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ImportanceCurrent fasting guidelines for procedures under anesthesia are poorly implemented, leading to negative metabolic sequelae. Recent studies in children showed support of liberal clear fluid intake; adult physiology can support clear fluid intake, but implementation studies are lacking.ObjectiveTo evaluate the successfulness of implementation of a liberal clear fluid policy with regard to fasting duration, well-being, and safety in adults scheduled for anesthesia.Design, Setting, and ParticipantsThis was a quality improvement study conducted from January 2016 to July 2021 at a tertiary referral hospital in the Netherlands. Adults scheduled for nonemergency procedures under anesthesia were included in the study. Patients undergoing obstetrics procedures or those who were intubated preoperatively were excluded.InterventionsStepwise introduction of a liberal fluid fasting policy, allowing for ingestion of clear fluids until arrival at the operating room.Main Outcomes and MeasuresThe primary outcome was change in fasting duration. Secondary outcomes were patient well-being, measured as preoperative thirst, amount of fluid ingested, postoperative nausea and vomiting (PONV), and administration of antiemetics. Safety was measured as incidence of regurgitation and aspiration (pneumonia).ResultsOf the 76 451 patients (mean [SD] age, 56 [17] years; 39 530 male individuals [52%] 36 921) included in the study, 59 036 (78%) followed the standard policy, and 16 815 (22%) followed the liberal policy. Time series analysis showed an estimated fasting duration decrease of 3:07 hours (IQR, 1:36-7:22; P P P P Conclusions and RelevanceResults of this quality improvement study suggest that a liberal fasting policy was associated with a clinically relevant reduction in fasting duration and improved patient well-being with regard to preoperative thirst and PONV. Although a slightly higher incidence of regurgitation could not be ruled out, wider implementation of such a policy may be advocated as results are still within the clinically accepted risks margins. Results suggest that surgical procedures in patients who drink clear fluids within 2 hours before anticipated anesthesia should not be postponed or canceled.

BACKGROUND Critical congenital heart disease (cCHD)—requiring cardiac intervention in the first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs—especially the brain—may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention. OBJECTIVE This study aimed to develop a clinical deterioration detection algorithm for PICU patients with cCHD. METHODS Retrospectively, synchronous per-second data of cerebral regional oxygen saturation (rSO2) and 4 vital parameters (respiratory rate, heart rate, oxygen saturation, and invasive mean blood pressure) in neonates with cCHD admitted to the University Medical Center Utrecht, the Netherlands, between 2002 and 2018 were extracted. Patients were stratified based on mean oxygen saturation during admission to account for physiological differences between acyanotic and cyanotic cCHD. Each subset was used to train our algorithm in classifying data as either stable, unstable, or sensor dysfunction. The algorithm was designed to detect combinations of parameters abnormal to the stratified subpopulation and significant deviations from the patient’s unique baseline, which were further analyzed to distinguish clinical improvement from deterioration. Novel data were used for testing, visualized in detail, and internally validated by pediatric intensivists. RESULTS A retrospective query yielded 4600 hours and 209 hours of per-second data in 78 and 10 neonates for, respectively, training and testing purposes. During testing, stable episodes occurred 153 times, of which 134 (88%) were correctly detected. Unstable episodes were correctly noted in 46 of 57 (81%) observed episodes. Twelve expert-confirmed unstable episodes were missed in testing. Time-percentual accuracy was 93% and 77% for, respectively, stable and unstable episodes. A total of 138 sensorial dysfunctions were detected, of which 130 (94%) were correct. CONCLUSIONS In this proof-of-concept study, a clinical deterioration detection algorithm was developed and retrospectively evaluated to classify clinical stability and instability, achieving reasonable performance considering the heterogeneous population of neonates with cCHD. Combined analysis of baseline (ie, patient-specific) deviations and simultaneous parameter-shifting (ie, population-specific) proofs would be promising with respect to enhancing applicability to heterogeneous critically ill pediatric populations. After prospective validation, the current—and comparable—models may, in the future, be used in the automated detection of clinical deterioration and eventually provide data-driven monitoring support to the medical team, allowing for timely intervention.

