Anaesthetic and perioperative considerations for extrapleural pneumonectomy and extended pleurectomy/decortication: a scoping review protocol.

INTRODUCTION: Extrapleural pneumonectomy (EPP) and extended pleurectomy/decortication (ePD) are surgical cytoreductive techniques aimed at achieving macroscopic resection in malignant pleural tumours such as pleural mesothelioma, non-mesothelioma pleural malignancies such as thymoma and sarcoma, and rarely for pleural tuberculosis, in a more limited fashion. Despite extensive studies on both surgical techniques and consequences, a significant knowledge gap remains regarding how best to approach the perioperative anaesthesia challenges for EPP and ePD.It is unknown if the risk stratification processes for such surgeries are standardised or what types of functional and dynamic cardiac and pulmonary tests are employed preoperatively to assist in the perioperative risk stratification. Further, it is unknown whether the types of anaesthesia and analgesia techniques employed, and the types of haemodynamic monitoring tools used, impact on outcomes. It is also unknown whether individualised haemodynamic protocols are used to guide the rational use of fluids, vasoactive drugs and inotropes.Finally, there is a dearth of evidence regarding how best to monitor these patients postoperatively or what the most effective enhanced recovery protocols are to best mitigate postoperative complications and accelerate hospital discharge. To increase our knowledge of the perioperative and anaesthetic treatment for patients undergoing EPP/ePD, this scoping review attempts to synthesise the literature and identify these knowledge gaps. METHODS AND ANALYSIS: This scoping review will be conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Review Protocols methodology. Electronic databases, OVID Medline, EMBASE and the Cochrane Library, will be systematically searched for relevant literature corresponding to EPP or ePD and perioperative or anaesthetic management. Data will be analysed and summarised descriptively and organised according to the three perioperative stages: preoperative, intraoperative and postoperative factors in clinical care. ETHICS AND DISSEMINATION: Ethics approval was not required. The findings will be disseminated through professional networks, conference presentations and publications in scientific journals.

Association of perioperative transfusion of fresh frozen plasma and outcomes after cardiac surgery.

BACKGROUND: Fresh frozen plasma (FFP) transfusion is used to manage coagulopathy and bleeding in cardiac surgery patients despite uncertainty about its safety and effectiveness. METHODS: We performed a propensity score matched analysis of the Australian and New Zealand Society of Cardiac and Thoracic Surgeons National Cardiac Surgery Database including patients from 39 centres from 2005 to 2018. We investigated the association of perioperative FFP transfusion with mortality and other clinical outcomes. RESULTS: Of 119,138 eligible patients, we successfully matched 13,131 FFP recipients with 13,131 controls. FFP transfusion was associated with 30-day mortality (odds ratio (OR), 1.41; 99% CI, 1.17-1.71; p < .0001), but not with long-term mortality (hazard ratio (HR), 0.92; 99% CI, 0.85-1.00; p = .007, Holm-Bonferroni α = 0.0004). FFP was also associated with return to theatre for bleeding (OR, 1.97; 99% CI, 1.66-2.34; p < .0001), prolonged intubation (OR, 1.15; 99% CI, 1.05-1.26; p < .0001) and increased chest tube drainage (Mean difference (MD) in mL, 131; 99% CI, 120-141; p < .0001). It was also associated with reduced postoperative creatinine levels (MD in g/L, -6.33; 99% CI, -10.28 to -2.38; p < .0001). CONCLUSION: In a multicentre, propensity score matched analysis, perioperative FFP transfusion was associated with increased 30-day mortality and had variable associations with secondary clinical outcomes.

Platelet Transfusion in Cardiac Surgery: An Entropy-Balanced, Weighted, Multicenter Analysis.

