Association of preoperative glucose concentration with myocardial injury and death after non-cardiac surgery (GlucoVISION): a prospective cohort study

Association between stress hyperglycemia ratio and postoperative major adverse cardiovascular and cerebrovascular events in noncardiac surgeries: a large perioperative cohort study

BACKGROUND

There has been a concerning rise in the incidence of major adverse cardiovascular and cerebrovascular events (MACCE) following noncardiac surgeries (NCS), significantly impacting surgical outcomes and patient prognosis. Glucose metabolism abnormalities induced by stress response under acute medical conditions may be a risk factor for postoperative MACCE. This study aims to explore the association between stress hyperglycemia ratio (SHR) and postoperative MACCE in patients undergoing general anesthesia for NCS.

METHODS

There were 12,899 patients in this perioperative cohort study. The primary outcome was MACCE within 30 days postoperatively, defined as angina, acute myocardial infarction, cardiac arrest, arrhythmia, heart failure, stroke, or in-hospital all-cause mortality. Kaplan-Meier curves visualized the cumulative incidence of MACCE. Cox proportional hazard models were utilized to assess the association between the risk of MACCE and different SHR groups. Restricted cubic spline analyses were conducted to explore potential nonlinear relationships. Additionally, exploratory subgroup analyses and sensitivity analyses were performed.

RESULTS

A total of 592 (4.59%) participants experienced MACCE within 30 days after surgery, and 1,045 (8.10%) within 90 days. After adjusting for confounding factors, compared to the SHR T2 group, the risk of MACCE within 30 days after surgery increased by 1.34 times (95% CI 1.08-1.66) in the T3 group and by 1.35 times (95% CI 1.08-1.68) in the T1 group respectively. In the non-diabetes group, the risk of MACCE within 30 days after surgery increased by 1.60 times (95% CI 1.21-2.12) in the T3 group and by 1.61 times (95% CI 1.21-2.14) in the T1 group respectively, while no statistically significant increase in risk was observed in the diabetes group. Similar results were observed within 90 days after surgery in the non-diabetes group. Additionally, a statistically significant U-shaped nonlinear relationship was observed in the non-diabetes group (30 days: P for nonlinear = 0.010; 90 days: P for nonlinear = 0.008).

CONCLUSION

In this large perioperative cohort study, we observed that both higher and lower SHR were associated with an increased risk of MACCE within 30 and 90 days after NCS, especially in patients without diabetes. These findings suggest that SHR potentially plays a key role in stratifying cardiovascular and cerebrovascular risk after NCS.

Development and Validation of an Explainable Machine Learning Model for Predicting Myocardial Injury After Noncardiac Surgery in Two Centers in China: Retrospective Study

Background

Myocardial injury after noncardiac surgery (MINS) is an easily overlooked complication but closely related to postoperative cardiovascular adverse outcomes; therefore, the early diagnosis and prediction are particularly important.

Objective

We aimed to develop and validate an explainable machine learning (ML) model for predicting MINS among older patients undergoing noncardiac surgery.

Methods

The retrospective cohort study included older patients who had noncardiac surgery from 1 northern center and 1 southern center in China. The data sets from center 1 were divided into a training set and an internal validation set. The data set from center 2 was used as an external validation set. Before modeling, the least absolute shrinkage and selection operator and recursive feature elimination methods were used to reduce dimensions of data and select key features from all variables. Prediction models were developed based on the extracted features using several ML algorithms, including category boosting, random forest, logistic regression, naïve Bayes, light gradient boosting machine, extreme gradient boosting, support vector machine, and decision tree. Prediction performance was assessed by the area under the receiver operating characteristic (AUROC) curve as the main evaluation metric to select the best algorithms. The model performance was verified by internal and external validation data sets with the best algorithm and compared to the Revised Cardiac Risk Index. The Shapley Additive Explanations (SHAP) method was applied to calculate values for each feature, representing the contribution to the predicted risk of complication, and generate personalized explanations.

