Teus H. Kappen

Effects of the introduction of the WHO "Surgical Safety Checklist" on in-hospital mortality: a cohort study.

Objective:To evaluate the effect of implementation of the WHOs Surgical Safety Checklist on mortality and to determine to what extent the potential effect was related to checklist compliance. Background:Marked reductions in postoperative complications after implementation of a surgical checklist have been reported. As compliance to the checklists was reported to be incomplete, it remains unclear whether the benefits obtained were through actual completion of a checklist or from an increase in overall awareness of patient safety issues. Methods:This retrospective cohort study included 25,513 adult patients undergoing non-day case surgery in a tertiary university hospital. Hospital administrative data and electronic patient records were used to obtain data. In-hospital mortality within 30 days after surgery was the main outcome and effect estimates were adjusted for patient characteristics, surgical specialty and comorbidity. Results:After checklist implementation, crude mortality decreased from 3.13% to 2.85% (P = 0.19). After adjustment for baseline differences, mortality was significantly decreased after checklist implementation (odds ratio [OR] 0.85; 95% CI, 0.73–0.98). This effect was strongly related to checklist compliance: the OR for the association between full checklist completion and outcome was 0.44 (95% CI, 0.28–0.70), compared to 1.09 (95% CI, 0.78–1.52) and 1.16 (95% CI, 0.86–1.56) for partial or noncompliance, respectively. Conclusions:Implementation of the WHO Surgical Checklist reduced in-hospital 30-day mortality. Although the impact on outcome was smaller than previously reported, the effect depended crucially upon checklist compliance.

Incidence of intraoperative hypotension as a function of the chosen definition: literature definitions applied to a retrospective cohort using automated data collection.

Background: Intraoperative hypotension (IOH) is a common side effect of general anesthesia and has been reported to be associated with adverse perioperative outcomes. These associations were found using different definitions for IOH. It is unknown whether the incidences of IOH found with those different definitions are comparable. The authors aimed to describe the relation between the chosen definition and incidence of IOH. Methods: First, a systematic literature search was performed to identify recent definitions of IOH that have been used in the anesthesia literature. Subsequently, these definitions were applied to a cohort of 15,509 consecutive adult patients undergoing noncardiac surgery during general anesthesia. The incidence of IOH according to the different threshold values was calculated, and the effect of a defined minimal duration of a hypotensive episode was studied. Results: Many different definitions of IOH were found. When applied to a cohort of patients, these different definitions resulted in different IOH incidences. Any episode of systolic blood pressure below 80 mmHg was found in 41% of the patients, whereas 93% of the patients had at least one episode of systolic blood pressure more than 20% below baseline. Both definitions are frequently used in the literature. The relation between threshold values from the literature and IOH incidence shows an S-shaped cumulative incidence curve, with occurrence frequencies of IOH varying from 5% to 99%. Conclusions: There is no widely accepted definition of IOH. With varying definitions, many different incidences can be reproduced. This might have implications for previously described associations between IOH and adverse outcomes.

Procedure-specific risk factor analysis for the development of severe postoperative pain.

Background: Many studies have analyzed risk factors for the development of severe postoperative pain with contradictory results. To date, the association of risk factors with postoperative pain intensity among different surgical procedures has not been studied and compared. Methods: The authors selected precisely defined surgical groups (at least 150 patients each) from prospectively collected perioperative data from 105 German hospitals (2004–2010). The association of age, sex, and preoperative chronic pain intensity with worst postoperative pain intensity was studied with multiple linear and logistic regression analyses. Pooled data of the selected surgeries were studied with random-effect analysis. Results: Thirty surgical procedures with a total number of 22,963 patients were compared. In each surgical procedure, preoperative chronic pain intensity and younger age were associated with higher postoperative pain intensity. A linear decline of postoperative pain with age was found. Females reported more severe pain in 21 of 23 surgeries. Analysis of pooled surgical groups indicated that postoperative pain decreased by 0.28 points (95% CI, 0.26 to 0.31) on the numeric rating scale (0 to 10) per decade age increase and postoperative pain increased by 0.14 points (95% CI, 0.13 to 0.15) for each higher score on the preoperative chronic pain scale. Females reported 0.29 points (95% CI, 0.22 to 0.37) higher pain intensity. Conclusions: Independent of the type and extent of surgery, preoperative chronic pain and younger age were associated with higher postoperative pain. Females consistently reported slightly higher pain scores regardless of the type of surgery. The clinical significance of this small sex difference has to be analyzed in future studies.