BACKGROUND: Platelet transfusion is common in cardiac surgery, but some studies have suggested an association with harm. Accordingly, we investigated the association of perioperative platelet transfusion with morbidity and mortality. METHODS: We conducted a retrospective analysis of prospectively collected data from the Australian Society of Cardiac and Thoracic Surgeons National Cardiac Surgery Database. We included consecutive adults from 2005 to 2018 across 40 centers. We used inverse probability of treatment weighting via entropy balancing to investigate the association of perioperative platelet transfusion with our 2 primary outcomes, operative mortality (composite of both 30-day and in-hospital mortality) and 90-day mortality, as well as multiple other clinically relevant secondary outcomes. RESULTS: Among 119,132 eligible patients, 25,373 received perioperative platelets and 93,759 were considered controls. After entropy balancing, platelet transfusion was associated with reduced operative mortality (odds ratio [OR], 0.63; 99% confidence interval [CI], 0.47-0.84; P < .0001) and 90-day mortality (OR, 0.66; 99% CI, 0.51-0.85; P < .0001). Moreover, it was associated with reduced odds of deep sternal wound infection (OR, 0.57; 99% CI, 0.36-0.89; P = .0012), acute kidney injury (OR, 0.84; 99% CI, 0.71-0.99; P = .0055), and postoperative renal replacement therapy (OR, 0.71; 99% CI, 0.54-0.93; P = .0013). These positive associations were observed despite an association with increased odds of return to theatre for bleeding (OR, 1.55; 99% CI, 1.16-2.09; P < .0001), pneumonia (OR, 1.26; 99% CI, 1.11-1.44; P < .0001), intubation for longer than 24 hours postoperatively (OR, 1.13; 99% CI, 1.03-1.24; P = .0012), inotrope use for >4 hours postoperatively (OR, 1.14; 99% CI, 1.11-1.17; P < .0001), readmission to hospital within 30 days of surgery (OR, 1.22; 99% CI, 1.11-1.34; P < .0001), as well as increased drain tube output (adjusted mean difference, 89.2 mL; 99% CI, 77.0 mL-101.4 mL; P < .0001). CONCLUSIONS: In cardiac surgery patients, perioperative platelet transfusion was associated with reduced operative and 90-day mortality. Until randomized controlled trials either confirm or refute these findings, platelet transfusion should not be deliberately avoided when considering odds of death.

Fresh frozen plasma transfusion after cardiac surgery.

INTRODUCTION: Fresh frozen plasma (FFP) transfusion in the intensive care unit (ICU) is commonly used to treat coagulopathy and bleeding in cardiac surgery, despite suggestion that it may increase the risk of morbidity and mortality through mechanisms such as fluid overload and infection. METHODS: We retrospectively studied consecutive adults undergoing cardiac surgery from the Medical Information Mart for Intensive Care III and IV databases. We applied propensity score matching to investigate the independent association of within-ICU FFP transfusion with mortality and other key clinical outcomes. RESULTS: Of our 12,043 adults who met inclusion criteria, 1585 (13.2%) received perioperative FFP with a median of 2.48 units per recipient (interquartile range [IQR]: 2.04, 4.33) at a median time of 1.83 h (IQR: 0.75, 3.75) after ICU admission. After propensity matching of 952 FFP recipients to 952 controls, we found no significant association between FFP use and hospital mortality (odds ratio (OR): 1.58; 99% confidence interval (CI): 0.57, 3.71), suspected infection (OR: 0.72; 99% CI: 0.49, 1.08), or acute kidney injury (OR: 1.23; 99% CI: 0.91, 1.67). However, FFP was associated with increased days in hospital (adjusted mean difference (AMD): 1.28; 99% CI: 0.27, 2.41; p = .0050), days in intensive care (AMD: 1.28; 99% CI: 0.27, 2.28; p = .0011), and chest tube output in millilitres up to 8 h after transfusion (AMD: 92.98; 99% CI: 52.22, 133.74; p < .0001). CONCLUSIONS: After propensity matching, FFP transfusion was not associated with increased hospital mortality, but was associated with increased length of stay and no decrease in bleeding in the early post-transfusion period.

Renin-angiotensin-aldosterone system dynamics after targeted blood pressure control using angiotensin II or norepinephrine in cardiac surgery: mechanistic randomised controlled trial.

