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AIM: The "2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery" provides recommendations to guide clinicians in the perioperative cardiovascular evaluation and management of adult patients undergoing noncardiac surgery. METHODS: A comprehensive literature search was conducted from August 2022 to March 2023 to identify clinical studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE: Recommendations from the "2014 ACC/AHA Guideline on Perioperative Cardiovascular Evaluation and Management of Patients Undergoing Noncardiac Surgery" have been updated with new evidence consolidated to guide clinicians; clinicians should be advised this guideline supersedes the previously published 2014 guideline. In addition, evidence-based management strategies, including pharmacological therapies, perioperative monitoring, and devices, for cardiovascular disease and associated medical conditions, have been developed.
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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.
Subject(s)
Heart Injuries , Myocardial Infarction , Humans , Female , Aged , Male , Prospective Studies , Self Report , Myocardial Infarction/epidemiology , Phenotype , Postoperative Complications/epidemiology , Risk FactorsABSTRACT
BACKGROUND: Postoperative respiratory failure is a serious complication that could benefit from early accurate identification of high-risk patients. We developed and validated a machine learning model to predict postoperative respiratory failure, defined as prolonged (>48 h) mechanical ventilation or reintubation after surgery. METHODS: Easily extractable electronic health record (EHR) variables that do not require subjective assessment by clinicians were used. From EHR data of 307,333 noncardiac surgical cases, the model, trained with a gradient boosting algorithm, utilised a derivation cohort of 99,025 cases from Seoul National University Hospital (2013-9). External validation was performed using three separate cohorts A-C from different hospitals comprising 208,308 cases. Model performance was assessed by area under the receiver operating characteristic (AUROC) curve and area under the precision-recall curve (AUPRC), a measure of sensitivity and precision at different thresholds. RESULTS: The model included eight variables: serum albumin, age, duration of anaesthesia, serum glucose, prothrombin time, serum creatinine, white blood cell count, and body mass index. Internally, the model achieved an AUROC of 0.912 (95% confidence interval [CI], 0.908-0.915) and AUPRC of 0.113. In external validation cohorts A, B, and C, the model achieved AUROCs of 0.879 (95% CI, 0.876-0.882), 0.872 (95% CI, 0.870-0.874), and 0.931 (95% CI, 0.925-0.936), and AUPRCs of 0.029, 0.083, and 0.124, respectively. CONCLUSIONS: Utilising just eight easily extractable variables, this machine learning model demonstrated excellent discrimination in both internal and external validation for predicting postoperative respiratory failure. The model enables personalised risk stratification and facilitates data-driven clinical decision-making.
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Machine Learning , Postoperative Complications , Respiratory Insufficiency , Humans , Female , Male , Middle Aged , Aged , Postoperative Complications/diagnosis , Adult , Cohort Studies , Risk Assessment/methods , Respiration, Artificial , Reproducibility of Results , Electronic Health Records , Predictive Value of Tests , Surgical Procedures, Operative/adverse effectsABSTRACT
BACKGROUND: Preoperative anaemia and red blood cell (RBC) transfusions are associated with poorer clinical outcomes. It is unknown whether perioperative RBC transfusions mediate the relationship between preoperative haemoglobin levels and postoperative outcomes. METHODS: This was a prospective observational study among patients aged ≥50 yr undergoing elective major noncardiac surgery from four Swedish hospitals. The co-primary outcomes were 1-yr major adverse cardiovascular and cerebrovascular events (MACCEs) and all-cause mortality. The secondary outcome was a composite of 30-day mortality, MACCEs, acute kidney injury (AKI), pulmonary embolism, anastomotic leak, and postoperative infection. Mediation analyses were conducted with preoperative haemoglobin as the exposure and RBC transfusion as a mediator. RESULTS: Among 1060 patients (mean age 70 [SD 9] yr; 472 [45%] women), 171 patients (16.1%) developed 1-yr MACCEs, and 105 patients (9.9%) died within 1 yr. Preoperative haemoglobin levels were significantly associated with both 1-yr MACCEs (b=-0.015, P=0.041) and all-cause mortality (b=-0.028, P<0.001). Volume of RBC transfusion was not directly associated with the outcomes and did not mediate the relationship between preoperative haemoglobin levels and 1-yr MACCEs (b=-0.001, P=0.451) or all-cause mortality (b=-0.002, P=0.293). For the secondary outcome, RBC transfusions had a significant mediating effect between preoperative haemoglobin and the composite 30-day outcome; however, no direct association was observed (b=0.006, P=0.554). CONCLUSIONS: Preoperative haemoglobin levels were significantly associated with 1-yr MACCEs and all-cause mortality. This effect was not mediated by perioperative RBC transfusions. Further research is needed to confirm these findings.