Results

A total of 19,463 eligible patients were included; among those, 12,464 patients in center 1 were included as the training set; 4754 patients in center 1 were included as the internal validation set; and 2245 in center 2 were included as the external validation set. The best-performing model for prediction was the CatBoost algorithm, achieving the highest AUROC of 0.805 (95% CI 0.778-0.831) in the training set, validating with an AUROC of 0.780 in the internal validation set and 0.70 in external validation set. Additionally, CatBoost demonstrated superior performance compared to the Revised Cardiac Risk Index (AUROC 0.636; P<.001). The SHAP values indicated the ranking of the level of importance of each variable, with preoperative serum creatinine concentration, red blood cell distribution width, and age accounting for the top three. The results from the SHAP method can predict events with positive values or nonevents with negative values, providing an explicit explanation of individualized risk predictions.

Conclusions

The ML models can provide a personalized and fairly accurate risk prediction of MINS, and the explainable perspective can help identify potentially modifiable sources of risk at the patient level.

Association between blood groups and myocardial injury after non-cardiac surgery: a retrospective cohort study

Blood group is a potential genetic element in coronary artery disease. Nevertheless, the relationship between different ABO blood groups and myocardial injury after non-cardiac surgery (MINS) is poorly understood. This study verified whether ABO blood group is a potential MINS influencing factor. This retrospective cohort study included 1201 patients who underwent elective non-cardiac surgery and a mandatory troponin test on postoperative days 1 and 2 from 2019 to 2020 at a university-affiliated tertiary hospital. The primary outcome was associations between ABO blood groups and MINS, assessed using univariate and multivariate logistic-regression analyses. Path analysis was used to investigate direct and indirect effects between blood group and MINS. MINS incidence (102/1201, 8.5%) was higher in blood-type B patients than in non-B patients [blood-type B: 44/400 (11.0%) vs. non-B: 58/801 (7.2%); adjusted odds ratio = 1.57 (1.03-2.38); p = 0.036]. In the confounding factor model, preoperative hypertension and coronary artery disease medical history were associated with MINS risk [adjusted odds ratio: 2.00 (1.30-3.06), p = 0.002; 2.81 (1.71-4.61), p < 0.001, respectively]. Path analysis did not uncover any mediating role for hypertension, diabetes, or coronary artery disease between blood type and MINS. Therefore, blood-type B is associated with higher MINS risk; potential mediators of this association need to be investigated.

Preoperative fasting glucose value can predict acute kidney injury in non-cardiac surgical patients without diabetes but not in patients with diabetes

BACKGROUND

Postoperative acute kidney injury (AKI) is a common and costly complication after non-cardiac surgery. Patients with or without diabetes could develop hyperglycemia before surgery, and preoperative hyperglycemia was closely associated with postoperative poor outcomes, but the association between preoperative fasting blood glucose level and postoperative AKI is still unclear.

METHODS

Data from patients undergoing non-cardiac surgery in Chongqing University Cancer Hospital from January 1, 2017, to May 31, 2023, were collected, preoperative glucose value and perioperative variables were extracted, the primary exposure of interest was preoperative glucose value, and the outcome was postoperative AKI.

RESULTS

Data from 39,986 patients were included in the final analysis, 741(1.9%) patients developed AKI, 134(5.6%) in the cohort with DM, and 607(1.6%) in the cohort without DM(OR 1.312, 95% CI 1.028-1.675, P = 0.029). A significant non-linear association between preoperative glucose and AKI exists in the cohort without DM after covariable adjustment (P = 0.000), and every 1 mmol/L increment of preoperative glucose level increased OR by 15% (adjusted OR 1.150, 95% CI 1.078-1.227, P = 0.000), the optimal cut-point of preoperative fasting glucose level to predict AKI was 5.39 mmol/L (adjusted OR 1.802, 95%CI 1.513-2.146, P = 0.000). However, in the cohort with DM, the relation between preoperative glucose and postoperative AKI was not significant after adjusting by covariables (P = 0.437). No significance exists between both cohorts in the risk of AKI over the range of preoperative glucose values.

CONCLUSION

A preoperative fasting glucose value of 5.39 mmol/L can predict postoperative acute kidney injury after non-cardiac surgery in patients without diagnosed diabetes, but it is not related to AKI in patients with the diagnosis.