Background: Hospitalized pediatric oncology patients are at risk of severe clinical deterioration. Yet Pediatric Early Warning System (PEWS) scores have not been prospectively validated in these patients. We aimed to determine the predictive performance of the modified BedsidePEWS score for unplanned pediatric intensive care unit (PICU) admission and cardiopulmonary resuscitation (CPR) in this patient population.Methods: We performed a prospective cohort study in an 80-bed pediatric oncology hospital in the Netherlands, where care has been nationally centralized. All hospitalized pediatric oncology patients aged 0–18 years were eligible for inclusion. A Cox proportional hazard model was estimated to study the association between BedsidePEWS score and unplanned PICU admissions or CPR. The predictive performance of the model was internally validated by bootstrapping.Results: A total of 1137 patients were included. During the study, 103 patients experienced 127 unplanned PICU admissions and three CPRs. The hazard ratio for unplanned PICU admission or CPR was 1.65 (95% confidence interval [CI]: 1.59–1.72) for each point increase in the modified BedsidePEWS score. The discriminative ability was moderate (D-index close to 0 and a C-index of 0.83 [95% CI: 0.79–0.90]). Positive and negative predictive values of modified BedsidePEWS score at the widely used cutoff of 8, at which escalation of care is required, were 1.4% and 99.9%, respectively.Conclusion: The modified BedsidePEWS score is significantly associated with requirement of PICU transfer or CPR. In pediatric oncology patients, this PEWS score may aid in clinical decision-making for timing of PICU transfer.

Pediatric early warning systems (PEWS) arewidely used to identify clinically deteriorating patients. Hospitalized pediatric oncology patients are particularly prone to clinical deterioration. We assessed the PEWS performance to predict early clinical deterioration and the effect of PEWS implementation on patient outcomes in pediatric oncology patients. PubMED, EMBASE, and CINAHL databases were systematically searched from inception up to March 2020. Quality assessment was performed using the Prediction model study Risk-Of-Bias Assessment Tool (PROBAST) and the Cochrane Risk-of-Bias Tool. Nine studies were included. Due to heterogeneity of study designs, outcome measures, and diversity of PEWS, it was not possible to conduct a meta-analysis. Although the studies reported high sensitivity, specificity, and area under the receiver operating characteristics curve (AUROC) of PEWS detecting inpatient deterioration, overall risk of bias of the studies was high. This review highlights limited evidence on the predictive performance of PEWS for clinical deterioration and the effect of PEWS implementation.

Background Critical congenital heart disease (cCHD)—requiring cardiac intervention in the first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs—especially the brain—may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention. Objective This study aimed to develop a clinical deterioration detection algorithm for PICU patients with cCHD. Methods Retrospectively, synchronous per-second data of cerebral regional oxygen saturation (rSO2) and 4 vital parameters (respiratory rate, heart rate, oxygen saturation, and invasive mean blood pressure) in neonates with cCHD admitted to the University Medical Center Utrecht, the Netherlands, between 2002 and 2018 were extracted. Patients were stratified based on mean oxygen saturation during admission to account for physiological differences between acyanotic and cyanotic cCHD. Each subset was used to train our algorithm in classifying data as either stable, unstable, or sensor dysfunction. The algorithm was designed to detect combinations of parameters abnormal to the stratified subpopulation and significant deviations from the patient’s unique baseline, which were further analyzed to distinguish clinical improvement from deterioration. Novel data were used for testing, visualized in detail, and internally validated by pediatric intensivists. Results A retrospective query yielded 4600 hours and 209 hours of per-second data in 78 and 10 neonates for, respectively, training and testing purposes. During testing, stable episodes occurred 153 times, of which 134 (88%) were correctly detected. Unstable episodes were correctly noted in 46 of 57 (81%) observed episodes. Twelve expert-confirmed unstable episodes were missed in testing. Time-percentual accuracy was 93% and 77% for, respectively, stable and unstable episodes. A total of 138 sensorial dysfunctions were detected, of which 130 (94%) were correct. Conclusions In this proof-of-concept study, a clinical deterioration detection algorithm was developed and retrospectively evaluated to classify clinical stability and instability, achieving reasonable performance considering the heterogeneous population of neonates with cCHD. Combined analysis of baseline (ie, patient-specific) deviations and simultaneous parameter-shifting (ie, population-specific) proofs would be promising with respect to enhancing applicability to heterogeneous critically ill pediatric populations. After prospective validation, the current—and comparable—models may, in the future, be used in the automated detection of clinical deterioration and eventually provide data-driven monitoring support to the medical team, allowing for timely intervention.