BACKGROUND: The role of the renin-angiotensin-aldosterone axis in vasoplegia after cardiac surgery remains unclear. We tested the hypothesis that, compared with norepinephrine, infusion of angiotensin II titrated to achieve similar mean arterial pressure (MAP) would suppress plasma renin concentration (PRC) while maintaining aldosterone levels. METHODS: In a double-blind, randomised controlled trial, subjects received either an infusion of angiotensin II or norepinephrine to maintain MAP 70-80 mm Hg from induction of anaesthesia. We compared PRC, aldosterone, dipeptidyl peptidase-3, and angiotensin-converting enzyme 2 activity between treatment groups, before surgery, on ICU admission, and 24 h after surgery. RESULTS: In 60 patients (11.7% female; mean age 68 yr [11 yr]), norepinephrine increased median PRC at ICU admission (median difference [MD] 46 [inter-quartile range, IQR, 3-88] µU ml-1; P<0.001) but angiotensin II did not (MD -3 [IQR -62 to 35] µU ml-1; P=0.36). Aldosterone levels increased with both. The aldosterone:PRC ratio did not change with norepinephrine (MD -0.01 [IQR -0.14 to 0.03] µU ml-1 per ng dl-1, P=0.76) but increased with angiotensin II (MD 0.05 [IQR 0.004-0.26] µU ml-1 per ng dl-1, P<0.001). The upper quartile of PRC before surgery was associated with higher vasopressor requirements when norepinephrine was used to maintain MAP, but not angiotensin II. Dipeptidyl peptidase-3 levels and angiotensin-converting enzyme 2 activities were similar at all time points. CONCLUSIONS: Angiotensin II suppressed renin release while maintaining aldosterone levels compared with norepinephrine. Higher plasma renin concentration before surgery was associated with greater vasopressor requirement for norepinephrine, but not angiotensin II. CLINICAL TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry-ACTRN12621000195853 23/02/2021.

Association of Perioperative Cryoprecipitate Transfusion and Mortality After Cardiac Surgery.

BACKGROUND: Cryoprecipitate is often transfused in patients undergoing cardiac surgery. However, its safety and effectiveness remain uncertain. METHODS: This study was a propensity score-matched analysis of data from the Australian and New Zealand Society of Cardiac and Thoracic Surgeons National Cardiac Surgery Database. The study included adults undergoing cardiac surgery between 2005 and 2018 across 38 sites. The association between perioperative cryoprecipitate transfusion and clinical outcomes was estimated, with a primary outcome of operative mortality. RESULTS: Of 119,132 eligible patients, 11,239 (9.43%) patients received cryoprecipitate. The median cumulative dose was 8 U (interquartile range, 5-10 U). After propensity score matching, we matched 9055 cryoprecipitate recipients to 9055 control subjects. Postoperative cryoprecipitate transfusion was associated with reduced operative mortality (odds ratio [OR], 0.82; 99% CI, 0.69-0.97; P = .002) and long-term mortality (hazard ratio, 0.92; 99% CI, 0.87-0.97; P = .0042). It was also associated with a reduction in acute kidney injury (OR, 0.85; 99% CI, 0.73-0.98; P = .0037) and all-cause infection (OR, 0.77; 99% CI, 0.67-0.88; P < .0001). These findings were observed despite increased rates of return to the operating room (OR, 1.36; 99% CI, 1.22-1.51; P < .0001) and cumulative 4-hour postoperative chest tube output (adjusted mean difference in mL, 97.69; 99% CI, 81.65;113.74; P < .0001). CONCLUSIONS: In a large, multicenter cohort study and after propensity score matching, perioperative transfusion of cryoprecipitate was associated with reduced operative and long-term mortality.

Platelet Transfusion After Cardiac Surgery.