Ward monitoring 4.0: real-time metabolic insights from continuous glucose monitoring into perioperative organ dysfunction

The now-routine clinical deployment of continuous glucose monitoring has demonstrated benefit in real-world settings. We make the case that continuous glucose monitoring can help re-examine, at scale, the role that (stress) hyperglycaemia plays in fuelling organ dysfunction after tissue trauma. Provided robust perioperative data do emerge, well-established continuous glucose monitoring technology could soon help transform the perioperative landscape.

Role of Preoperative Oral Rehydration Solution on Myocardial Ischaemia During Orthopaedic Surgery under Spinal Anaesthesia: A Prospective Randomised Study

Objective

Preoperative oral rehydration solution (ORS) supplementation offers wide postoperative benefits, but its role in reducing post-spinal myocardial ischaemia is uncertain. We evaluated this aspect in elective lower limb orthopaedic surgeries and compared it to conventional preoperative fasting.

Methods

Prospectively, we randomised 126 patients aged >60 years into two groups: (A) received reconstituted ORS (1000 mL) during the overnight preoperative fasting, continued up to 2 hrs prior to spinal anaesthesia (SA) induction; (B) kept on conventional overnight preoperative fasting. This study evaluated electrocardiographic ischaemic changes at 2, 5, 10, 15, and 30 minutes after SA induction.

Results

In total, 27 patients (group A: 7; group B: 20) developed transient electrocardiographic ischaemic changes. On intergroup comparison, group B had a significantly higher incidence at all time points, with highest statistical levels at 5- and 10-minutes ((P < 0.001). The receiver operating characteristic curve at a threshold fasting duration (fluids) of >3 hours, had an area-under-curve of 0.74 to predict such changes within 30 minutes of SA induction (sensitivity 96.30%, specificity 55.56%, accuracy 64.29%, odds ratio 32.50, relative risk 20.80, (P < 0.001). Post-spinal hemodynamic changes were higher in group B than in A; hypotension and tachycardia were statistically significant ((P=0.020). The pleth variability index was significantly higher ((P < 0.001), while perfusion index was significantly lower (P < 0.001) in group B at all time points.

Conclusion

Preoperative ORS supplementation significantly reduced post-spinal transient ischaemic electrocardiographic changes in elderly patients than conventional overnight fasting.

Nomogram for Predicting Intraoperative Hemodynamic Instability in Patients With Normotensive Pheochromocytoma

CONTEXT

Intraoperative hemodynamic instability (HI) deteriorates surgical outcomes of patients with normotensive pheochromocytoma (NP).

OBJECTIVE

To characterize the hemodynamics of NP and develop and externally validate a prediction model for intraoperative HI.

METHODS

Data on 117 patients with NP (derivation cohort) and 40 patients with normotensive adrenal myelolipoma (NAM) who underwent laparoscopic adrenalectomy from January 2011 to November 2021 were retrospectively collected. Data on 22 patients with NP (independent validation cohort) were collected from another hospital during the same period. The hemodynamic characteristics of patients with NP and NAM were compared. Machine learning models were used to identify risk factors associated with HI. The final model was visualized via a nomogram.

RESULTS

Forty-eight (41%) out of 117 patients experienced HI, which was significantly more than that for NAM. A multivariate logistic regression including age, tumor size, fasting plasma glucose, and preoperative systolic blood pressure showed good discrimination measured by area under curve (0.8286; 95% CI 0.6875-0.9696 and 0.7667; 95% CI 0.5386-0.9947) for predicting HI in internal and independent validation cohorts, respectively. The sensitivities and positive predictive values were 0.6667 and 0.7692 for the internal and 0.9167 and 0.6111 for the independent validations, respectively. The final model was visualized via a nomogram and yielded net benefits across a wide range of risk thresholds in decision curve analysis.

CONCLUSION

Patients with NP experienced HI during laparoscopic adrenalectomy. The nomogram can be used for individualized prediction of intraoperative HI in patients with NP.