Studies of intraoperative hypotension typically specify a blood pressure threshold associated with adverse outcomes. Such thresholds are likely to be study-biased, investigator-biased, or both. We hypothesised that a newly developed modelling method without a threshold, which is biologically more plausible than a threshold-based approach, would reveal a continuous association between exposure to intraoperative hypotension and adverse outcomes.Single-centre, retrospective cohort study of subjects ≥60 yr old undergoing noncardiac surgery. We modelled intraoperative hypotension using three different approaches: (1) unweighted, (2) weighted for degree of hypotension (depth), and (3) weighted for duration of hypotension. The primary outcome was myocardial injury, defined as elevated troponin I (60 ng LMyocardial injury occurred in 1812/15 452 (12%) procedures, with 554/15 452 (3.6%) procedures resulting in death before discharge from hospital. The unweighted lower blood pressure measure (OR: 0.26, 95% confidence interval [CI]: 0.12-0.53) and the depth-weighted measure (OR: 4.4, 95% CI: 2.6-7.4) were associated with myocardial injury. The duration-weighted measure was not associated with myocardial injury (OR: 0.89, 95% CI: 0.61-1.3). The unweighted measure (OR 0.08, 95% CI: 0.01-0.40) and the depth-weighted measure (OR: 12, 95% CI, 3.8-35) were associated with in-hospital mortality, but not the duration-weighted measure (OR: 1.3, 95% CI: 0.53-3.0).Intraoperative hypotension appears to have a graded association with postoperative myocardial injury and mortality, with depth appearing to contribute more than duration.

The intensive care unit (ICU) is one of the most technically advanced environments in healthcare, using a multitude of medical devices for drug administration, mechanical ventilation and patient monitoring. However, these technologies currently come with disadvantages, namely noise pollution, information overload and alarm fatigue—all caused by too many alarms. Individual medical devices currently generate alarms independently, without any coordination or prioritisation with other devices, leading to a cacophony where important alarms can be lost amongst trivial ones, occasionally with serious or even fatal consequences for patients. We have called this approach to the design of medical devices the single-device paradigm, and believe it is obsolete in modern hospitals where patients are typically connected to several devices simultaneously. Alarm rates of one alarm every four minutes for only the physiological monitors (as recorded in the ICUs of two hospitals contributing to this paper) degrades the quality of the patient’s healing environment and threatens patient safety by constantly distracting healthcare professionals. We outline a new approach to medical device design involving the application of human factors principles which have been successful in eliminating alarm fatigue in commercial aviation. Our approach comprises the networked-device paradigm, comprehensive alarms and humaniform information displays. Instead of each medical device alarming separately at the patient’s bedside, our proposed approach will integrate, prioritise and optimise alarms across all devices attached to each patient, display information more intuitively and hence increase alarm quality while reducing the number of alarms by an order of magnitude below current levels.

IntroductionHospitalised paediatric oncology patients are at risk to develop acute complications. Early identification of clinical deterioration enabling adequate escalation of care remains challenging. Various Paediatric Early Warning Systems (PEWSs) have been evaluated, also in paediatric oncology patients but mostly in retrospective or case–control study designs. This study protocol encompasses the first prospective cohort with the aim of evaluating the predictive performance of a modified Bedside PEWS score for non-elective paediatric intensive care unit (PICU) admission or cardiopulmonary resuscitation in hospitalised paediatric oncology patients.Methods and analysisA prospective cohort study will be conducted at the 80-bed Dutch paediatric oncology hospital, where all national paediatric oncology care has been centralised, directly connected to a shared 22-bed PICU. All patients between 1 February 2019 and 1 February 2021 admitted to the inpatient nursing wards, aged 0–18 years, with an International Classification of Diseases for Oncology (ICD-O) diagnosis of paediatric malignancy will be eligible. A Cox proportional hazard regression model will be used to estimate the association between the modified Bedside PEWS and time to non-elective PICU transfer or cardiopulmonary arrest. Predictive performance (discrimination and calibration) will be assessed internally using resampling validation. To account for multiple occurrences of the event of interest within each patient, the unit of study is a single uninterrupted ward admission (a clinical episode).Ethics and disseminationThe study protocol has been approved by the institutional ethical review board of our hospital (MEC protocol number 16-572/C). We adapted our enrolment procedure to General Data Protection Regulation compliance. Results will be disseminated at scientific conferences, regional educational sessions and publication in peer-reviewed journals.Trial registration numberNetherlands Trial Registry (NL8957).

The overwhelming amount, production speed, multidimensionality, and potential value of data currently available-often simplified and referred to as big data -exceed the limits of understanding of the human brain. At the same time, developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time. What is the role of the health care professional in collaboration with the data scientist in the changing landscape of modern care? We discuss how health care professionals should provide expert knowledge in each of the stages of clinical decision support design: data level, algorithm level, and decision support level. Including various ethical considerations, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values.

