mortality following unplanned escalation of care was 29.3% (confidence interval [CI] 24.1% to 35.0%), ranging from 22% to 57%, with all positive MEWS values. The association of MEWS with future mortality was not statistically significant (P=0.0107). A misclassification rate of 0.29 (CI 0.24 to 0.35) was observed with this association.

Conclusion: MEWS provided no clinical benefit as an early warning system, as mortality was elevated throughout the MEWS scale in this clinical setting. The high misclassification rate indicates MEWS does not provide discriminatory support for patients at risk for mortality.

Perioperative management in thoracic surgery

Thoracic surgery has undergone significant advances in recent years related to anesthetic and surgical techniques and the prevention and management of complications related to the procedure. This has allowed improvements in patient clinical outcomes in surgeries of this kind. Despite the above, thoracic surgery, especially related to pulmonary resection, is not without risk, and is associated to considerable morbidity and mortality. Fast track or enhanced recovery after anesthesia protocols, minimally invasive surgery, and intraoperative anesthetic management improve the prognosis and safety of thoracic surgery. Patients in the postoperative period of major thoracic surgery require intensive surveillance, especially the first 24-72hours after surgery. Admission to the ICU is especially recommended in those patients with comorbidities, a reduced cardiopulmonary reserve, extensive lung resections, and those requiring support due to life-threatening organ failure. During the postoperative period, intensive cardiorespiratory monitoring, proper management of thoracic drainage, aggressive pain control (multimodal analgesia and regional anesthetic techniques), nausea and multimodal rehabilitation are key elements for avoiding adverse events. Medical complications include respiratory failure, arrhythmias, respiratory infections, atelectasis and thromboembolic lung disease. The most frequent surgical complications are hemothorax, chylothorax, bronchopleural fistula and prolonged air leakage. The multidisciplinary management of these patients throughout the perioperative period is essential in order to ensure the best surgical outcomes.

Perioperative Factors for Predicting the Need for Postoperative Intensive Care after Major Lung Resection

Postoperative management after major lung surgery is critical. This study evaluates risk factors for predicting mandatory intensive care unit (ICU) admission immediately after major lung resection. We retrospectively reviewed patients for whom the surgeon requested an ICU bed before major lung resection surgery. Patients were classified into three groups. Univariable and multivariable logistic regression analyses were performed, and a clinical nomogram was constructed. Among 340 patients, 269, 50, and 21 were classified into the no need for ICU, mandatory ICU admission, and late-onset complication groups, respectively. Predictive postoperative diffusion capacity of the lung for carbon monoxide (47.2 (interquartile range (IQR) 43.3–65.7)% versus vs. 67.8 (57.1–79.7)%; p = 0.003, odds ratio (OR) 0.969, 95% confidence interval (CI) 0.95–0.99), intraoperative blood loss (400.00 (250.00–775.00) mL vs. 100.00 (50.00–250.00) mL; p = 0.040, OR 1.001, 95% CI 1.000–1.002), and open thoracotomy (p = 0.030, OR 2.794, 95% CI 1.11–7.07) were significant predictors for mandatory ICU admission. The risk estimation nomogram demonstrated good accuracy in estimating the risk of mandatory ICU admission (concordance index 83.53%). In order to predict the need for intensive care after major lung resection, preoperative and intraoperative factors need to be considered.

Association between anaesthetic technique and unplanned admission to intensive care after thoracic lung resection surgery: the second Association of Cardiothoracic Anaesthesia and Critical Care (ACTACC) National Audit

Unplanned intensive care admission is a devastating complication of lung resection and is associated with significantly increased mortality. We carried out a two-year retrospective national multicentre cohort study to investigate the influence of anaesthetic and analgesic technique on the need for unplanned postoperative intensive care admission. All patients undergoing lung resection surgery in 16 thoracic surgical centres in the UK in the calendar years 2013 and 2014 were included. We defined critical care admission as the unplanned need for either tracheal intubation and mechanical ventilation or renal replacement therapy, and sought an association between mode of anaesthesia (total intravenous anaesthesia vs. volatile) and analgesic technique (epidural vs. paravertebral) and need for intensive care admission. A total of 253 out of 11,208 patients undergoing lung resection in the study period had an unplanned admission to intensive care in the postoperative period, giving an incidence of intensive care unit admission of 2.3% (95%CI 2.0-2.6%). Patients who had an unplanned admission to intensive care unit had a higher mortality (29.00% vs. 0.03%, p < 0.001), and hospital length of stay was increased (26 vs. 6 days, p < 0.001). Across univariate, complete case and multiple imputation (multivariate) models, there was a strong and significant effect of both anaesthetic and analgesic technique on the need for intensive care admission. Patients receiving total intravenous anaesthesia (OR 0.50 (95%CI 0.34-0.70)), and patients receiving epidural analgesia (OR 0.56 (95%CI 0.41-0.78)) were less likely to have an unplanned admission to intensive care after thoracic surgery. This large retrospective study suggests a significant effect of both anaesthetic and analgesic technique on outcome in patients undergoing lung resection. We must emphasise that the observed association does not directly imply causation, and suggest that well-conducted, large-scale randomised controlled trials are required to address these fundamental questions.

