Dexamethasone and chronic postsurgical pain: the pendulum meets reductionistic thinking.

Reductionist thinking results in the bulk of anaesthesia trial designs being a single intervention to address what are in fact complex processes. The Perioperative Administration of Dexamethasone and Infection (PADDI) trial assessed the safety of a single preoperative dose of dexamethasone. Surprising to most, in the original report, a single dose of dexamethasone increased the incidence of the secondary outcome chronic postsurgical pain. Was this a chance finding or does dexamethasone increase chronic postsurgical pain? In an attempt to address this question, the PADDI investigators have now analysed this prespecified secondary outcome in two ways: as a substudy published earlier in this Journal, and as a retrospective analysis of the ENIGMA-II chronic pain database in this issue of the Journal. The PADDI investigators have now presented enough data to convince us that indeed a single dose of dexamethasone is safe and effective. However, the increase in chronic postsurgical pain seen in the original PADDI publication highlights the complexities, and the possible immunologic mechanisms, behind the genesis of chronic postsurgical pain. These publications from the PADDI group raise questions about other anti-inflammatory agents we use regularly for long-term postoperative pain management, and highlights the need for well-designed clinical trials to address this critically important patient-centred adverse functional outcome.

Postoperative troponin surveillance to detect myocardial infarction: an observational cohort modelling study.

BACKGROUND: Clinical presentation of postoperative myocardial infarction (POMI) is often silent. Several international guidelines recommend routine troponin surveillance in patients at risk. We compared how these different guidelines select patients for surveillance after noncardiac surgery with our established risk stratification model. METHODS: We used outcome data from two prospective studies: Measurement of Exercise Tolerance before Surgery (METS) and Troponin Elevation After Major non-cardiac Surgery (TEAMS). We compared the major American, Canadian, and European guideline recommendations for troponin surveillance with our established risk stratification model. For each guideline and model, we quantified the number of patients requiring monitoring, % POMI detected, sensitivity, specificity, diagnostic odds ratio, and number needed to screen (NNS). RESULTS: METS and TEAMS contributed 2350 patients, of whom 319 (14%) had myocardial injury, 61 (2.5%) developed POMI, and 14 (0.6%) died. Our risk stratification model selected fewer patients for troponin monitoring (20%), compared with the Canadian (78%) and European (79%) guidelines. The sensitivity to detect POMI was highest with the Canadian and European guidelines (0.85; 95% confidence interval [CI] 0.74-0.92). Specificity was highest using the American guidelines (0.91; 95% CI 0.90-0.92). Our risk stratification model had the best diagnostic odds ratio (2.5; 95% CI 1.4-4.2) and a lower NNS (21 vs 35) compared with the guidelines. CONCLUSIONS: Most postoperative myocardial infarctions were detected by the Canadian and European guidelines but at the cost of low specificity and a higher number of patients undergoing screening. Patient selection based on our risk stratification model was optimal.

Postoperative myocardial injury phenotypes and self-reported disability in patients undergoing noncardiac surgery: a multicentre observational study.

BACKGROUND: Postoperative myocardial injury (PMI) comprises a spectrum of mechanisms resulting in troponin release. The impact of different PMI phenotypes on postoperative disability remains unknown. METHODS: This was a multicentre prospective cohort study including patients aged ≥50 yr undergoing elective major noncardiac surgery. Patients were stratified in five groups based on the occurrence of PMI and clinical information on postoperative adverse events: PMI classified as myocardial infarction (MI; according to fourth definition), PMI plus adverse event other than MI, clinically silent PMI (PMI without adverse events), adverse events without PMI, and neither PMI nor an adverse event (reference). The primary endpoint was 6-month self-reported disability (assessed by WHO Disability Assessment Schedule 2.0 [WHODAS]). Disability-free survival was defined as WHODAS ≤16%. RESULTS: We included 888 patients of mean age 69 (range 53-91) yr, of which 356 (40%) were women; 151 (17%) patients experienced PMI, and 625 (71%) experienced 6-month disability-free survival. Patients with PMI, regardless of its phenotype, had higher preoperative disability scores than patients without PMI (difference in WHODAS; ß: 3.3, 95% confidence interval [CI]: 0.5-6.2), but scores remained stable after surgery (ß: 1.2, 95% CI: -3.2-5.6). Before surgery, patients with MI (n=36, 4%) were more disabled compared with patients without PMI and no adverse events (ß: 5.5, 95% CI: 0.3-10.8). At 6 months, patients with MI and patients without PMI but with adverse events worsened in disability score (ß: 11.2, 95% CI: 2.3-20.2; ß: 8.1, 95% CI: 3.0-13.2, respectively). Patients with clinically silent PMI did not change in disability score at 6 months (ß: 1.39, 95% CI: -4.50-7.29, P=0.642). CONCLUSIONS: Although patients with postoperative myocardial injury had higher preoperative self-reported disability, disability scores did not change at 6 months after surgery. However, patients experiencing myocardial infarction worsened in disability score after surgery.