Rationale: Myocardial injury, as reflected by elevated cardiac troponin levels in plasma, is common in patients with community-acquired pneumonia (CAP), but its temporal dynamics and etiology remain unknown. Objectives: Our aim was to determine the incidence of troponin release in patients with CAP and identify risk factors that may point to underlying etiologic mechanisms. Methods: We included consecutive patients admitted with severe CAP to two intensive care units in the Netherlands between 2011 and 2015. High-sensitivity cardiac troponin I was measured daily during the first week. We used multivariable linear regression to identify variables associated with troponin release on admission, and we used mixed-effects regression to model the daily rise and fall of troponin levels over time. Results: Of 200 eligible patients, 179 were included, yielding 792 observation days. A total of 152 (85%) patients developed raised troponin levels greater than 26 ng/L. Baseline factors independently associated with troponin release included coronary artery disease (176% increase; 95% confidence interval [CI], 11–589), smoking (248% increase; 95% CI, 33–809), and higher Acute Physiology and Chronic Health Evaluation IV score (2% increase; 95% CI, 0.8–3.3), whereas Staphylococcus aureus as a causative pathogen was protective (70% reduction; 95% CI, 18–89). Time-dependent risk factors independently associated with daily increase in troponin concentrations included reduced platelet count (2.3% increase; 95% CI, 0.6–4), tachycardia (1.5% increase; 95% CI, 0.1–2.9), hypotension (6.2% increase; 95% CI, 2.1–10.6), dobutamine use (44% increase; 95% CI, 12–85), prothrombin time (8.2% increase; 95% CI, 0.2–16.9), white cell count (1.7% increase; 95% CI, 0–3.5), and fever (22.7% increase; 95% CI, 0.1–49.6). Conclusions: Cardiac injury develops in a majority of patients with severe CAP. Myocardial oxygen supply–demand mismatch and activated inflammation/coagulation are associated with this injury.

Background: Intraoperative hypotension is a common side effect of general anaesthesia and might lead to inadequate organ perfusion. It is unclear to what extent hypotension during noncardiac surgery is associated with unfavourable outcomes. Methods: We conducted a systematic search in PubMed, Embase, Web of Science, and CINAHL, and classified the quality of retrieved articles according to predefined adapted STROBE and CONSORT criteria. Reported strengths of associations from high-quality studies were classified into end-organ specific injury risks, such as acute kidney injury, myocardial injury, and stroke, and overall organ injury risks for various arterial blood pressure thresholds. Results: We present an overview of 42 articles on reported associations between various absolute and relative intraoperative hypotension definitions and their associations with postoperative adverse outcomes after noncardiac surgery. Elevated risks of end-organ injury were reported for prolonged exposure (≥10 min) to mean arterial pressures

UNSTRUCTURED The overwhelming amount, production speed, multidimensionality, and potential value of data currently available—often simplified and referred to as big data —exceed the limits of understanding of the human brain. At the same time, developments in data analytics and computational power provide the opportunity to obtain new insights and transfer data-provided added value to clinical practice in real time. What is the role of the health care professional in collaboration with the data scientist in the changing landscape of modern care? We discuss how health care professionals should provide expert knowledge in each of the stages of clinical decision support design: data level, algorithm level, and decision support level. Including various ethical considerations, we advocate for health care professionals to responsibly initiate and guide interprofessional teams, including patients, and embrace novel analytic technologies to translate big data into patient benefit driven by human(e) values.

Guidelines for postoperative pain treatment are based on patients' pain scores. Patients with an intermediate Numeric Rating Scale (NRS) score of 5 or 6 may consider their pain as either bearable or unbearable, which makes it difficult to decide on pain treatment because guidelines advise professionals to treat pain at NRS > 4. Educating patients in using an NRS score for pain might improve adequate pain treatment. A quasi-randomized controlled trial was conducted in which 194 preoperative patients watched the educational film and 183 the control film. Pain scores were considered discordant when patients reported an NRS ≤ 4 and wanted additional opioids or when patients reported an NRS > 4 and did not want additional opioids. Beliefs, fear, and knowledge of pain; pain assessment; and pain treatment were measured by questionnaires. No significant differences in discordant pain scores between the groups were found: relative risk (RR) 0.73, confidence interval (CI) 0.47-1.15 at rest and RR 0.96, CI 0.72-1.28 at movement. Patients in the intervention group had lower NRS pain scores than patients in the control group. In the intervention group, patients had significantly more knowledge and lower barriers to pain management compared with the control group. We did not find a statistically significant reduction in discordant pain scores when comparing the intervention group with the control group. However, patients in the intervention group had significantly lower pain scores, lower barriers, and more knowledge of pain treatment than patients in the control group.