Perioperative strategies to reduce risk of myocardial injury after non-cardiac surgery (MINS): A narrative review

Myocardial injury is a frequent complication of surgical patients after having non-cardiac surgery that is strongly associated with perioperative mortality. While intraoperative anesthesia-related deaths are exceedingly rare, about 1% of patients undergoing non-cardiac surgery die within the first 30 postoperative days. Given the number of surgeries performed annually, death following surgery is the second leading cause of death in the United States. Myocardial injury after non-cardiac surgery (MINS) is defined as an elevation in troponin concentrations within 30 days postoperatively. Although typically asymptomatic, patients with MINS suffer myocardial damage and have a 10% risk of death within 30 days after surgery and excess risks of mortality that persist during the first postoperative year. Many factors for the development of MINS are non-modifiable, such as preexistent coronary artery disease. Preventive measures, systematic approaches to surveillance and treatment standards are still lacking, however many factors are modifiable and should be considered in clinical practice: the importance of hemodynamic control, adequate oxygen supply, metabolic homeostasis, the use of perioperative medications such as statins, anti-thrombotic agents, beta-blockers, or anti-inflammatory agents, as well as some evidence regarding the choice of sedative and analgesic for anesthesia are discussed. Also, as age and complexity in comorbidities of the surgical patient population increase, there is an urgent need to identify patients at risk for MINS and develop prevention and treatment strategies. In this review, we provide an overview of current screening standards and promising preventive options in the perioperative setting and address knowledge gaps requiring further investigation.

Strategies for intraoperative glucose management: a scoping review

PURPOSE

Perioperative hyperglycemia is associated with adverse outcomes for patients with and without diabetes. Guidelines and published protocols for intraoperative glycemic management have substantial variation in their recommendations. We sought to characterize the current evidence-guiding intraoperative glycemic management in a scoping review.

SOURCES

Our search strategy included MEDLINE (Ovid and EBSCO), PubMed, PubMed Central, EMBASE, CINAHL, Cochrane Library, SciVerse Scopus, and Web of Science and a gray literature search of Google, Google Scholar, hand searching of the reference lists of included articles, OAISter, institutional protocols, and ClinicalTrails.gov.

PRINCIPAL FINDINGS

We identified 41 articles that met our inclusion criteria, 24 of which were original research studies. Outcomes and exposures were defined heterogeneously across studies, which limited comparison and synthesis. Investigators often created arbitrary and differing categories of glucose values rather than analyzing glucose as a continuous variable, which limited our ability to combine results from different studies. In addition, the study populations and surgery types also varied considerably, with few studies performed during day surgeries and specific surgical disciplines. Study populations often included more than one type of surgery, indication, and urgency that were expected to have varying physiologic and inflammatory responses. Combining low- and high-risk patients in the same study population may obscure the harms or benefits of intraoperative glycemic management for high-risk procedures or patients.

CONCLUSION

Future studies examining intraoperative glycemic management should carefully consider the study population, surgical characteristics, and pre- and postoperative management of hyperglycemia.

Cardioprotective Effects of Glucose-Insulin-Potassium Infusion in Patients Undergoing Cardiac Surgery: A Systematic Review and Meta-Analysis

The infusion of glucose-insulin-potassium (GIK) has yielded conflicting results in terms of cardioprotective effects. We conducted a meta-analysis to examine the impact of perioperative GIK infusion in early outcome after cardiac surgery. Randomized controlled trials (RCTs) were eligible if they examined the efficacy of GIK infusion in adults undergoing cardiac surgery. The main study endpoint was postoperative myocardial infarction (MI) and secondary outcomes were hemodynamics, any complications and hospital resources utilization. Subgroup analyses explored the impact of the type of surgery, GIK composition and timing of administration. Odds ratio (OR) or mean difference (MD) with 95% confidence interval (CI) were calculated with a random-effects model. Fifty-three studies (n=6129) met the inclusion criteria. Perioperative GIK infusion was effective in reducing MI (k=32 OR 0.66[0.48, 0.89] P=0.0069), acute kidney injury (k=7 OR 0.57[0.4, 0.82] P=0.0023) and hospital length of stay (k=19 MD -0.89[-1.63, -0.16] days P=0.0175). Postoperatively, the GIK-treated group presented higher cardiac index (k=14 MD 0.43[0.29, 0.57] L/min P<0.0001) and lesser hyperglycemia (k=20 MD -30[-47, -13] mg/dL P=0.0005) than in the usual care group. The GIK-associated protection for MI was effective when insulin infusion rate exceeded 2 mUI/kg/min and after coronary artery bypass surgery. Certainty of evidence was low given imprecision of the effect estimate, heterogeneity in outcome definition and risk of bias. Perioperative GIK infusion is associated with improved early outcome and reduced hospital resource utilization after cardiac surgery. Supporting evidence is heterogenous and further research is needed to standardize the optimal timing and composition of GIK solutions.