Effect of a national guideline on postoperative troponin surveillance: a retrospective cohort study.

PURPOSE: We aimed to evaluate the effect of the 2017 Canadian Cardiovascular Society (CCS) guidelines on troponin surveillance after noncardiac surgery. METHODS: This was a single-centre, retrospective, observational study. Patients aged 40 yr or older undergoing intermediate- to high-risk elective noncardiac surgery between 2016 and 2021 were included. We compared the number and percentage of troponin tests ordered before and after the guidelines were published and compared patient characteristics, specifically cardiovascular comorbidity, using odds ratio's (OR) with 95% confidence intervals (CIs). Outcomes were myocardial injury, myocardial infarction (MI), and in-hospital mortality. RESULTS: The cohort included 36,386 patients and the median age was 63 yr. Between 2016 and 2018, troponin surveillance was done in 2,461 (13%) of the 19,046 patients, compared with 2,398 (14%) of the 17,340 patients who had surgery between 2019 and 2021 (OR, 1.08; 95% CI, 1.02 to 1.15). Patients who had surgery in the second period had less cardiovascular comorbidity; the adjusted OR for troponin surveillance was 1.14 (95% CI, 1.07 to 1.21). In the two periods, troponin was elevated in 561 (2.9%) and 470 (2.7%) patients, an MI was documented in 54 (0.3%) and 36 (0.2%) patients, and 95 (0.5%) and 73 (0.4%) patients died, respectively. After adjustment for baseline differences in the two periods, the ORs for MI and mortality were 0.83 (95% CI, 0.54 to 1.27) and 0.88 (95% CI, 0.64 to 1.19), respectively. CONCLUSION: Although the odds of troponin ordering were slightly but significantly higher after publication of the CCS guidelines, the odds for detecting an MI and for mortality did not change.

RéSUMé: OBJECTIF: Notre objectif était d'évaluer l'effet des lignes directrices 2017 de la Société canadienne de cardiologie (SCC) sur le monitorage de la troponine après une chirurgie non cardiaque. MéTHODE: Il s'agissait d'une étude observationnelle rétrospective monocentrique. Les patient·es âgé·es de 40 ans ou plus bénéficiant d'une chirurgie non cardiaque non urgente à risque intermédiaire à élevé entre 2016 et 2021 ont été inclus·es. Nous avons comparé le nombre et le pourcentage de tests de troponine prescrits avant et après la publication des lignes directrices et comparé les caractéristiques des patient·es, en particulier la comorbidité cardiovasculaire, en utilisant le rapport de cotes (RC) avec des intervalles de confiance (IC) à 95 %. Les critères d'évaluation comprenaient les lésions myocardiques, l'infarctus du myocarde (IM) et la mortalité hospitalière. RéSULTATS: La cohorte comprenait 36 386 personnes et l'âge médian était de 63 ans. Entre 2016 et 2018, le monitorage de la troponine a été réalisé chez 2461 (13 %) des 19 046 patient·es, contre 2398 (14 %) des 17 340 patient·es opéré·es entre 2019 et 2021 (RC, 1,08; IC 95%, 1,02 à 1,15). Les patient·es qui ont bénéficié d'une intervention chirurgicale au cours de la deuxième période présentaient moins de comorbidité cardiovasculaire; le RC ajusté pour le monitorage de la troponine était de 1,14 (IC 95 %, 1,07 à 1,21). Au cours des deux périodes, la troponine était élevée chez 561 (2,9 %) et 470 (2,7 %) patient·es, un IM a été documenté chez 54 (0,3 %) et 36 (0,2 %) patient·es, et 95 (0,5 %) et 73 (0,4 %) patient·es sont décédé·es, respectivement. Après ajustement pour tenir compte des différences initiales au cours des deux périodes, les RC pour l'IM et la mortalité étaient de 0,83 (IC 95 %, 0,54 à 1,27) et de 0,88 (IC 95 %, 0,64 à 1,19), respectivement. CONCLUSION: Bien que les probabilités de commande de troponine aient été légèrement mais significativement plus élevées après la publication des lignes directrices de la SCC, les probabilités de détection d'un IM et de mortalité n'ont pas changé.

Platform trials for anaesthesia and perioperative medicine: a narrative review.