BACKGROUND Cardiac surgery with cardiopulmonary bypass has a major impact on the congenital immune response, in which Toll-like receptors (TLRs) are the first line of defence. Decreased surface expression of TLRs and impaired monocyte responsiveness to TLR ligands occur following surgery. However, the clinical implications of this altered immune response are not clear. OBJECTIVES To study cardiac surgery induced changes in perioperative TLR expression and monocyte responsiveness, and the association with postoperative inflammatory complications. DESIGN A prospective cohort study. SETTING Single university hospital, enrolment March to December 2007. PATIENTS Eighty-four out of 92 patients who underwent coronary artery bypass grafting (CABG) were followed up until hospital discharge. MAIN OUTCOME MEASURES We assessed in-vivo TLR-2 and TLR-4 expression and ex-vivo monocyte responsiveness to TLR-2 and TLR-4 ligands, measured by Pam3Cys and lipopolysaccharide (LPS)-induced interleukin (IL)-6 and IL-8, and tumour necrosis factor alpha (TNF-α) secretion until 24 h after surgery. Patients were followed to identify adverse inflammatory and infectious outcomes. RESULTS Monocyte TLR expression decreased during CABG but returned to baseline after 24 h [linear mixed effects (LME) over time P

Background In a large cluster-randomized trial on the impact of a prediction model, presenting the calculated risk of postoperative nausea and vomiting (PONV) on-screen (assistive approach) increased the administration of risk-dependent PONV prophylaxis by anaesthetists. This change in therapeutic decision-making did not improve the patient outcome; that is, the incidence of PONV. The present study aimed to quantify the effects of adding a specific therapeutic recommendation to the predicted risk (directive approach) on PONV prophylaxis decision-making and the incidence of PONV. Methods A prospective before–after study was conducted in 1483 elective surgical inpatients. The before-period included care-as-usual and the after-period included the directive risk-based (intervention) strategy. Risk-dependent effects on the administered number of prophylactic antiemetics and incidence of PONV were analysed by mixed-effects regression analysis. Results During the intervention period anaesthetists administered 0.5 [95% confidence intervals (CIs): 0.4–0.6] more antiemetics for patients identified as being at greater risk of PONV. This directive approach led to a reduction in PONV [odds ratio (OR): 0.60, 95% CI: 0.43–0.83], with an even greater reduction in PONV in high-risk patients (OR: 0.45, 95% CI: 0.28–0.72). Conclusions Anaesthetists administered more prophylactic antiemetics when a directive approach was used for risk-tailored intervention compared with care-as-usual. In contrast to the previously studied assistive approach, the increase in PONV prophylaxis now resulted in a lower PONV incidence, particularly in high-risk patients. When one aims for a truly ‘PONV-free hospital)', a more liberal use of prophylactic antiemetics must be accepted and lower-risk thresholds should be set for the actionable recommendations.

BackgroundMyocardial injury, as reflected by elevated cardiac troponin levels in plasma, is common in patients with community-acquired pneumonia (CAP), but its temporal dynamics and etiology remain unknown. Our aim was to determine the incidence of troponin release in patients with CAP and identify risk factors which may point to underlying etiologic mechanisms.MethodsWe included consecutive patients admitted with severe CAP to two intensive care units in the Netherlands between 2011 and 2015. High-sensitivity cardiac troponin I was measured daily during the first week. We used multivariable linear regression to identify variables associated with troponin release on admission, and mixed-effects regression to model the daily rise and fall of troponin levels over time.ResultsAmong 200 eligible patients, 179 were included, yielding 792 observation days. A total of 152 (85%) patients developed raised troponin levels >26 ng/L. Baseline factors independently associated with troponin release included coronary artery disease (160% increase, 95% CI 7–529), smoking (304% increase, 95% CI 59-924), and higher APACHE IV score (2% increase, 95% CI 0.7-3.3), whereasStaphylococcus aureusas a causative pathogen was protective (67% reduction, 95% CI 9-88). Time-dependent risk factors independently associated with daily increase in troponin concentrations included reduced platelet count (1.7% increase, 95% CI 0.1-3.4), tachycardia (1.6% increase, 95% CI 0.3-3), hypotension (5.1% increase, 95% CI 1-9.4) and dobutamine use (38.4% increase 95% CI 8.8-76).ConclusionsCardiac injury develops in a majority of patients with severe CAP. Myocardial oxygen supply-demand mismatch and activated coagulation are potential causes of this injury.