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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.
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Myocardial Infarction , Troponin , Humans , Prospective Studies , Canada/epidemiology , Myocardial Infarction/diagnosis , Myocardial Infarction/epidemiology , Cohort Studies , Postoperative Complications/epidemiology , Risk Factors , BiomarkersABSTRACT
Guidelines provide a framework to take better care of our patients. They are published by different professional groups and are based on all the research done for us by hardworking colleagues. Compiling a guideline is an enormous amount of work and is generally done with the utmost care. However, recommendations often require a subjective interpretation of published research, where personal and academic interests can influence the outcome. We discuss two recently published guidelines on perioperative cardiovascular assessment that led to different conclusions on some important areas of patient care.
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Cardiovascular Diseases , Perioperative Medicine , Humans , Perioperative Care , Professionalism , PrognosisABSTRACT
INTRODUCTION: Cardiac complications after major noncardiac surgery are common and associated with high morbidity and mortality. How preoperative use of beta-blockers may impact perioperative cardiac complications remains unclear. METHODS: In a multicentre prospective cohort study, preoperative beta-blocker use was ascertained in consecutive patients at elevated cardiovascular risk undergoing major noncardiac surgery. Cardiac complications were prospectively monitored and centrally adjudicated by two independent experts. The primary endpoint was perioperative myocardial infarction or injury attributable to a cardiac cause (cardiac PMI) within the first three postoperative days. The secondary endpoints were major adverse cardiac events (MACE), defined as a composite of myocardial infarction, acute heart failure, life-threatening arrhythmia, and cardiovascular death and all-cause death after 365 days. We used inverse probability of treatment weighting to account for differences between patients receiving beta-blockers and those who did not. RESULTS: A total of 3839/10 272 (37.4%) patients (mean age 74 yr; 44.8% female) received beta-blockers before surgery. Patients on beta-blockers were older, and more likely to be male with established cardiorespiratory and chronic kidney disease. Cardiac PMI occurred in 1077 patients, with a weighted odds ratio of 1.03 (95% confidence interval [CI] 0.94-1.12, P=0.55) for patients on beta-blockers. Within 365 days of surgery, 971/10 272 (9.5%) MACE had occurred, with a weighted hazard ratio of 0.99 (95% CI 0.83-1.18, P=0.90) for patients on beta-blockers. CONCLUSION: Preoperative use of beta-blockers was not associated with decreased cardiac complications including cardiac perioperative myocardial infarction or injury and major adverse cardiac event. Additionally, preoperative use of beta-blockers was not associated with increased all-cause death within 30 and 365 days. CLINICAL TRIAL REGISTRATION: NCT02573532.