OBJECTIVES: To investigate the independent association of platelet transfusion with hospital mortality and key relevant clinical outcomes in cardiac surgery. DESIGN: A single-center, propensity score-matched, retrospective, cohort study. SETTING: At an American tertiary teaching hospital data from the Medical Information Mart for Intensive Care III and IV databases from 2001 to 2019. PARTICIPANTS: Consecutive adults undergoing coronary artery bypass graft and/or cardiac valvular surgery. INTERVENTIONS: Platelet transfusion during perioperative intensive care unit (ICU) admission. MEASUREMENTS AND MAIN RESULTS: Overall, 12,043 adults met the study inclusion criteria. Of these, 1,621 (13.5%) received apheresis-leukoreduced platelets, with a median of 1.19 units per recipient (IQR: 0.93-1.19) at a median of 1.78 hours (IQR: 0.75-4.25) after ICU admission. The platelet count was measured in 1,176 patients (72.5%) before transfusion, with a median count of 120 × 109/L (IQR: 89.0-157.0), and only 53 (3.3%) had platelet counts below 50 × 109/L. After propensity matching of 1,046 platelet recipients with 1,046 controls, perioperative platelet transfusion carried no association with in-hospital mortality (odds ratio [OR]: 1.28; 99% CI: 0.49-3.35; p = 0.4980). However, it was associated with a pattern of decreased odds of suspected infection (eg, respiratory infection, urinary tract infection, septicaemia, or other; OR: 0.70; 99% CI: 0.50-0.97; p = 0.0050), days in the hospital (adjusted mean difference [AMD]: 0.86; 99% CI: -0.27 to 1.98; p = 0.048), or days in intensive care (AMD 0.83; 99% CI: -0.15 to 1.82; p = 0.0290). CONCLUSIONS: Platelet transfusion was not associated with hospital mortality, but it was associated with decreased odds of suspected infection and with shorter ICU and hospital stays.

Cryoprecipitate Transfusion After Cardiac Surgery.

OBJECTIVES: The association of cryoprecipitate transfusion with patient outcomes after cardiac surgery is unclear. We aimed to investigate the predictors of, and outcomes associated with, postoperative cryoprecipitate transfusion in cardiac surgery patients. METHODS: We used the Medical Information Mart for Intensive Care III and IV databases. We included adults undergoing cardiac surgery, and propensity score matched cryoprecipitate-treated patients to controls. Using the matched cohort, we investigated the association of cryoprecipitate use with clinical outcomes. The primary outcome was in-hospital mortality. Secondary outcomes were infection, acute kidney injury, intensive care unit length of stay, hospital length of stay, and chest tube output at 2-hour intervals. RESULTS: Of 12,043 eligible patients, 283 (2.35%) patients received cryoprecipitate. The median dose was 5.83 units (IQR 4.17-7.24) given at a median first transfusion time of 1.75 hours (IQR 0.73-4.46) after intensive care unit admission. After propensity scoring, we matched 195 cryoprecipitate recipients to 743 controls. Postoperative cryoprecipitate transfusion was not significantly associated with in-hospital mortality (odds ratio [OR] 1.10; 99% confidence interval [CI] 0.43-2.84; p=0.791), infection (OR 0.77; 99% CI 0.45-1.34; p=0.220), acute kidney injury (OR 1.03; 99% CI 0.65-1.62; p=0.876) or cumulative chest tube output (adjusted mean difference 8 hrs post transfusion, 11 mL; 99% CI -104 to 125; p=0.804). CONCLUSIONS: Although cryoprecipitate was typically given to sicker patients with more bleeding, its administration was not associated with worse outcomes. Large, multicentred studies are warranted to further elucidate cryoprecipitate's safety profile and patterns of use in cardiac surgery.

Predicting atrial fibrillation after cardiac surgery: a scoping review of associated factors and systematic review of existing prediction models.

INTRODUCTION: Postoperative atrial fibrillation (POAF) is common after cardiac surgery and associated with increased hospital length of stay, patient morbidity and mortality. We aimed to identify factors associated with POAF and evaluate the accuracy of available POAF prediction models. METHODS: We screened articles from Ovid MEDLINE® and PubMed Central® (PMC) and included studies that evaluated risk factors associated with POAF or studies that designed or validated POAF prediction models. We only included studies in cardiac surgical patients with sample size n ⩾ 50 and a POAF outcome group ⩾20. We summarised factors that were associated with POAF and assessed prediction model performance by reviewing reported calibration and discriminative ability. RESULTS: We reviewed 232 studies. Of these, 142 fulfilled the inclusion criteria. Age was frequently found to be associated with POAF, while most other variables showed contradictory findings, or were assessed in few studies. Overall, 15 studies specifically developed and/or validated 12 prediction models. Of these, all showed poor discrimination or absent calibration in predicting POAF in externally validated cohorts. CONCLUSIONS: Except for age, reporting of factors associated with POAF is inconsistent and often contradictory. Prediction models have low discrimination, missing calibration statistics, are at risk of bias and show limited clinical applicability. This suggests the need for studies that prospectively collect AF relevant data in large cohorts and then proceed to validate findings in external data sets.