BACKGROUND A large cohort study recently reported high pain scores after caesarean section (CS). The aim of this study was to analyse how pain after CS interferes with patients' activities and to identify possible causes of insufficient pain treatment. METHODS We analysed pain scores, pain-related interferences (with movement, deep breathing, mood and sleep), analgesic techniques, analgesic consumption, adverse effects and the wish to have received more analgesics during the first 24 h after surgery. To better evaluate the severity of impairment by pain, the results of CS patients were compared with those of patients undergoing hysterectomy. RESULTS CS patients (n = 811) were compared with patients undergoing abdominal, laparoscopic-assisted vaginal or vaginal hysterectomy (n = 2406, from 54 hospitals). Pain intensity, wish for more analgesics and most interference outcomes were significantly worse after CS compared with hysterectomies. CS patients with spinal or general anaesthesia and without patient-controlled analgesia (PCA) received significantly less opioids on the ward (62% without any opioid) compared with patients with PCA (p

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.

BACKGROUND:: For outcomes research where changes in intraoperative blood pressure are a possible causative factor, it is important to determine an appropriate source for a reference value. We studied to what extent preinduction blood pressure values in the operating room differ from those obtained during preoperative evaluation outside the operating room. METHODS:: Cohort study including 4408 patients aged 60 years or older undergoing noncardiac surgery. The outcome was the difference between the preinduction mean blood pressure (MBP) and the MBP obtained during preoperative evaluation. A difference of ≥10 mm Hg was considered clinically relevant. A paired samples t test was used to estimate the difference. Linear regression was used to obtain estimates adjusted for patient characteristics, comorbidity, medications, type of surgery, and preoperative blood pressure. RESULTS:: Complete data were available for 3660 (83%) patients. There were 2228 (61%) patients with a difference of ≥10 mm Hg between the preinduction and preoperative MBP. The overall mean difference between both MBPs was 11 mm Hg (95% confidence interval, 10–11) with important variability among individuals. Patients with higher preoperative MBP values had smaller differences. After adjusting for patient characteristics, comorbidity, medications, type of surgery, and preoperative blood pressure, the difference decreased an estimated 5.0 mm Hg (95% confidence interval, 4.7–5.4) for every increase of 10 mm Hg in preoperative MBP. Patient characteristics, comorbidity, type of surgery, or medication were not strongly associated with the difference. CONCLUSIONS:: The average preinduction blood pressure was higher than the preoperative blood pressure. This difference between the measurements can be explained by stress-induced effects and regression to the mean. To define an optimal reference value for research purposes or to arrive at a clinical perioperative blood pressure target, one should consider that there is important variability both within and between patients.

Background Little is known about the incidence of severe critical events in children undergoing general anaesthesia in Europe. We aimed to identify the incidence, nature, and outcome of severe critical events in children undergoing anaesthesia, and the associated potential risk factors. Methods The APRICOT study was a prospective observational multicentre cohort study of children from birth to 15 years of age undergoing elective or urgent anaesthesia for diagnostic or surgical procedures. Children were eligible for inclusion during a 2-week period determined prospectively by each centre. There were 261 participating centres across 33 European countries. The primary endpoint was the occurence of perioperative severe critical events requiring immediate intervention. A severe critical event was defined as the occurrence of respiratory, cardiac, allergic, or neurological complications requiring immediate intervention and that led (or could have led) to major disability or death. This study is registered with ClinicalTrials.gov, number NCT01878760. Findings Between April 1, 2014, and Jan 31, 2015, 31 127 anaesthetic procedures in 30 874 children with a mean age of 6·35 years (SD 4·50) were included. The incidence of perioperative severe critical events was 5·2% (95% CI 5·0–5·5) with an incidence of respiratory critical events of 3·1% (2·9–3·3). Cardiovascular instability occurred in 1·9% (1·7–2·1), with an immediate poor outcome in 5·4% (3·7–7·5) of these cases. The all-cause 30-day in-hospital mortality rate was 10 in 10 000. This was independent of type of anaesthesia. Age (relative risk 0·88, 95% CI 0·86–0·90; p