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Adrenergic beta-Antagonists , Postoperative Complications , Preoperative Care , Humans , Adrenergic beta-Antagonists/therapeutic use , Adrenergic beta-Antagonists/adverse effects , Male , Female , Aged , Prospective Studies , Postoperative Complications/epidemiology , Preoperative Care/methods , Middle Aged , Aged, 80 and over , Cohort Studies , Surgical Procedures, Operative/adverse effects , Myocardial Infarction/epidemiology , Heart Diseases/epidemiologyABSTRACT
BACKGROUND: Numerous models have been developed to predict acute kidney injury (AKI) after noncardiac surgery, yet there is a lack of independent validation and comparison among them. METHODS: We conducted a systematic literature search to review published risk prediction models for AKI after noncardiac surgery. An independent external validation was performed using a retrospective surgical cohort at a large Chinese hospital from January 2019 to October 2022. The cohort included patients undergoing a wide range of noncardiac surgeries with perioperative creatinine measurements. Postoperative AKI was defined according to the Kidney Disease Improving Global Outcomes creatinine criteria. Model performance was assessed in terms of discrimination (area under the receiver operating characteristic curve, AUROC), calibration (calibration plot), and clinical utility (net benefit), before and after model recalibration through intercept and slope updates. A sensitivity analysis was conducted by including patients without postoperative creatinine measurements in the validation cohort and categorising them as non-AKI cases. RESULTS: Nine prediction models were evaluated, each with varying clinical and methodological characteristics, including the types of surgical cohorts used for model development, AKI definitions, and predictors. In the validation cohort involving 13,186 patients, 650 (4.9%) developed AKI. Three models demonstrated fair discrimination (AUROC between 0.71 and 0.75); other models had poor or failed discrimination. All models exhibited some miscalibration; five of the nine models were well-calibrated after intercept and slope updates. Decision curve analysis indicated that the three models with fair discrimination consistently provided a positive net benefit after recalibration. The results were confirmed in the sensitivity analysis. CONCLUSIONS: We identified three models with fair discrimination and potential clinical utility after recalibration for assessing the risk of acute kidney injury after noncardiac surgery.
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Acute Kidney Injury , Postoperative Complications , Humans , Acute Kidney Injury/diagnosis , Acute Kidney Injury/etiology , Postoperative Complications/diagnosis , Postoperative Complications/etiology , Postoperative Complications/epidemiology , Risk Assessment/methods , Retrospective Studies , Cohort Studies , Creatinine/blood , Surgical Procedures, Operative/adverse effects , Middle Aged , Male , Female , Risk Factors , AgedABSTRACT
BACKGROUND: Guideline adherence in the medical field leaves room for improvement. Digitalised decision support helps improve compliance. However, the complex nature of the guidelines makes implementation in clinical practice difficult. METHODS: This single-centre prospective study included 204 adult ASA physical status 3-4 patients undergoing elective noncardiac surgery at a German university hospital. Agreement of clearance for surgery between a guideline expert and a digital guideline support tool was investigated. The decision made by the on-duty anaesthetists (standard approach) was assessed for agreement with the expert in a cross-over design. The main outcome was the level of agreement between digital guideline support and the expert. RESULTS: The digital guideline support approach cleared 18.1% of the patients for surgery, the standard approach cleared 74.0%, and the expert approach cleared 47.5%. Agreement of the expert decision with digital guideline support (66.7%) and the standard approach (67.6%) was fair (Cohen's kappa 0.37 [interquartile range 0.26-0.48] vs 0.31 [0.21-0.42], P=0.6). Taking the expert decision as a benchmark, correct clearance using digital guideline support was 50.5%, and correct clearance using the standard approach was 44.6%. Digital guideline support incorrectly asked for additional examinations in 31.4% of the patients, whereas the standard approach did not consider conditions that would have justified additional examinations before surgery in 29.4%. CONCLUSIONS: Strict guideline adherence for clearance for surgery through digitalised decision support inadequately considered patients, clinical context. Vague formulations, weak recommendations, and low-quality evidence complicate guideline translation into explicit rules. CLINICAL TRIAL REGISTRATION: NCT04058769.