Large randomised trials provide the most reliable evidence of effectiveness of new treatments in clinical practice. However, the time and resources required to complete such trials can be daunting. An overarching clinical trial platform focused on a single condition or type of surgery, aiming to compare several treatments, with an option to stop any or add in new treatment options, can provide greater efficiency. This has the potential to accelerate knowledge acquisition and identify effective, ineffective, or harmful treatments faster. The master protocol of the platform defines the study population(s) and standardised procedures. Ineffective or harmful treatments can be discarded or study drug dose modified during the life cycle of the trial. Other adaptive elements that can be modified include eligibility criteria, required sample size for any comparison(s), randomisation assignment ratio, and the addition of other promising treatment options. There are excellent opportunities for anaesthetists to establish platform trials in perioperative medicine. Platform trials are highly efficient, with the potential to provide quicker answers to important clinical questions that lead to improved patient care.

Postoperative mortality risk prediction that incorporates intraoperative vital signs: development and internal validation in a historical cohort.

PURPOSE: Accurate risk reassessment after surgery is crucial for postoperative planning for monitoring and disposition. Existing postoperative mortality risk prediction models using preoperative features do not incorporate intraoperative hemodynamic derangements that may alter risk stratification. Intraoperative vital signs may provide an objective and readily available prognostic resource. Our primary objective was to derive and internally validate a logistic regression (LR) model by adding intraoperative features to established preoperative predictors to predict 30-day postoperative mortality. METHODS: Following Research Ethics Board approval, we analyzed a historical cohort that included patients aged ≥ 45 undergoing noncardiac surgery with an overnight stay at two tertiary hospitals (2013 to 2017). Features included intraoperative vital signs (blood pressure, heart rate, end-tidal carbon dioxide partial pressure, oxygen saturation, and temperature) by threshold and duration of exposure, as well as patient, surgical, and anesthetic factors. The cohort was divided temporally 75:25 into derivation and validation sets. We constructed a multivariable LR model with 30-day all-cause mortality as the outcome and evaluated performance metrics. RESULTS: There were 30,619 patients in the cohort (mean [standard deviation] age, 66 [11] yr; 50.2% female; 2.0% mortality). In the validation set, the primary LR model showed a c-statistic of 0.893 (99% confidence interval [CI], 0.853 to 0.927), a Nagelkerke R-squared of 0.269, a scaled Brier score of 0.082, and an area under precision-recall curve of 0.158 (baseline 0.017 for an uninformative model). The addition of intraoperative vital signs to preoperative factors minimally improved discrimination and calibration. CONCLUSION: We derived and internally validated a model that incorporated vital signs to improve risk stratification after surgery. Preoperative factors were strongly predictive of mortality risk, and intraoperative predictors only minimally improved discrimination. External and prospective validations are needed. STUDY REGISTRATION: www. CLINICALTRIALS: gov (NCT04014010); registered on 10 July 2019.

RéSUMé: OBJECTIF: Une réévaluation précise des risques après la chirurgie est cruciale pour la planification postopératoire du monitorage et du congé. Les modèles existants de prédiction du risque de mortalité postopératoire utilisant des caractéristiques préopératoires n'intègrent pas les perturbations hémodynamiques peropératoires, lesquelles pourraient modifier la stratification du risque. Les signes vitaux peropératoires peuvent fournir une ressource pronostique objective et facilement disponible. Notre objectif principal était de dériver et de valider en interne un modèle de régression logistique (RL) en ajoutant des caractéristiques peropératoires aux prédicteurs préopératoires établis pour prédire la mortalité postopératoire à 30 jours. MéTHODE: À la suite de l'approbation du Comité d'éthique de la recherche, nous avons analysé une cohorte historique qui comprenait des patients âgés de ≥ 45 ans bénéficiant d'une chirurgie non cardiaque avec un séjour d'une nuit dans deux hôpitaux tertiaires (2013 à 2017). Les caractéristiques comprenaient les signes vitaux peropératoires (tension artérielle, fréquence cardiaque, pression télé-expiratoire en CO2, saturation en oxygène et température) par seuil et durée d'exposition, ainsi que des facteurs propres au patient, chirurgicaux et anesthésiques. La cohorte a été divisée temporellement 75:25 en ensembles de dérivation et de validation. Nous avons élaboré un modèle de RL multivariée avec la mortalité toutes causes confondues à 30 jours comme critère, et évalué les mesures de performance. RéSULTATS: Il y avait 30 619 patients dans la cohorte (âge moyen [écart type], 66 [11] ans; 50,2 % de femmes; 2,0 % de mortalité). Dans l'ensemble de validation, le modèle de RL primaire a montré une statistique c de 0,893 (intervalle de confiance [IC] à 99 %, 0,853 à 0,927), un R carré de Nagelkerke de 0,269, un score de Brier mis à l'échelle de 0,082 et une aire sous la courbe de rappel et précision de 0,158 (ligne de base 0,017 pour un modèle non informatif). L'ajout de signes vitaux peropératoires aux facteurs préopératoires a amélioré de façon minimale la discrimination et l'étalonnage. CONCLUSION: Nous avons dérivé et validé en interne un modèle qui incorporait des signes vitaux pour améliorer la stratification des risques après la chirurgie. Les facteurs préopératoires étaient fortement prédictifs du risque de mortalité, et les prédicteurs peropératoires n'ont que que très peu amélioré la discrimination. Une validation externe et prospective est nécessaire. ENREGISTREMENT DE L'éTUDE: www.ClinicalTrials.gov (NCT04014010); enregistrée le 10 juillet 2019.