Preoperative risk factors for unexpected postoperative intensive care unit admission: A retrospective case analysis

INTRODUCTION

The purpose of this retrospective case-control study was to investigate preoperative risk factors for unexpected postoperative intensive care unit (ICU) admissions in patients undergoing non-emergent surgical procedures in a tertiary medical centre.

METHODS

A medical record review of adult patients undergoing elective non-cardiac and non-transplant major surgical procedures during the period of January 2011 through December 2015 in the operating rooms of a large university hospital was carried out. The primary outcome assessed was unexpected ICU admission, with mortality as a secondary outcome. Demographic data, length of hospital and ICU stay and preoperative comorbidities were also obtained as exposure variables. Propensity score matching was then employed to yield a study and control group.

RESULTS

The group of patients who met inclusion criteria in the study and the control group that did not require ICU admission were obtained, each containing 1191 patients after propensity matching. Patients with acute and/or chronic kidney injury (odds ratio (OR) 2.20 [1.75-2.76]), valvular heart disease (OR: 1.94 [1.33-2.85]), peripheral vascular disease (PVD) (OR: 1.41 [1.02-1.94]) and congestive heart failure (CHF) (OR: 1.80 [1.31-2.46]) were all associated with increased unexpected ICU admission. History of cerebrovascular accident (CVA) (OR: 3.03 [1.31-7.01]) and acute and/or chronic kidney injury (OR: 1.62 [1.12-2.35]) were associated with increased mortality in all patients; CVA was also associated with increased mortality (OR: 3.15 [1.21-8.20]) specifically in the ICU population.

CONCLUSIONS

CHF, acute/chronic kidney injury, PVD and valve disease were significantly associated with increased unexpected ICU admission; patients with CVA suffered increased mortality when admitted to the ICU.

Who Needs to Be Allocated in ICU after Thoracic Surgery? An Observational Study

Background. The effective use of ICU care after lung resections has not been completely studied. The aims of this study were to identify predictive factors for effective use of ICU admission after lung resection and to develop a risk composite measure to predict its effective use. Methods. 120 adult patients undergoing elective lung resection were enrolled in an observational prospective cohort study. Preoperative evaluation and intraoperative assessment were recorded. In the postoperative period, patients were stratified into two groups according to the effective and ineffective use of ICU. The use of ICU care was considered effective if a patient experienced one or more of the following: maintenance of controlled ventilation or reintubation; acute respiratory failure; hemodynamic instability or shock; and presence of intraoperative or postanesthesia complications. Results. Thirty patients met the criteria for effective use of ICU care. Logistic regression analysis identified three independent predictors of effective use of ICU care: surgery for bronchiectasis, pneumonectomy, and age ≥ 57 years. In the absence of any predictors the risk of effective need of ICU care was 6%. Risk increased to 25–30%, 66–71%, and 93% with the presence of one, two, or three predictors, respectively. Conclusion. ICU care is not routinely necessary for all patients undergoing lung resection.

Preoperative predictive factors for intensive care unit admission after pulmonary resection

Objective:

To determine whether the use of a set of preoperative variables can predict the need for postoperative ICU admission.

Methods:

This was a prospective observational cohort study of 120 patients undergoing elective pulmonary resection between July of 2009 and April of 2012. Prediction of ICU admission was based on the presence of one or more of the following preoperative characteristics: predicted pneumonectomy; severe/very severe COPD; severe restrictive lung disease; FEV₁ or DLCO predicted to be < 40% postoperatively; SpO₂ on room air at rest < 90%; need for cardiac monitoring as a precautionary measure; or American Society of Anesthesiologists physical status ≥ 3. The gold standard for mandatory admission to the ICU was based on the presence of one or more of the following postoperative characteristics: maintenance of mechanical ventilation or reintubation; acute respiratory failure or need for noninvasive ventilation; hemodynamic instability or shock; intraoperative or immediate postoperative complications (clinical or surgical); or a recommendation by the anesthesiologist or surgeon to continue treatment in the ICU.