Preoperative Insulin Intensification to Improve Day of Surgery Blood Glucose Control

Background

Guidelines offer varying recommendations for preoperative long-acting basal insulin dosing, despite mounting evidence of the advantages of maintaining perioperative glucose levels between 80 and 180 mg/dL.

Observations

We iteratively adjusted health care practitioner (HCP) instructions to intensify insulin dosing on the evening before surgery for 195 consecutive patients with diabetes mellitus treated with long-acting basal insulin with an evening dosage. Baseline data was collected in phase 1. In phase 2, the preoperative insulin dose on the evening before surgery was increased for patients with hemoglobin A_1c (HbA_1c) > 8%; in phase 3, it was increased for patients with HbA_1c ≤ 8% while sustaining the phase 2 change. Increased preoperative insulin doses did not change the rates of day of surgery (DOS) hyperglycemia or hypoglycemia. Overall, HCP adherence to the modified protocols was high (89%). A decline in HCP adherence after phase 2 protocol change was associated with a transient increase in DOS hyperglycemia. Patient adherence to preoperative medication instructions was high (86%) and was not affected by protocol changes.

Conclusions

Preoperative insulin intensification the evening before surgery did not change rates of DOS hyperglycemia or hypoglycemia. HCP adherence decreased transiently, which briefly increased DOS hyperglycemia rates in some patients. Perioperative hyperglycemia, defined as blood glucose levels ≥ 180 mg/dL in the immediate pre- and postoperative period, is associated with increased postoperative morbidity, including infections, preoperative interventions, and in-hospital mortality.1-3 Despite being identified as a barrier to optimal perioperative glycemic control, limited evidence is available on patient or health care practitioner (HCP) adherence to preoperative insulin protocols.4-6.

Preoperative hyperglycemia is associated with elevated risk of perioperative ischemic stroke in type 2 diabetic patients undergoing non-cardiovascular surgery: A retrospective cohort study

BACKGROUND

Diabetes mellitus (DM) has been reported to be associated with perioperative stroke, but the effects of preoperative hyperglycemia on the risk of perioperative stroke in diabetic patients undergoing non-cardiovascular surgery remain unclear. This study investigated the association between preoperative hyperglycemia and the risk of perioperative ischemic stroke in type 2 diabetic patients undergoing non-cardiovascular surgery.

METHODS

This retrospective cohort study screened 27,002 patients with type 2 DM undergoing non-cardiovascular surgery with general anesthesia between January 2008 and August 2019 at The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital. The exposure of interest was preoperative hyperglycemia, defined as a fasting plasma glucose (FPG) ≥ 7 mmol/L. The outcome of interest was a new diagnosis of perioperative ischemic stroke within 30 days after surgery. Residual confounding was minimized by controlling for observable patient and intraoperative factors. Logistic regression was conducted in the total and propensity score matched cohorts. In addition, we stratified patients into six subgroups to investigate whether the association between preoperative hyperglycemia and perioperative ischemic stroke differs in these subgroups.

RESULTS

The overall incidence of perioperative ischemic stroke was 0.53% (n = 144) in the current cohort. The odds of perioperative ischemic stroke were significantly increased for patients with preoperative hyperglycemia after adjusting for patient- related variables (OR: 1.95; 95% CI: 1.39-2.75; p < 0.001), surgery-related variables (OR: 2.1; 95% CI: 1.51-2.94; p < 0.001), and all confounding variables (OR: 1.78; 95% CI: 1.26-2.53; p < 0.001). The risk of perioperative stroke was significantly increased in patients with preoperative hyperglycemia (OR: 2.51; 95% CI: 1.66-3.9; p < 0.001) in the propensity score matched cohort. Preoperative hyperglycemia was associated with the outcome for all the subgroups except for patients undergoing neurosurgery.