Linkage of Australian national registry data using a statistical linkage key.

BACKGROUND: Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581). Our aim was to investigate the ability to link data using SLK-581 between two national databases, and to compare this linkage to that achieved with direct identifiers or other non-identifying variables. METHODS: The Australian and New Zealand Society of Cardiothoracic Surgeons database (ANZSCTS-CSD) contains fully identified data. The Australian and New Zealand Intensive Care Society database (ANZICS-APD) contains non-identified data together with SLK-581. Identifying data is removed at participating hospitals prior to central collation and storage. We used the local hospital ANZICS-APD data at a large single tertiary centre prior to deidentification and linked this to ANZSCTS-CSD data. We compared linkage using SLK-581 to linkage using non-identifying variables (dates of admission and discharge, age and sex) and linkage using a complete set of unique identifiers. We compared the rate of match, rate of mismatch and clinical characteristics between unmatched patients using the different methods. RESULTS: There were 1283 patients eligible for matching in the ANZSCTS-CSD. 1242 were matched using unique identifiers. Using non-identifying variables 1151/1242 (92.6%) patients were matched. Using SLK-581, 1202/1242 (96.7%) patients were matched. The addition of non-identifying data to SLK-581 provided few additional patients (1211/1242, 97.5%). Patients who did not match were younger, had a higher mortality risk and more non-standard procedures vs matched patients. The differences between unmatched patients using different matching strategies were small. CONCLUSION: All strategies provided an acceptable linkage. SLK-581 improved the linkage compared to non-identifying variables, but was not as successful as direct identifiers. SLK-581 may be used to improve linkage between national registries where identifying information is not available or cannot be released.

The Association Between Pulsatile Cardiopulmonary Bypass and Acute Kidney Injury After Cardiac Surgery: A Before-and-After Study.

OBJECTIVES: To investigate the association between pulsatile perfusion and cardiac surgery-associated acute kidney injury. DESIGN: An uncontrolled, retrospective before-and-after study. SETTING: Single tertiary hospital. PARTICIPANTS: A total of 2,489 patients undergoing cardiac surgery with cardiopulmonary bypass (CPB). INTERVENTIONS: Pulsatile versus nonpulsatile perfusion. MEASUREMENTS AND MAIN RESULTS: Data for nonpulsatile perfusion was collected from April 1, 2016, to March 31, 2017 (n = 1,223). A practice change to universal pulsatile CPB occurred on April 3, 2017. Data for pulsatile perfusion was collected from May 1, 2017, to June 30, 2018 (n = 1,266). The primary outcome was the incidence of acute kidney injury (AKI) after cardiac surgery. Multivariable analysis was carried out to adjust for known confounders. Secondary outcomes included AKI stage, stroke, length of stay, and mortality. Subgroup analyses were carried out using prolonged CPB and chronic kidney disease. The primary outcome, incidence of AKI, did not differ between the nonpulsatile control group and the pulsatile group (23.9% v 25.4%, p = 0.392). The pulsatile group was not associated with AKI in the multivariable analysis (Odds ratio 1.09, p = 0.413). There were no differences in stages of AKI in the nonpulsatile group v pulsatile group (13.6% v 14.9%, 2.9% v 4.3%, and 7.4% v 6.1% for stages 1, 2, and 3, respectively, p = 0.12). There were no differences in subgroup analyses or secondary outcomes. CONCLUSIONS: There was no association found between kidney injury and pulsatile perfusion. It is likely that there is either no association between pulsatile perfusion and reduced kidney injury or that the difference is extremely small.

Development and Validation of a Score to Identify Cardiac Surgery Patients at High Risk of Prolonged Mechanical Ventilation.