Prediction models for clustered data: comparison of a random intercept and standard regression model

BackgroundWhen study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions.MethodsUsing an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated.ResultsThe model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept.ConclusionThe models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Impact of risk assessments on prophylactic antiemetic prescription and the incidence of postoperative nausea and vomiting: a cluster-randomized trial.

Background:Clinical prediction models have been shown to have moderate sensitivity and specificity, yet their use will depend on implementation in clinical practice. The authors hypothesized that implementation of a prediction model for postoperative nausea and vomiting (PONV) would lower the PONV incidence by stimulating anesthesiologists to administer more “risk-tailored” prophylaxis to patients. Methods:A single-center, cluster-randomized trial was performed in 12,032 elective surgical patients receiving anesthesia from 79 anesthesiologists. Anesthesiologists were randomized to either exposure or nonexposure to automated risk calculations for PONV (without patient-specific recommendations on prophylactic antiemetics). Anesthesiologists who treated less than 50 enrolled patients were excluded during the analysis to avoid too small clusters, yielding 11,613 patients and 57 anesthesiologists (intervention group: 5,471 and 31; care-as-usual group: 6,142 and 26). The 24-h incidence of PONV (primary outcome) and the number of prophylactic antiemetics administered per patient were studied for risk-dependent differences between allocation groups. Results:There were no differences in PONV incidence between allocation groups (crude incidence intervention group 41%, care-as-usual group 43%; odds ratio, 0.97; 95% CI, 0.87–1.1; risk-dependent odds ratio, 0.92; 95% CI, 0.80–1.1). Nevertheless, intervention-group anesthesiologists administered more prophylactic antiemetics (rate ratio, 2.0; 95% CI, 1.6–2.4) and more risk-tailored than care-as-usual–group anesthesiologists (risk-dependent rate ratio, 1.6; 95% CI, 1.3–2.0). Conclusions:Implementation of a PONV prediction model did not reduce the PONV incidence despite increased antiemetic prescription in high-risk patients by anesthesiologists. Before implementing prediction models into clinical practice, implementation studies that include patient outcomes as an endpoint are needed.

Incidence of intraoperative hypoxemia in children in relation to age.

BACKGROUND:Although respiratory problems are by far the most frequent complications of pediatric anesthesia, there are currently no reliable data on the incidence of perioperative hypoxemia in children. Most studies investigating the incidence of pediatric respiratory complications were based on self-report. METHODS:We studied the incidence of intraoperative hypoxemia as well as that of pulse oximeter artifacts prospectively in 575 pediatric noncardiac surgery patients aged between 0 and 16 years operated in a tertiary pediatric university hospital. Subsequently, the incidence of intraoperative hypoxemia was determined retrospectively in 8277 patients registered in an anesthesia information management system (AIMS) of the same hospital. RESULTS:In the prospective cohort, at least 1 episode of oxygen saturation (SpO2) ⩽ 90% for at least 1 minute occurred in 69 of 575 cases (12%; 95% confidence interval [CI], 9%–15%). Furthermore, in 35 of 575 (6%; 95% CI, 4%–8%) cases at least 1 true hypoxemic event was observed. In total, 117 episodes of SpO2 ⩽ 90% were observed in the prospective study, of which 3 of 117 could not be specified and 67 of 114 (54%; 95% CI, 42%–65%) episodes were classified as true hypoxemia. False-positive low SpO2 values were mainly caused by dislodgment of the pulse oximeter. In the retrospective analysis, SpO2 ⩽ 90% and SpO2 ⩽ 80% for at least 1 minute were documented in the AIMS in 18% (95% CI, 17%–19%) and 7.5% (95% CI, 7%–8%) of the cases, respectively; 31 and 10 episodes per 100 cases, respectively. The incidence of hypoxemia increased in younger age groups: SpO2 ⩽ 90% for at least 1 minute occurred in 56% (95% CI, 49%–63%) of neonates (170 episodes per 100 cases). CONCLUSIONS:The incidence of intraoperative hypoxemia increased with younger age, with the highest incidence in neonates. Because of the high artifact rate, unvalidated pulse oximeter data in AIMS should be interpreted with caution because only up to 65% of all hypoxemic episodes recorded during pediatric anesthesia were caused by true hypoxia.