CONCLUSION

Preoperative hyperglycemia is associated with an elevated risk of perioperative stroke in patients with type 2 DM undergoing non-cardiovascular surgery. The effect could be eliminated for patients undergoing neurosurgery, during which specific risk factors should be considered.

Hypotension as a marker or mediator of perioperative organ injury: a narrative review

Perioperative hypotension has been repeatedly associated with organ injury and worse outcome, yet many interventions to reduce morbidity by attempting to avoid or reverse hypotension have floundered. In part, this reflects uncertainty as to what threshold of hypotension is relevant in the perioperative setting. Shifting population-based definitions for hypertension, plus uncertainty regarding individualised norms before surgery, both present major challenges in constructing useful clinical guidelines that may help improve clinical outcomes. Aside from these major pragmatic challenges, a wealth of biological mechanisms that underpin the development of higher blood pressure, particularly with increasing age, suggest that hypotension (however defined) or lower blood pressure per se does not account solely for developing organ injury after major surgery. The mosaic theory of hypertension, first proposed more than 60 yr ago, incorporates multiple, complementary mechanistic pathways through which clinical (macrovascular) attempts to minimise perioperative organ injury may unintentionally subvert protective or adaptive pathways that are fundamental in shaping the integrative host response to injury and inflammation. Consideration of the mosaic framework is critical for a more complete understanding of the perioperative response to acute sterile and infectious inflammation. The largely arbitrary treatment of perioperative blood pressure remains rudimentary in the context of multiple complex adaptive hypertensive endotypes, defined by distinct functional or pathobiological mechanisms, including the regulation of reactive oxygen species, autonomic dysfunction, and inflammation. Developing coherent strategies for the management of perioperative hypotension requires smarter, mechanistically solid interventions delivered by RCTs where observer bias is minimised.

Intraoperative Hyperglycemia May Be Associated with an Increased Risk of Myocardial Injury after Non-Cardiac Surgery in Diabetic Patients

BACKGROUND

Hyperglycemia in surgical candidates is associated with increased mortality and morbidity. We aimed to evaluate the effect of intraoperative blood glucose level on the incidence of myocardial injury after non-cardiac surgery (MINS) in diabetic patients.

METHODS

Diabetic patients with available intraoperative blood glucose measurement during non-cardiac surgery were enrolled in this study. Based on the highest intraoperative blood glucose level, patients were stratified into two groups: the blood sugar glucose (BST) < 180 group (intraoperative peak glucose < 180 mg/dL) and BST ≥ 180 group (intraoperative peak glucose ≥ 180 mg/dL). The primary outcome was the incidence of MINS, and secondary outcomes were in-hospital and 30-day mortalities.

RESULTS

Of the 11,302 diabetic patients, 8337 were in the BST < 180 group (73.8%) and 2965 in the BST ≥ 180 group (26.2%). After adjustment with inverse probability weighting, MINS was significantly higher in the BST ≥ 180 group (24.0% vs. 17.2%; odds ratio (OR), 1.26; 95% confidence interval (CI), 1.14-1.40; p < 0.001). In addition, in-hospital and 30-day mortalities were also higher in the BST ≥ 180 group compared to the BST < 180 group (4.2% vs. 2.3%, hazard ratio (HR), 1.39; 95% CI, 1.07-1.81; p = 0.001, and 3.1% vs. 1.8%; HR, 1.76; 95% CI, 1.31-2.36; p < 0.001, respectively). Receiver-operating characteristic plots showed that the threshold of glucose level associated with MINS was 149 mg/dL.

CONCLUSION

Intraoperative hyperglycemia was associated with an increased MINS incidence and postoperative mortality in diabetic patients. Close monitoring of intraoperative blood glucose level may be helpful in detection and management of MINS.

Diagnosis and Management of Patients With Myocardial Injury After Noncardiac Surgery: A Scientific Statement From the American Heart Association

Myocardial injury after noncardiac surgery is defined by elevated postoperative cardiac troponin concentrations that exceed the 99th percentile of the upper reference limit of the assay and are attributable to a presumed ischemic mechanism, with or without concomitant symptoms or signs. Myocardial injury after noncardiac surgery occurs in ≈20% of patients who have major inpatient surgery, and most are asymptomatic. Myocardial injury after noncardiac surgery is independently and strongly associated with both short-term and long-term mortality, even in the absence of clinical symptoms, electrocardiographic changes, or imaging evidence of myocardial ischemia consistent with myocardial infarction. Consequently, surveillance of myocardial injury after noncardiac surgery is warranted in patients at high risk for perioperative cardiovascular complications. This scientific statement provides diagnostic criteria and reviews the epidemiology, pathophysiology, and prognosis of myocardial injury after noncardiac surgery. This scientific statement also presents surveillance strategies and treatment approaches.