Aim The purpose of this study was to determine the incidence of reintubation due to upper airway obstruction in a homogeneous group of ventilated infants with Respiratory Syncytial Virus bronchiolitis. Our secondary objective was to determine whether prophylactic administration of dexamethasone prior to extubation was associated with decreased risk of reintubation. Methods This retrospective observational study in two Pediatric Intensive Care Units in 2 university hospitals in The Netherlands included two hundred patients younger than 13 months admitted with respiratory insufficiency caused by Respiratory Syncytial Virus bronchiolitis, requiring invasive mechanical ventilation. A logistic regression analysis with propensity score method was used to adjust for possible confounding. Results Reintubation due to post-extubation stridor occurred in 17 (8.5%) of 200 patients. After propensity score matching, administration of dexamethasone prior to extubation was associated with a significantly (p = 0.0011) decreased risk of reintubation due to post-extubation stridor compared to patients not receiving prophylactic dexamethasone (absolute risk reduction 13%, 95% CI 5.3–21%). Conclusion Reintubation due to post-extubation stridor is an important complication of ventilation for Respiratory Syncytial Virus bronchiolitis. Dexamethasone administered prior to extubation probably reduces the risk of post-extubation stridor necessitating reintubation in these infants. The results of this study support initiation of a placebo-controlled trial to confirm the beneficial effect of prophylactic dexamethasone.

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; P unadjusted=5.6 × 10(-7); P corrected=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.

Internal validity of a risk model can be studied efficiently with bootstrapping to assess possible optimism in model performance. Assumptions of the regular bootstrap are violated when the development data are clustered. We compared alternative resampling schemes in clustered data for the estimation of optimism in model performance. A simulation study was conducted to compare regular resampling on only the patient level with resampling on only the cluster level and with resampling sequentially on both the cluster and patient levels (2-step approach). Optimism for the concordance index and calibration slope was estimated. Resampling of only patients or only clusters showed accurate estimates of optimism in model performance. The 2-step approach overestimated the optimism in model performance. If the number of centers or intraclass correlation coefficient was high, resampling of clusters showed more accurate estimates than resampling of patients. The 3 bootstrap schemes also were applied to empirical data that were clustered. The results presented in this paper support the use of resampling on only the clusters for estimation of optimism in model performance when data are clustered. © 2013 © The Author 2013. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to understand. This article aims to provide the necessary insight for clinicians to assess the value of a prediction model that they intend to use in their clinical practice. RECENT FINDINGS: Recent developments in prediction model research include the continuous development of new performance characteristics for prediction models, increasing insight into the limitations of old characteristics, as well as an improved understanding of the generalizability of prediction models to new populations and practices. SUMMARY: Clinicians can assess the value of a prediction model for their practice by first identifying what the usage of the model will be. Second, they can recognize which performance characteristics are relevant to their assessment of the model. Finally, they need to decide whether the available scientific evidence sufficiently matches their clinical practice to proceed with implementation.

Aims and objectives. To measure the diagnostic value of the Numeric Rating Scale by comparing it to a Verbal Rating Scalein older patients.Background. Pain management in older patients is an important challenge because of their greater susceptibility to adverseeffects of analgesics. Nurses play an important role in applying guidelines for postoperative pain treatment. However, effec-tive pain management is dependent upon valid and reliable pain assessment.Design. Cross-sectional study.Methods. In total, 2674 older patients scored their postoperative pain on an 11-point numeric rating scale (NRS) and anadjective scale (VRS) including no pain, little pain, painful but bearable, considerable pain and terrible pain. The diagnosticvalue of different NRS cut-off values for administering analgesics is determined by an ROC curve.Results. Sensitivity of NRS > 3 for ‘unbearable’ pain in older patients was 72% with a specificity of 97 2%. With a cut-offpoint NRS > 4, sensitivity increased to 83%, while specificity was 96 7%. With a cut-off point NRS > 5, sensitivity was94%, while specificity was 85%. A high proportion (75%) of older old patients ( 75 years) with ‘painful but bearable’considers NRS 4, 5 and 6 to this VRS category.Conclusion. Using an NRS cut-off point > 3or> 4, a large group of older patients with ‘bearable’ pain would incorrectlyclassified as ‘unbearable’. When we make the assumption that bearable pain means no wish for additional analgesics, thismisclassification might result in overtreatment with analgesics, while 3% would be undertreated. With NRS cut-off point> 5, 6% have a risk of overtreatment and 15% of undertreatment.Relevance to clinical practice. Nurses should not rely solely on the NRS score in determining pain treatment; they need tocommunicate with older patients about their pain, the need for analgesics and eventual misconceptions about analgesics.Key words: analgesics, guideline, older old patients, older patients, pain measurement, postoperative pain

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.