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Guideline Adherence , Preoperative Care , Adult , Aged , Female , Humans , Male , Middle Aged , Cross-Over Studies , Decision Support Systems, Clinical , Decision Support Techniques , Elective Surgical Procedures/standards , Germany , Practice Guidelines as Topic , Preoperative Care/methods , Preoperative Care/standards , Prospective Studies , SoftwareABSTRACT
BACKGROUND: Postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) are common after noncardiac surgery. Postsurgical pain is frequent and can persist as chronic postsurgical pain (CPSP). The association between postsurgical pain and POD or POCD is biologically plausible. We conducted this systematic review to evaluate the association between acute postsurgical pain or CPSP and POD or POCD in adults undergoing noncardiac surgery. METHODS: We followed Preferred Reporting Items for Systematic Review and Meta-Analyses. We searched MEDLINE, EMBASE, Cochrane, CINAHL and PSYCHINFO up to May 2023. We included cohort, case-control, and cross-sectional studies of any language. Pairs of reviewers independently screened studies, extracted data and assessed the risk of bias using the CLARITY tool and the Joanna Briggs Institute checklist. We assessed the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach. Where possible, we conducted random-effects meta-analyses to summarise our findings. RESULTS: We analysed 30 studies (>9000 participants) that assessed the association between acute postoperative pain and POD/POCD. Dose-response meta-analyses found that postoperative pain intensity was associated with occurrence of POD (adjusted relative risk [aRR]/unit of pain intensity: 1.26; 95% confidence interval [CI]: 1.17-1.35; low certainty of evidence) and risk of developing POD (aRR/unit of pain intensity: 1.18; 95% CI: 1.08-1.30; low certainty of evidence). There was very low certainty of evidence regarding the association between postoperative pain and POCD. No studies assessed the association between CPSP and POCD. Residual confounding and substantial methodological variability between studies prevented pooling data from many of the included studies and lowered certainty of evidence. CONCLUSIONS: Dose-response meta-analyses found that postoperative pain intensity was associated with occurrence of and risk of developing POD. SYSTEMATIC REVIEW PROTOCOL: PROSPERO-CRD42021192105.
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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.
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Diabetes Mellitus, Type 1 , Hyperglycemia , Humans , Blood Glucose/metabolism , Blood Glucose Self-Monitoring , Continuous Glucose Monitoring , Multiple Organ FailureABSTRACT
BACKGROUND: Patients with elevated preoperative plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP >100 pg ml-1) experience more complications after noncardiac surgery. Individuals prescribed renin-angiotensin system (RAS) inhibitors for cardiometabolic disease are at particular risk of perioperative myocardial injury and complications. We hypothesised that stopping RAS inhibitors before surgery increases the risk of perioperative myocardial injury, depending on preoperative risk stratified by plasma NT-proBNP concentrations. METHODS: In a preplanned analysis of a phase 2a trial in six UK centres, patients ≥60 yr old undergoing elective noncardiac surgery were randomly assigned either to stop or continue RAS inhibitors before surgery. The pharmacokinetic profile of individual RAS inhibitors determined for how long they were stopped before surgery. The primary outcome, masked to investigators, clinicians, and patients, was myocardial injury (plasma high-sensitivity troponin-T ≥15 ng L-1 or a ≥5 ng L-1 increase, when preoperative high-sensitivity troponin-T ≥15 ng L-1) within 48 h after surgery. The co-exposures of interest were preoperative plasma NT-proBNP (< or >100 pg ml -1) and stopping or continuing RAS inhibitors. RESULTS: Of 241 participants, 101 (41.9%; mean age 71 [7] yr; 48% females) had preoperative NT-proBNP >100 pg ml -1 (median 339 [160-833] pg ml-1), of whom 9/101 (8.9%) had a formal diagnosis of cardiac failure. Myocardial injury occurred in 63/101 (62.4%) subjects with NT-proBNP >100 pg ml-1, compared with 45/140 (32.1%) subjects with NT-proBNP <100 pg ml -1 {odds ratio (OR) 3.50 (95% confidence interval [CI] 2.05-5.99); P<0.0001}. For subjects with preoperative NT-proBNP <100 pg ml-1, 30/75 (40%) who stopped RAS inhibitors had myocardial injury, compared with 15/65 (23.1%) who continued RAS inhibitors (OR for stopping 2.22 [95% CI 1.06-4.65]; P=0.03). For preoperative NT-proBNP >100 pg ml-1, myocardial injury rates were similar regardless of stopping (62.2%) or continuing (62.5%) RAS inhibitors (OR for stopping 0.98 [95% CI 0.44-2.22]). CONCLUSIONS: Stopping renin-angiotensin system inhibitors in lower-risk patients (preoperative NT-proBNP <100 pg ml -1) increased the likelihood of myocardial injury before noncardiac surgery.