Myocardial injury in noncardiac surgery

Myocardial injury is defined as an elevation of cardiac troponin (cTn) levels with or without associated ischemic symptoms. Robust evidence suggests that myocardial injury increases postoperative mortality after noncardiac surgery. The diagnostic criteria for myocardial injury after noncardiac surgery (MINS) include an elevation of cTn levels within 30 d of surgery without evidence of non-ischemic etiology. The majority of cases of MINS do not present with ischemic symptoms and are caused by a mismatch in oxygen supply and demand. Predictive models for general cardiac risk stratification can be considered for MINS. Risk factors include comorbidities, anemia, glucose levels, and intraoperative blood pressure. Modifiable factors may help prevent MINS; however, further studies are needed. Recent guidelines recommend routine monitoring of cTn levels during the first 48 h post-operation in high-risk patients since MINS most often occurs in the first 3 days after surgery without symptoms. The use of cardiovascular drugs, such as aspirin, antihypertensives, and statins, has had beneficial effects in patients with MINS, and direct oral anticoagulants have been shown to reduce the mortality associated with MINS in a randomized controlled trial. Myocardial injury detected before noncardiac surgery was also found to be associated with postoperative mortality, though further studies are needed.

Quality gaps in screening and monitoring for postoperative hyperglycemia in a Canadian hospital: a retrospective cohort study

INTRODUCTION

Evidence-based preoperative, intraoperative and postoperative glycemic management may reduce poor surgical outcomes. Previous studies suggest that quality gaps in perioperative glycemic management may be common.

RESEARCH DESIGN AND METHODS

This retrospective cohort study used administrative health and laboratory data from a single center to estimate quality gaps in perioperative glycemic management in patients with and without diabetes between April 2019 and March 2020. We examined the proportion of patients with preoperative hemoglobin A1c (HbA1c) measurement, postoperative point-of-care testing (POCT) for glucose, hyperglycemia, and basal bolus insulin regimens. We compared the median length of stay (LOS) in patients with and without postoperative hyperglycemia, adjusted for age and sex.

RESULTS

There were 6576 patients in our cohort; 1165 (17.8%) had diabetes. Most patients with diabetes had an HbA1c measured prior to surgery (n=697, 59.8%). Postoperatively, 16.9% of patients with diabetes had no POCT monitoring (n=197) and 65.7% had hyperglycemia (n=636). Only 35.9% of patients who received insulin had a basal bolus insulin regimen (n=229). Patients with diabetes who had postoperative hyperglycemia had a longer median LOS compared with those who did not have postoperative hyperglycemia (8.4 days (95% CI 7.5 to 9.4) and 6.7 days (95% CI 6.3 to 7.1), respectively). In patients without diabetes, median LOS was 7.4 days (95% CI 4.4 to 10.4) for those with hyperglycemia and 5.2 days (95% CI 5.1 to 5.4) for those with in-target glucose.

CONCLUSIONS

Quality gaps in perioperative glycemic management include measurement of blood glucose after surgery and treatment of postoperative hyperglycemia. These gaps may contribute to longer LOS.

Glycemic variability in type 2 diabetes mellitus and acute coronary syndrome: liraglutide compared with insulin glargine: a pilot study

Objective

To explore the glucagon-like peptide-1 analogue liraglutide in the hospital setting in patients with type 2 diabetes mellitus (T2DM) and acute coronary syndrome and to evaluate the safety and efficacy and its impact on hospitalization and short-term glycemic variability (GV).

Methods

A 12-week, open-label, prospective, randomized pilot clinical study with parallel groups that compared liraglutide (group 1) with glargine (group 2) and its impact on glycemic control and GV.