Systematic review and consensus definitions for the Standardized Endpoints in Perioperative Medicine (StEP) initiative: cardiovascular outcomes.

BACKGROUND: Adverse cardiovascular events are a leading cause of perioperative morbidity and mortality. The definitions of perioperative cardiovascular adverse events are heterogeneous. As part of the international Standardized Endpoints in Perioperative Medicine initiative, this study aimed to find consensus amongst clinical trialists on a set of standardised and valid cardiovascular outcomes for use in future perioperative clinical trials. METHODS: We identified currently used perioperative cardiovascular outcomes by a systematic review of the anaesthesia and perioperative medicine literature (PubMed/Ovid, Embase, and Cochrane Library). We performed a three-stage Delphi consensus-gaining process that involved 55 clinician researchers worldwide. Cardiovascular outcomes were first shortlisted and the most suitable definitions determined. These cardiovascular outcomes were then assessed for validity, reliability, feasibility, and clarity. RESULTS: We identified 18 cardiovascular outcomes. Participation in the three Delphi rounds was 100% (n=19), 71% (n=55), and 89% (n=17), respectively. A final list of nine cardiovascular outcomes was elicited from the consensus: myocardial infarction, myocardial injury, cardiovascular death, non-fatal cardiac arrest, coronary revascularisation, major adverse cardiac events, pulmonary embolism, deep vein thrombosis, and atrial fibrillation. These nine cardiovascular outcomes were rated by the majority of experts as valid, reliable, feasible, and clearly defined. CONCLUSIONS: These nine consensus cardiovascular outcomes can be confidently used as endpoints in clinical trials designed to evaluate perioperative interventions with the goal of improving perioperative outcomes.

Risk Factors for Failure to Rescue in Myocardial Infarction after Noncardiac Surgery: A Cohort Study.

BACKGROUND: Compared to other perioperative complications, failure to rescue (i.e., death after suffering a complication) is highest after perioperative myocardial infarction (a myocardial infarction that occurs intraoperatively or within 30 days after surgery). The purpose of this study was to identify patient and surgical risk factors for failure to rescue in patients who have had a perioperative myocardial infarction. METHODS: Individuals who experienced a perioperative myocardial infarction after noncardiac surgery between 2012 and 2016 were identified from the American College of Surgeons (Chicago, Illinois) National Surgical Quality Improvement Program database. Multivariable logistic regression was used to identify risk factors for failure to rescue. Subgroup and sensitivity analyses evaluated the robustness of primary findings. RESULTS: The authors identified 1,307,884 individuals who had intermediate to high-risk noncardiac surgery. A total of 8,923 (0.68%) individuals had a perioperative myocardial infarction, of which 1,726 (19.3%) experienced failure to rescue. Strongest associations (adjusted odds ratio greater than 1.5) were age 85 yr or older (2.52 [95% CI, 2.05 to 3.09] vs. age younger than 65 yr), underweight body mass index (1.53 [95% CI, 1.17 to 2.01] vs. normal body mass index), American Society of Anesthesiologists class IV (1.76 [95% CI, 1.33 to 2.31] vs. class I or II) and class V (3.48 [95% CI, 2.20 to 5.48] vs. class I or II), and presence of: ascites (1.81 [95% CI, 1.15 to 2.87]), disseminated cancer (1.54 [95% CI, 1.18 to 2.00]), systemic inflammatory response syndrome (1.55 [95% CI, 1.26 to 1.90]), sepsis (1.75 [95% CI, 1.39 to 2.20]), septic shock (1.79 [95% CI, 1.34 to 2.37]), and dyspnea at rest (1.94 [95% CI, 1.32 to 2.86]). Patients who had emergency surgery, high-risk procedures, and postoperative complications were at higher risk of failure to rescue. CONCLUSIONS: Routinely identified patient and surgical factors predict risk of failure to rescue after perioperative myocardial infarction.