Results:

Among the 120 patients evaluated, 24 (20.0%) were predicted to require ICU admission, and ICU admission was considered mandatory in 16 (66.6%) of those 24. In contrast, among the 96 patients for whom ICU admission was not predicted, it was required in 14 (14.5%). The use of the criteria for predicting ICU admission showed good accuracy (81.6%), sensitivity of 53.3%, specificity of 91%, positive predictive value of 66.6%, and negative predictive value of 85.4%.

Conclusions:

The use of preoperative criteria for predicting the need for ICU admission after elective pulmonary resection is feasible and can reduce the number of patients staying in the ICU only for monitoring.

Development and Validation of an Intraoperative Predictive Model for Unplanned Postoperative Intensive Care

Background:

The allocation of intensive care unit (ICU) beds for postoperative patients is a challenging daily task that could be assisted by the real-time detection of ICU needs. The goal of this study was to develop and validate an intraoperative predictive model for unplanned postoperative ICU use.

Methods:

With the use of anesthesia information management system, postanesthesia care unit, and scheduling data, a data set was derived from adult in-patient noncardiac surgeries. Unplanned ICU admissions were identified (4,847 of 71,996; 6.7%), and a logistic regression model was developed for predicting unplanned ICU admission. The model performance was tested using bootstrap validation and compared with the Surgical Apgar Score using area under the curve for the receiver operating characteristic.

Results:

The logistic regression model included 16 variables: age, American Society of Anesthesiologists physical status, emergency case, surgical service, and 12 intraoperative variables. The area under the curve was 0.905 (95% CI, 0.900–0.909). The bootstrap validation model area under the curves were 0.513 at booking, 0.688 at 3 h before case end, 0.738 at 2 h, 0.791 at 1 h, and 0.809 at case end. The Surgical Apgar Score area under the curve was 0.692. Unplanned ICU admissions had more ICU-free days than planned ICU admissions (5 vs. 4; P &lt; 0.001) and similar mortality (5.6 vs. 6.0%; P = 0.248).

Conclusions:

The authors have developed and internally validated an intraoperative predictive model for unplanned postoperative ICU use. Incorporation of this model into a real-time data sniffer may improve the process of allocating ICU beds for postoperative patients.

Thoracic surgery mortality and morbidity in a university hospital

This study was undertaken to determine the mortality and morbidity of lung resection surgery in the 2,415-bed Siriraj University Hospital, Thailand, and compare them to rates in similar facilities (benchmarking). Demographic and clinical data as well as perioperative outcome variables of patients who underwent elective thoracic surgery from January 2006 to May 2010 were reviewed retrospectively. There were 558 cases of lung resection. Mortality was 0.9% and perioperative morbidity was 8.2%. Univariate analysis identified age >75 years, history of pulmonary disease, preoperative rehabilitation consultation, and operative time >2 h as predictors of mortality and morbidity. With less statistical power, hypertension, cancer, peripheral vascular disease, and thoracotomy also contributed to perioperative outcome. Comparisons with data from the current literature place our results in the range of good quality. Following benchmarking criteria, perioperative outcomes after lung resection surgery in our hospital are good. To further improve quality, we will pay special attention to patients with advanced age and history of pulmonary disease.

Predicting risk of intensive care unit admission after resection for non-small cell lung cancer: a validation study

A model for predicting the risk of emergency, unplanned intensive care unit (ICU) admission after lung resection for lung cancer has been reported. However, it has not been validated outside of the derivation cohort, and the aim of our study was to undertake external validation at our institution. We reviewed a series of consecutive patients who underwent major lung resection for non-small cell lung cancer over a 6-year period. Test performance was evaluated by area under the receiver operator characteristic (ROC) curve. Between 2003 and 2008, 425 patients underwent major lung resections for lung cancer. The mean age (SD) was 65 (10) years and 241 (57%) were men. A total of 77 (18%) patients were admitted to ICU, 47 for elective admission and 30 (7%) for treatment of post-procedure complications. Of the 30 patients admitted for complications, the median length of ICU (interquartile range) stay was 3 days (1-15 days). The mortality rate among these patients was 17%. The area under the ROC curve was 0.66 (95% CI 0.53-0.79). The Brunelli scoring system had moderate discriminating ability to predict the risk of ICU admission after lung resection in our institution.