OBJECTIVE: To develop and validate a score for the early identification of cardiac surgery patients at high risk of prolonged mechanical ventilation (MV) who may be suitable targets for interventional trials. DESIGN: Retrospective analysis. SETTING: Tertiary intensive care unit. PARTICIPANTS: Cardiac surgery patients. INTERVENTIONS: Observational study. MEASUREMENTS AND MAIN RESULTS: The study comprised 1,994 patients. Median age was 67 years, and 1,457 patients (74%) were male. Median duration of MV was 9.4 hours. A total of 229 (11%), 182 (9%), and 127 (6%) patients received MV for ≥24, ≥36, and ≥48 hours, respectively. In-hospital mortality was 13%, 15%, and 17%, respectively. For the study model, all preoperative, intraoperative, and early (first 4 hours) postoperative variables were considered. A multivariable logistic regression model was developed, and a predictive scoring system was derived. Using MV ≥24 hours as the primary outcome, the model performance in the development set was good with a c-index of 0.876 (95% confidence interval 0.846-0.905) and a Brier's score of 0.062. In the validation set, the c-index was 0.907 (0.867-0.948), Brier's score was 0.059, and the model remained well calibrated. CONCLUSIONS: The authors developed a simple score to predict prolonged MV after cardiac surgery. This score, if externally validated, is potentially suitable for identifying a high-risk target population for future randomized controlled trials of postoperative care after cardiac surgery.

Acute Risk Change: An Innovative Measure of Operative Adverse Events and Perioperative Team Performance.

OBJECTIVES: Cardiac surgical risk models predict mortality preoperatively, whereas intensive care unit (ICU) models predict mortality postoperatively. Finding a large difference between the 2 (an acute risk change [ARC]) may reflect an alteration in the status of the patient related to the surgery. An adverse ARC was associated with morbidity and mortality in an Australian population. The aims of this study were to validate ARC in a UK population and to investigate the possible mechanisms behind ARC. DESIGN: This was a retrospective case-control study. SETTING: Single, high-volume cardiothoracic hospital. PARTICIPANTS: Data from 4,842 cardiac surgical patients were collected between 2013 and 2015. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: EuroSCORE was recalibrated to each preceding year's data. ARC was defined as postoperative minus preoperative percentage mortality risk. Association among ARC, morbidity, and mortality was tested. Cases with large adverse ARC (greater than +15%) were compared with cases with large favorable ARC (less than -10%) with regard to intraoperative adverse events, unmeasured patient risk factors, and postoperative events. Adverse ARC was associated with hospital mortality, ICU stay, ICU readmission, renal support, prolonged intubation and return to the operating room (p < 0.001). Intraoperative adverse events occurred in 23 of 33 patients with adverse ARC; however, only 2 of 17 patients with favorable ARC reported adverse events (p < 0.001). Unmeasured risk factors were present in 48% of patients in the adverse ARC group. CONCLUSION: ARC is a readily available and sensitive marker that correlates strongly with morbidity and mortality. The use of ARC in local and national quality monitoring could identify areas for improvement of the quality of cardiac surgical care.

Measuring the quality of perioperative care in cardiac surgery.

Quality of care is of increasing importance in health and surgical care. In order to maintain and improve quality, we must be able to measure it and identify variation. In this narrative review, we aim to identify measures used in the assessment of quality of care in cardiac surgery and to evaluate their utility. The electronic databases Pubmed/MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews, and CINAHL were searched for original published studies using the terms 'cardiac surgery' and 'quality or outcome or process or structure' as either keywords in the title or text or MeSH terms. Secondary searches and identification of references from original articles were carried out. We found a total of 54 original articles evaluating measurements of quality. While structure, process, and outcome indicators remain the mainstay of quality measurement, new and innovative methods of risk assessment have improved reliability and discrimination. Continuous assessment provides a promising method of both maintaining and improving quality of care. Future studies should focus on long-term and patient-centred outcomes, such as quality-of-life measures.

Acute Risk Change for Cardiothoracic Admissions to Intensive Care (ARCTIC index): a new measure of quality in cardiac surgery.