Genome-wide association study of monoamine metabolite levels in human cerebrospinal fluid

Studying genetic determinants of intermediate phenotypes is a powerful tool to increase our understanding of genotype–phenotype correlations. Metabolic traits pertinent to the central nervous system (CNS) constitute a potentially informative target for genetic studies of intermediate phenotypes as their genetic underpinnings may elucidate etiological mechanisms. We therefore conducted a genome-wide association study (GWAS) of monoamine metabolite (MM) levels in cerebrospinal fluid (CSF) of 414 human subjects from the general population. In a linear model correcting for covariates, we identified one locus associated with MMs at a genome-wide significant level (standardized β=0.32, P=4.92 × 10−8), located 20 kb from SSTR1, a gene involved with brain signal transduction and glutamate receptor signaling. By subsequent whole-genome expression quantitative trait locus (eQTL) analysis, we provide evidence that this variant controls expression of PDE9A (β=0.21; Punadjusted=5.6 × 10−7; Pcorrected=0.014), a gene previously implicated in monoaminergic transmission, major depressive disorder and antidepressant response. A post hoc analysis of loci significantly associated with psychiatric disorders suggested that genetic variation at CSMD1, a schizophrenia susceptibility locus, plays a role in the ratio between dopamine and serotonin metabolites in CSF. The presented DNA and mRNA analyses yielded genome-wide and suggestive associations in biologically plausible genes, two of which encode proteins involved with glutamate receptor functionality. These findings will hopefully contribute to an exploration of the functional impact of the highlighted genes on monoaminergic transmission and neuropsychiatric phenotypes.

Adaptation of Clinical Prediction Models for Application in Local Settings

Background. When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. Objective. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. Methods. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Results. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Conclusions. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices.

Influence of propofol–opioid vs isoflurane–opioid anaesthesia on postoperative troponin release in patients undergoing coronary artery bypass grafting

BACKGROUND In experimental and clinical studies, volatile anaesthesia has proven to possess cardioprotective properties. However, no randomized controlled trials on the use of isoflurane during the entire cardiac surgical procedure are available. We therefore compared isoflurane-sufentanil vs propofol-sufentanil anaesthesia in patients undergoing coronary artery bypass grafting. METHODS One hundred patients were randomly assigned to receive isoflurane-sufentanil (I) (n = 51) or propofol-sufentanil (P) (n = 49) anaesthesia, aimed at the same hypnotic depth. Postoperative concentrations of cardiac troponin I (cTnI) were followed for 72 h. Secondary outcome variables were length of stay (LOS) in the intensive care unit (ICU) and in hospital, and 30 day and 1 yr mortality and morbidity, defined as acute myocardial infarction, arrhythmias, and cardiac dysfunction. Groups were compared by an on-treatment analysis, using linear mixed models for repeated measures. RESULTS Eighty-four patients completed the protocol (I: 41 vs P: 43). Postoperative cTnI concentrations increased to a maximum of I: 2.72 ng ml(-1) (1.78-5.85) and P: 2.64 ng ml(-1) (1.67-4.83), but did not differ between groups (P=0.11). LOS in the ICU and in hospital was similar [ICU I: 18 (17.0-21.5) vs P: 19 (17.0-22.0) h; hospital I: 9 (6.5-8.0) vs P: 8 (6.0-9.0) days]. Cardiac morbidity and mortality in hospital and 30 days after surgery did not differ between groups. One year after surgery, two patients had died of non-cardiac causes. No between-group differences in cardiac morbidity were found. CONCLUSIONS In this study, the use of isoflurane-sufentanil in comparison with propofol-sufentanil anaesthesia does not afford additional reduction of postoperative cTnI levels.

Intraoperative hypotension and delirium after on-pump cardiac surgery

BACKGROUND Delirium is a common complication after cardiac surgery and may be as a result of inadequate cerebral perfusion. We studied delirium after cardiac surgery in relation to intraoperative hypotension (IOH). METHODS This observational single-centre, cohort study was nested in a randomized trial, on a single intraoperative dose of dexamethasone vs placebo during cardiac surgery. During the first four postoperative days, patients were screened for delirium based on the Confusion Assessment Method (CAM) for Intensive Care Unit on the intensive care unit, CAM on the ward, and by inspection of medical records. To combine depth and duration of IOH, we computed the area under the curve for four blood pressure thresholds. Logistic regression analyses were performed to investigate the association between IOH and the occurrence of postoperative delirium, adjusting for confounding and using a 99% confidence interval to correct for multiple testing. RESULTS Of the 734 included patients, 99 patients (13%) developed postoperative delirium. The adjusted Odds Ratio for the Mean Arterial Pressure <60 mm Hg threshold was 1.04 (99% confidence interval: 0.99-1.10) for each 1000 mm Hg(2) min(2) AUC(2) increase. IOH, as defined according to the other three definitions, was not associated with postoperative delirium either. Deep and prolonged IOH seemed to increase the risk of delirium, but this was not statistically significant. CONCLUSIONS Independent of the applied definition, IOH was not associated with the occurrence of delirium after cardiac surgery.