Results

Thirteen patients were included. During hospitalization, mean glucose was 164.75 mg/dL (standard deviation [SD] 19.94) in group 1 and 166.69 mg/dL (38.22) in group 2. GV determined by CV and SD was 20.98 (7.68) vs. 25.48 (7.19) and 34.37 (13.05) vs. 43.56 (19.53) in groups 1 and 2, respectively. Group 1 prandial insulin requirements during hospitalization were lower compared with group 2. Follow-up A1c in group 1 was 6.9% (−1.51%) and 6.5% in group 2 (−1.27). GV after discharge and hypoglycemia were lower in group 1 compared with group 2.

Conclusions

Liraglutide seems to reduce GV in the acute phase of acute coronary syndrome, and patients achieved optimal control with a low incidence of hypoglycemia. These results support the need to explore liraglutide in a larger multicenter trial.

Trial registration: The study was approved by the National Medical Ethics Committee of Spain. The study was registered at European Clinical Trials Database (EudraCT): 2014003298-40.

Prediction of mortality at one year after surgery for pertrochanteric fracture in the elderly via a Bayesian belief network

BACKGROUND

Pertrochanteric fractures in the elderly are common and associated with considerable mortality and disability. However, the predictors of the fracture mortality have been somewhat controversial. The aim of this study was to use univariate, multivariate analyses and a Bayesian belief network (BBN) model, which are graphic and intuitive to the clinician, to understand of the prognosis of pertrochanteric fractures.

METHODS

Records of patients undergoing surgery at our hospital between January 2013 and June 2018 were retrospectively reviewed. Univariate and multivariate regression as well as a machine-learned BBN model were used to estimate mortality at one year after surgery for pertrochanteric fracture in the elderly.

RESULTS

Complete data were available for 448 surgically treated patients who were followed up for 12 months (age ≥60 years). Multivariate regression analysis revealed that hypertension, diabetes mellitus, chronic obstructive pulmonary disease, albumin, serum potassium, blood urea nitrogen and blood lactate were independent risk factors for death in surgical treatment patients (P < 0.05). First-degree predictors of mortality following surgery were established: the number of comorbid diseases, serum albumin, blood lactate and blood urea nitrogen. Following cross-validation, the area under the ROC curve was 0.85 (95% CI: 0.76-0.91) for the one-year probability of postoperative mortality.

CONCLUSION

We believe cohesive models such as the Bayesian belief network can be useful as clinical decision-support tools and provide clinicians with information to the treatment of old pertrochanteric fracture. This method warrants further development and must be externally validated in other patient populations.

The Effects of Type 2 Diabetes and Postoperative Pneumonia on the Mortality in Inpatients with Surgery

OBJECTIVE

The aim of the study was to explore the relationship between type 2 diabetes (T2DM) and postoperative pneumonia, and the effects of T2DM and postoperative pneumonia on the mortality in inpatients with surgery.

METHODS

A retrospective study was conducted on 43,174 inpatients with surgery in The First Hospital of Qinhuangdao. These patients were divided into four groups according to T2DM and postoperative pneumonia, Group A subjects without T2DM and postoperative pneumonia, Group B subjects with T2DM only, Group C subjects with postoperative pneumonia only and Group D subjects with T2DM and postoperative pneumonia. In-hospital mortality was collected.

RESULTS

The incidences of postoperative pneumonia were higher in patients with T2DM than patients without T2DM (T2DM 3.2% vs Non-diabetes 1.7%, χ ²=36.219, P<0.001). The mortalities were 0.3% in Group A, 0.3% in Group B, 4.6% in Group C and 8.6% in Group D. In multiple logistic regression analysis, adjusted for sex, age, emergency admissions, coronary heart disease, heart failure, chronic kidney disease, hypoproteinemia, stroke and transient ischemic attack, the mortalities of Group C and Group D were 4.515 (95% CI: 2.779～7.336, P<0.001) times and 8.468 (95% CI: 3.567～20.099, P<0.001) times than the mortality of Group A.

CONCLUSION

T2DM is susceptible to postoperative pneumonia. The mortality increased in patients with postoperative pneumonia. When patients with T2DM and postoperative pneumonia at the same time, the mortality increased further. In T2DM patients with postoperative pneumonia, perioperative management should be improved for patient safety.