BACKGROUND: Quality of cardiac surgical care may vary between institutions. Mortality is low and large numbers are required to discriminate between hospitals. Measures other than mortality may provide better comparisons. OBJECTIVES: To develop and assess the Acute Risk Change for Cardiothoracic Admissions to Intensive Care (ARCTIC) index, a new performance measure for cardiothoracic admissions to intensive care units (ICUs). METHODS: The Australian and New Zealand Society of Cardiac and Thoracic Surgeons database and Australian and New Zealand Intensive Care Society Adult Patient Database were linked. Logistic regression was used to generate a predicted risk of death first from preoperative data using the previously validated Allprocscore and second on admission to an ICU using Acute Physiology and Chronic Health Evaluation III score. Change in risk as a percentage (ARCTIC) was calculated for each patient. The validity of ARCTIC as a marker of quality was assessed by comparison with intraoperative variables and postoperative morbidity markers. RESULTS: Sixteen thousand six hundred eighty-seven patients at 21 hospitals from 2008 to 2011 were matched. An increase in ARCTIC score was associated with prolonged cardiopulmonary bypass time (P = .001), intraoperative blood product transfusion (P < .001), reoperation (P < .0001), postoperative renal failure (P < .0001), prolonged ventilation (P < .0001), and stroke (P = .001). CONCLUSIONS: The ARCTIC index is associated with known markers of perioperative performance and postoperative morbidity. It may be used as an overall marker of quality for cardiac surgery. Further work is required to assess ARCTIC as a method to discriminate between cardiac surgical units.

Single-centre experience of donation after cardiac death.

OBJECTIVES: To describe the design, development and implementation of an organ and tissue donation after cardiac death (DCD) program, evaluate its success and assess its impact on tissue and organ availability and the number of donors after brain death. DESIGN, PARTICIPANTS AND SETTING: Prospective collection of patient characteristics and outcomes for actual and potential donors from 2000 to 2010, thus including the 5 years after the implementation of a DCD program at a major Australian tertiary hospital in 2006. MAIN OUTCOME MEASURES: The number and type of donors before and after implementation of the DCD program, and subsequent numbers of solid organ and tissue donations. RESULTS: The DCD program was associated with an increase in overall donor numbers. There were 80 donors (20 DCD and 60 donation after brain death [DBrD]) after 2006, compared with 51 DBrD donors in the previous 5 years. Four of the DBrD donors were patients who were initially considered for DCD. DCD accounted for eight of the total 19 donors in 2009 and seven of the total 23 donors in 2010. There were 62 solid organ and 35 tissue and cornea transplants as a result of the DCD program. CONCLUSIONS: Successful implementation of a DCD program is possible and has led to an increase in overall donor numbers and organs transplanted without any reduction in DBrD donors. The widespread implementation of DCD across Australia may help reduce the shortfall of organs for transplantation.

Mortality in adult intensive care patients with severe systemic inflammatory response syndromes is strongly associated with the hypo-immune TNF -238A polymorphism.

The systemic inflammatory response syndrome (SIRS) is associated with activation of innate immunity. We studied the association between mortality and measures of disease severity in the intensive care unit (ICU) and functional polymorphisms in genes coding for Toll-like receptor 4 (TLR4), macrophage migratory inhibitory factor (MIF), tumour necrosis factor (TNF) and lymphotoxin-alpha (LTA). Two hundred thirty-three patients with severe SIRS were recruited from one general adult ICU in a tertiary centre in the UK. DNA from patients underwent genotyping by 5' nuclease assay. Genotype was compared to phenotype. Primary outcome was mortality in ICU. Minor allele frequencies were TLR4 +896G 7%, MIF 173C 16%, TNF -238A 10% and LTA +252G 34%. The frequency of the hypoimmune minor allele TNF -238A was significantly higher in patients who died in ICU compared to those who survived (p = 0.0063) as was the frequency of the two haplotypes LTA +252G, TNF -1031T, TNF -308G, TNF -238A and LTA +252G, TNF-1031T, TNF-308A and TNF-238A (p = 0.0120 and 0.0098, respectively). These findings re-enforce the view that a balanced inflammatory/anti-inflammatory response is the most important determinant of outcome in sepsis. Genotypes that either favour inflammation or its counter-regulatory anti-inflammatory response are likely to influence mortality and morbidity.