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Heart Injuries , Natriuretic Peptide, Brain , Female , Humans , Aged , Male , Troponin T , Renin-Angiotensin System , Biomarkers , Peptide FragmentsABSTRACT
Myocardial injury after noncardiac surgery (MINS) and perioperative myocardial injury are associated with increased morbidity and mortality. Both are diagnosed by a perioperative increase in troponin, yet there is controversy if MINS is a genuine myocardial insult. We applied postoperative cardiovascular magnetic resonance T2 mapping techniques to visualise acute myocardial injury (i.e. oedema) in six patients with multiple cardiovascular risk factors who underwent aortic surgery. The burden of myocardial oedema was substantially higher in four patients with elevated troponin qualifying for MINS, compared with patients without MINS. The data and images suggest that MINS represents genuine myocardial injury.
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Magnetic Resonance Imaging , Postoperative Complications , Humans , Male , Postoperative Complications/diagnostic imaging , Postoperative Complications/etiology , Aged , Female , Middle Aged , Magnetic Resonance Imaging/methods , Troponin/blood , Aged, 80 and over , Edema/diagnostic imaging , Edema/etiologyABSTRACT
BACKGROUND: Limited knowledge exists regarding long-term renal outcomes after noncardiac surgery. This study investigated the incidence of, and risk factors for, developing advanced chronic kidney disease (CKD) and major adverse kidney events within 1 yr of surgery in a nationwide cohort. METHODS: Adults without renal dysfunction before noncardiac surgery in Sweden were included between 2007 and 2013 in this observational multicentre cohort study. We analysed data from a national surgical database linked to several national and quality outcome registries. Associations of perioperative risk factors with advanced CKD (estimated glomerular filtration rate [eGFR] <30 ml min-1 1.73 m-2) and major adverse kidney events within 1 yr (MAKE365, comprising eGFR <30 ml min-1 1.73 m-2, chronic dialysis, death) were quantified. RESULTS: Of 237,124 patients, 1597 (0.67%) developed advanced CKD and 16,789 (7.1%) developed MAKE365. Risk factors for advanced CKD included higher ASA physical status, urological surgery, extended surgical duration, prolonged postoperative hospital stay, repeated surgery, and postoperative use of renin-angiotensin-aldosterone system blockers. Advanced acute kidney disease (AKD) (eGFR <30 ml min-1 1.73 m-2 within 90 postoperative days) occurred in 1661 (0.70%) patients and was associated with advanced CKD (subdistribution hazard ratio [SHR] 44.5, 95% confidence interval [CI] 38.7-51.1) and MAKE365 (hazard ratio [HR] 6.60, 95% CI 6.07-7.17). Among patients with advanced AKD after surgery 36% developed advanced CKD at 1 yr after surgery and 51% developed MAKE365. CONCLUSIONS: Advanced CKD within 1 yr after surgery is uncommon but clinically important in patients without preoperative renal dysfunction. Advanced AKD after surgery constitutes a major risk factor for advanced CKD and MAKE365.