Integration of the Duke Activity Status Index into preoperative risk evaluation: a multicentre prospective cohort study.

BACKGROUND: The Duke Activity Status Index (DASI) questionnaire might help incorporate self-reported functional capacity into preoperative risk assessment. Nonetheless, prognostically important thresholds in DASI scores remain unclear. We conducted a nested cohort analysis of the Measurement of Exercise Tolerance before Surgery (METS) study to characterise the association of preoperative DASI scores with postoperative death or complications. METHODS: The analysis included 1546 participants (≥40 yr of age) at an elevated cardiac risk who had inpatient noncardiac surgery. The primary outcome was 30-day death or myocardial injury. The secondary outcomes were 30-day death or myocardial infarction, in-hospital moderate-to-severe complications, and 1 yr death or new disability. Multivariable logistic regression modelling was used to characterise the adjusted association of preoperative DASI scores with outcomes. RESULTS: The DASI score had non-linear associations with outcomes. Self-reported functional capacity better than a DASI score of 34 was associated with reduced odds of 30-day death or myocardial injury (odds ratio: 0.97 per 1 point increase above 34; 95% confidence interval [CI]: 0.96-0.99) and 1 yr death or new disability (odds ratio: 0.96 per 1 point increase above 34; 95% CI: 0.92-0.99). Self-reported functional capacity worse than a DASI score of 34 was associated with increased odds of 30-day death or myocardial infarction (odds ratio: 1.05 per 1 point decrease below 34; 95% CI: 1.00-1.09), and moderate-to-severe complications (odds ratio: 1.03 per 1 point decrease below 34; 95% CI: 1.01-1.05). CONCLUSIONS: A DASI score of 34 represents a threshold for identifying patients at risk for myocardial injury, myocardial infarction, moderate-to-severe complications, and new disability.

Chronotropic incompetence and myocardial injury after noncardiac surgery: planned secondary analysis of a prospective observational international cohort study.

BACKGROUND: Physiological measures of heart failure are common in surgical patients, despite the absence of a diagnosis. Heart rate (HR) increases during exercise are frequently blunted in heart failure (termed chronotropic incompetence), which primarily reflects beta-adrenoreceptor dysfunction. We examined whether chronotropic incompetence was associated with myocardial injury after noncardiac surgery. METHODS: This was a predefined analysis of an international cohort study where participants aged ≥40 yr underwent symptom-limited cardiopulmonary exercise testing before noncardiac surgery. Chronotropic incompetence was defined as the ratio of increase in HR during exercise to age-predicted maximal increase in HR <0.6. The primary outcome was myocardial injury within 3 days after surgery, defined by high-sensitivity troponin assays >99th centile. Explanatory variables were biomarkers for heart failure (ventilatory efficiency slope [minute ventilation/carbon dioxide production] ≥34; peak oxygen consumption ≤14 ml kg-1 min-1; HR recovery ≤6 beats min-1 decrease 1 min post-exercise; preoperative N-terminal pro-B-type natriuretic peptide [NT pro-BNP] >300 pg ml-1). Myocardial injury was compared in the presence or absence of sympathetic (i.e. chronotropic incompetence) or parasympathetic (i.e. impaired HR recovery after exercise) thresholds indicative of dysfunction. Data are presented as odds ratios (ORs) (95% confidence intervals). RESULTS: Chronotropic incompetence occurred in 396/1325 (29.9%) participants; only 16/1325 (1.2%) had a heart failure diagnosis. Myocardial injury was sustained by 162/1325 (12.2%) patients. Raised preoperative NT pro-BNP was more common when chronotropic incompetence was <0.6 (OR: 1.57 [1.11-2.23]; P=0.011). Chronotropic incompetence was not significantly associated with myocardial injury (OR: 1.05 [0.74-1.50]; P=0.78), independent of rate-limiting therapy. HR recovery <12 beats min-1 decrease after exercise was associated with myocardial injury in the presence (OR: 1.62 [1.05-2.51]; P=0.03) or absence (OR: 1.60 [1.06-2.39]; P=0.02) of chronotropic incompetence. CONCLUSIONS: Chronotropic incompetence is common in surgical patients. In contrast to parasympathetic dysfunction which was associated with myocardial injury, preoperative chronotropic incompetence (suggestive of sympathetic dysfunction) was not associated with postoperative myocardial injury.