Background Numeric pain scores have become important in clinical practice to assess postoperative pain and to help develop guidelines for treating pain. Professionals need the patients' pain scores to administer analgesic medication. However, do professionals interpret the pain scores in line with the actual perception of pain by the patients? Objective The study aim was to assess which Numerical Rating Scale (NRS) pain score was considered bearable on a Verbal Rating Scale (VRS) by patients and professionals. Methods This prospective study examined the relationship between the Numerical Rating Scale and a Verbal Rating Scale. The patients ( n =10,434) rated their pain the day after surgery on the 11-point NRS (0=no pain and 10=worst imaginable pain) and a VRS comprising five descriptors: " no pain "; " little pain "; " painful but bearable "; " considerable pain "; and " terrible pain ". The first three categories together (" no pain ", " little pain " and " painful but bearable ") were considered "bearable" and the last two categories (" considerable pain" and " terrible pain") were deemed as "unbearable" pain. The professionals ( n =303) were asked to relate the numbers of the NRS to the words of the VRS. Results Most patients considered NRS 4–6 as "bearable" pain. Among professionals, anesthesiologists, Post Anaesthesia Care nurses, and ward nurses interpreted NRS scores in the same way as the patients. Only the Acute Pain Nurses interpreted the scores differently; they considered NRS of 5 and higher to be not bearable. Conclusions Some care providers and patients differ in their interpretation of the postoperative NRS scores. A risk of overtreatment might arise when health care providers rigidly follow guidelines that prescribe strong analgesics for pain scores above 3 or 4 without probing the patient's preference for pharmacological treatment.

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. Clinical trial registration information: NCT00356746 (http://www.clinicaltrials.gov/ct2/show/NCT00356746?term=NCT00356746&rank=1).

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.

The N-methyl-d-aspartate receptor (NMDAR) coagonists glycine, d-serine and l-proline play crucial roles in NMDAR-dependent neurotransmission and are associated with a range of neuropsychiatric disorders. We conducted the first genome-wide association study of concentrations of these coagonists and their enantiomers in plasma and cerebrospinal fluid (CSF) of human subjects from the general population (N=414). Genetic variants at chromosome 22q11.2, located in and near PRODH (proline dehydrogenase), were associated with l-proline in plasma (β=0.29; P=6.38 × 10-10). The missense variant rs17279437 in the proline transporter SLC6A20 was associated with l-proline in CSF (β=0.28; P=9.68 × 10-9). Suggestive evidence of association was found for the d-serine plasma-CSF ratio at the d-amino-acid oxidase (DAO) gene (β=−0.28; P=9.08 × 10-8), whereas a variant in SRR (that encodes serine racemase and is associated with schizophrenia) constituted the most strongly associated locus for the l-serine to d-serine ratio in CSF. All these genes are highly expressed in rodent meninges and choroid plexus, anatomical regions relevant to CSF physiology. The enzymes and transporters they encode may be targeted to further construe the nature of NMDAR coagonist involvement in NMDAR gating. Furthermore, the highlighted genetic variants may be followed up in clinical populations, for example, schizophrenia and 22q11 deletion syndrome. Overall, this targeted metabolomics approach furthers the understanding of NMDAR coagonist concentration variability and sets the stage for non-targeted CSF metabolomics projects.Molecular Psychiatry advance online publication, 10 February 2015; doi:10.1038/mp.2014.190.

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

Background: Postoperative pain is commonly assessed through a Numerical Rating Scale (NRS), an 11-point scale where 0 indicates no pain and 10 indicates the worst imaginable pain. Guidelines advise the administration of analgesics at NRS pain scores above 3 or 4. In clinical practice, not all patients with pain scores above the treatment threshold are willing to accept additional analgesic treatment, especially when opioids are offered. The objective of this study is to measure the relation between patients’ NRS pain scores and their desire for additional opioids. Methods: This cross-sectional study examined 1,084 patients in an academic hospital the day after surgery between January 2010 and June 2010. The day after surgery, patients were asked to score their pain and desire for opioids. Sensitivity, specificity, positive predictive value, and negative predictive value of the desire for opioids and the different NRS thresholds were calculated. Results: Only when patients scored an 8 or higher on the NRS did the majority express a need for opioids. Many patients did not desire opioids, because they considered their pain tolerable, even at an NRS score above 4. Conclusions: With the current guidelines (i.e., using pain scores above 3 or 4 for prescribing opioids), many patients could be overtreated. Therefore, scores generated by the NRS should be interpreted individually.

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.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.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).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.