Subject(s)
Acute Kidney Injury , Postoperative Complications , Renal Insufficiency, Chronic , Humans , Male , Female , Renal Insufficiency, Chronic/epidemiology , Aged , Middle Aged , Risk Factors , Cohort Studies , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Sweden/epidemiology , Acute Kidney Injury/epidemiology , Acute Kidney Injury/etiology , Glomerular Filtration Rate , Adult , Aged, 80 and over , Incidence , RegistriesABSTRACT
BACKGROUND: The accurate diagnosis of heart failure (HF) before major noncardiac surgery is frequently challenging. The impact of diagnostic accuracy for HF on intraoperative practice patterns and clinical outcomes remains unknown. METHODS: We performed an observational study of adult patients undergoing major noncardiac surgery at an academic hospital from 2015 to 2019. A preoperative clinical diagnosis of HF was defined by keywords in the preoperative assessment or a diagnosis code. Medical records of patients with and without HF clinical diagnoses were reviewed by a multispecialty panel of physician experts to develop an adjudicated HF reference standard. The exposure of interest was an adjudicated diagnosis of heart failure. The primary outcome was volume of intraoperative fluid administered. The secondary outcome was postoperative acute kidney injury (AKI). RESULTS: From 40 659 surgeries, a stratified subsample of 1018 patients were reviewed by a physician panel. Among patients with adjudicated diagnoses of HF, those without a clinical diagnosis (false negatives) more commonly had preserved left ventricular ejection fractions and fewer comorbidities. Compared with false negatives, an accurate diagnosis of HF (true positives) was associated with 470 ml (95% confidence interval: 120-830; P=0.009) lower intraoperative fluid administration and lower risk of AKI (adjusted odds ratio:0.39, 95% confidence interval 0.18-0.89). For patients without adjudicated diagnoses of HF, non-HF was not associated with differences in either fluids administered or AKI. CONCLUSIONS: An accurate preoperative diagnosis of heart failure before noncardiac surgery is associated with reduced intraoperative fluid administration and less acute kidney injury. Targeted efforts to improve preoperative diagnostic accuracy for heart failure may improve perioperative outcomes.
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BACKGROUND: Myocardial injury after noncardiac surgery (MINS) is one of the most common complications associated with postoperative adverse cardiovascular outcomes and mortality. However, MINS often fails to be timely diagnosed due to the absence of clinical symptoms and limited diagnostic methods. The metabolomic analysis might be an efficient way to discover new biomarkers of MINS. Characterizing the metabolomic features of MINS patients may provide new insight into the diagnosis of MINS. METHODS: In this study, serum samples from 20 matched patients with or without MINS (n = 10 per group) were subjected to untargeted metabolomics analysis to investigate comprehensive metabolic information. Differential metabolites were identified, and the enriched metabolic pathway was determined based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. RESULTS: A comprehensive analysis revealed 124 distinct metabolites, predominantly encompassing lipids, amino acids and other compounds. The observed modifications in metabolic pathways in patients with or without MINS showed significant clustering in cholesterol metabolism, aldosterone synthesis and secretion, primary bile acid biosynthesis, as well as cysteine and methionine metabolism. Four specific metabolites (taurocholic acid, L-pyroglutamic acid, taurochenodeoxycholic acid, and pyridoxamine) exhibited promising potential as biomarkers for prognosticating MINS. CONCLUSIONS: This study contributes valuable insights into the metabolomic features of MINS and the discovery of potential biomarkers which may help the early diagnosis of MINS. The identified metabolites and altered pathways offer valuable insights into the molecular underpinnings of MINS, paving the way for improved diagnostic approaches and potential intervention strategies.
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Heart Injuries , Postoperative Complications , Humans , Postoperative Complications/diagnosis , Metabolomics , Biomarkers , HeartABSTRACT
BACKGROUND: Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication following noncardiac surgery and is associated with increased mortality. Early identification of geriatric patients at high risk of AKI could facilitate preventive measures and improve patient prognosis. This study used machine learning methods to identify important features and predict AKI following noncardiac surgery in geriatric patients. METHODS: The data for this study were obtained from a prospective cohort. Patients aged ≥ 65 years who received noncardiac surgery from June 2019 to December 2021 were enrolled. Data were split into training set (from June 2019 to March 2021) and internal validation set (from April 2021 to December 2021) by time. The least absolute shrinkage and selection operator (LASSO) regularization algorithm and the random forest recursive feature elimination algorithm (RF-RFE) were used to screen important predictors. Models were trained through extreme gradient boosting (XGBoost), random forest, and LASSO. The SHapley Additive exPlanations (SHAP) package was used to interpret the machine learning model. RESULTS: The training set included 6753 geriatric patients. Of these, 250 (3.70%) patients developed AKI. The XGBoost model with RF-RFE selected features outperformed other models with an area under the precision-recall curve (AUPRC) of 0.505 (95% confidence interval [CI]: 0.369-0.626) and an area under the receiver operating characteristic curve (AUROC) of 0.806 (95%CI: 0.733-0.875). The model incorporated ten predictors, including operation site and hypertension. The internal validation set included 3808 geriatric patients, and 96 (2.52%) patients developed AKI. The model maintained good predictive performance with an AUPRC of 0.431 (95%CI: 0.331-0.524) and an AUROC of 0.845 (95%CI: 0.796-0.888) in the internal validation. CONCLUSIONS: This study developed a simple machine learning model and a web calculator for predicting AKI following noncardiac surgery in geriatric patients. This model may be a valuable tool for guiding preventive measures and improving patient prognosis. TRIAL REGISTRATION: The protocol of this study was approved by the Committee of Ethics from West China Hospital of Sichuan University (2019-473) with a waiver of informed consent and registered at www.chictr.org.cn (ChiCTR1900025160, 15/08/2019).
Subject(s)
Acute Kidney Injury , Machine Learning , Postoperative Complications , Humans , Acute Kidney Injury/diagnosis , Acute Kidney Injury/etiology , Acute Kidney Injury/epidemiology , Aged , Female , Male , Prospective Studies , Postoperative Complications/diagnosis , Postoperative Complications/etiology , Aged, 80 and over , Risk Assessment/methods , Surgical Procedures, Operative/adverse effects , Risk FactorsABSTRACT
BACKGROUND: Perioperative myocardial injury/infarction (PMI) following noncardiac surgery is a frequent cardiac complication. This study aims to evaluate PMI risk and explore preoperative assessment tools of PMI in patients at increased cardiovascular (CV) risk who underwent noncardiac surgery under the surgical and medical co-management (SMC) model. METHODS: A prospective cohort study that included consecutive patients at increased CV risk who underwent intermediate- or high-risk noncardiac surgery at the Second Medical Center, Chinese PLA General Hospital, between January 2017 and December 2022. All patients were treated with perioperative management by the SMC team. The SMC model was initiated when surgical intervention was indicated and throughout the entire perioperative period. The incidence, risk factors, and impact of PMI on 30-day mortality were analyzed. The ability of the Revised Cardiac Risk Index (RCRI), frailty, and their combination to predict PMI was evaluated. RESULTS: 613 eligible patients (mean [standard deviation, SD] age 73.3[10.9] years, 94.6% male) were recruited consecutively. Under SMC, PMI occurred in 24/613 patients (3.9%). Patients with PMI had a higher rate of 30-day mortality than patients without PMI (29.2% vs. 0.7%, p = 0.00). The FRAIL Scale for frailty was independently associated with an increased risk for PMI (odds ratio = 5.91; 95% confidence interval [CI], 2.34-14.93; p = 0.00). The RCRI demonstrated adequate discriminatory capacity for predicting PMI (area under the curve [AUC], 0.78; 95% CI, 0.67-0.88). Combining frailty with the RCRI further increased the accuracy of predicting PMI (AUC, 0.87; 95% CI, 0.81-0.93). CONCLUSIONS: The incidence of PMI was relatively low in high CV risk patients undergoing intermediate- or high-risk noncardiac surgery under SMC. The RCRI adequately predicted PMI. Combining frailty with the RCRI further increased the accuracy of PMI predictions, achieving excellent discriminatory capacity. These findings may aid personalized evaluation and management of high-risk patients who undergo intermediate- or high-risk noncardiac surgery.
Subject(s)
Myocardial Infarction , Postoperative Complications , Humans , Male , Female , Aged , Prospective Studies , Myocardial Infarction/epidemiology , Myocardial Infarction/diagnosis , Postoperative Complications/epidemiology , Postoperative Complications/diagnosis , Postoperative Complications/etiology , Risk Assessment/methods , Risk Factors , Surgical Procedures, Operative/adverse effects , Middle Aged , Incidence , Aged, 80 and over , Frailty/epidemiology , Frailty/diagnosis , China/epidemiologyABSTRACT
INTRODUCTION: Frailty has become a worldwide health burden that has a large influence on public health and clinical practice. The incidence of frailty is anticipated to increase as the ageing population increases. Myocardial injury after noncardiac surgery (MINS) is associated with short-term and long-term mortality. However, the incidence of MINS in frail geriatric patients is unknown. METHODS AND ANALYSIS: This prospective, multicentre, real-world observational cohort study will be conducted at 18 designated centres in China from January 2023 to December 2024, with an anticipated sample size of 856 patients aged 65 years and older who are scheduled to undergo noncardiac surgery. The primary outcome will be the incidence of MINS. MINS is defined as a fourth-generation plasma cardiac troponin T (cTnT) concentration ≥ 0.03 ng/mL exhibited at least once within 30 days after surgery, with or without symptoms of myocardial ischaemia. All data will be collected via electronic data acquisition. DISCUSSION: This study will explore the incidence of MINS in frail patients. The characteristics, predictive factors and 30-day outcomes of MINS in frail patients will be further investigated to lay the foundation for identifying clinical interventions. CLINICAL TRIAL REGISTRATION: https://beta. CLINICALTRIALS: gov/study/NCT05635877 , NCT05635877.
Subject(s)
Frailty , Myocardial Ischemia , Humans , Aged , Postoperative Complications/diagnosis , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Prospective Studies , Frailty/diagnosis , Frailty/epidemiology , Frailty/complications , Myocardial Ischemia/diagnosis , Myocardial Ischemia/epidemiology , Myocardial Ischemia/etiology , Cohort Studies , Risk Factors , Observational Studies as Topic , Multicenter Studies as TopicABSTRACT
BACKGROUND: One-lung ventilation and intrathoracic operations during thoracoscopic surgery often result in intraoperative hypoxaemia and haemodynamic fluctuations, resulting in perioperative myocardial injury. Dexmedetomidine, an alpha-2 (α-2) agonist, has demonstrated myocardial protection. We hypothesize that the routine intravenous administration of dexmedetomidine could reduce the extent of myocardial injury during video-assisted thoracoscopic surgery (VATS). METHODS: The study included patients aged ≥ 45 years, classified as American Society of Anesthesiologists physical status I-III, who underwent general anesthesia for video-assisted thoracoscopic surgery. The patients were randomly assigned to either the intervention group, receiving general anesthesia with dexmedetomidine, or the control group, receiving general anesthesia without dexmedetomidine. Patients in the intervention group received a loading dose of dexmedetomidine (0.5 µg·kg-1) before anesthesia induction, followed by a continuous infusion (0.5 µg·kg-1·h-1) until the completion of the surgery. Placebos (saline) were administered for the control group to match the treatment. The primary outcome assessed was the high-sensitivity cardiac troponin T on postoperative day 1. Additionally, the incidence of myocardial injury after noncardiac surgery (MINS) was noted. RESULTS: A total of 110 participants completed this study. The median [interquartile range (IQR)] concentration of hs-cTnT on postoperative day 1 was lower in the intervention group compared with the control group (7 [6-9] vs. 8 [7-11] pg·ml-1; difference in medians,1 pg·ml-1; 95% confidence interval [CI], 0 to 2; P = 0.005). Similarly, on postoperative day 3, the median [IQR] concentration of hs-cTnT in the intervention group was also lower than that in the control group (6 [5-7] vs. 7 [6-9]; difference in medians,1 pg·ml-1; 95%CI, 0 to 2; P = 0.011). Although the incidence of MINS was not statistically significant (the intervention group vs. the control group, 3.8% vs. 9.1%, P = 0.465), there was a decreasing trend in the incidence of MINS in the intervention group. CONCLUSION: The administration of perioperative dexmedetomidine in patients ≥ 45 years undergoing video-assisted thoracoscopic surgery could lower the release of postoperative hs-cTnT without reducing incidence of myocardial injury. TRIAL REGISTRATION: chictr.org.cn (ChiCTR2200063193); prospectively registered 1 September 2022.