Hospital Readmission After Perioperative Acute Myocardial Infarction Associated With Noncardiac Surgery

Postoperative Myocardial Infarction after Non-Cardiac Surgery: An Update

Every year, not less than 300 million non-cardiac surgery interventions are performed in the world. Perioperative mortality after non-cardiac surgery is estimated at 2% in patients over 45 years of age. Cardiovascular events account for half of these deaths, and most are due to perioperative myocardial infarction (MINS). The diagnosis of postoperative myocardial infarction, before the introduction of cardiac biomarkers, was based on symptoms and electrocardiographic changes and its incidence was largely underestimated. The incidence of MINS when a standard troponin assay is used ranges between 8 and 19% but increases to 20-30% with high-sensitivity troponin assays. Higher troponin values suggesting myocardial injury, both with or without a definite diagnosis of myocardial infarction, are associated with an increase in 30-day and 1-year mortality. Diagnostic and therapeutic strategies are reported.

Development and validation of a prediction model to predict major adverse cardiovascular events in elderly patients undergoing noncardiac surgery: A retrospective cohort study

BACKGROUND AND AIMS

Current existing predictive tools have limitations in predicting major adverse cardiovascular events (MACEs) in elderly patients. We will build a new prediction model to predict MACEs in elderly patients undergoing noncardiac surgery by using traditional statistical methods and machine learning algorithms.

METHODS

MACEs were defined as acute myocardial infarction (AMI), ischemic stroke, heart failure and death within 30 days after surgery. Clinical data from 45,102 elderly patients (≥65 years old), who underwent noncardiac surgery from two independent cohorts, were used to develop and validate the prediction models. A traditional logistic regression and five machine learning models (decision tree, random forest, LGBM, AdaBoost, and XGBoost) were compared by the area under the receiver operating characteristic curve (AUC). In the traditional prediction model, the calibration was assessed using the calibration curve and the patients' net benefit was measured by decision curve analysis (DCA).

RESULTS

Among 45,102 elderly patients, 346 (0.76%) developed MACEs. The AUC of this traditional model was 0.800 (95% CI, 0.708-0.831) in the internal validation set, and 0.768 (95% CI, 0.702-0.835) in the external validation set. In the best machine learning prediction model-AdaBoost model, the AUC in the internal and external validation set was 0.778 and 0.732, respectively. Besides, for the traditional prediction model, the calibration curve of model performance accurately predicted the risk of MACEs (Hosmer and Lemeshow, p = 0.573), the DCA results showed that the nomogram had a high net benefit for predicting postoperative MACEs.

CONCLUSIONS

This prediction model based on the traditional method could accurately predict the risk of MACEs after noncardiac surgery in elderly patients.

Perioperative bleeding and outcomes after noncardiac surgery

BACKGROUND

Perioperative bleeding is a common and potentially life-threatening complication after surgery. We sought to identify the frequency, patient characteristics, causes, and outcomes of perioperative bleeding in patients undergoing noncardiac surgery.

METHODS

In a retrospective cohort study of a large administrative database, adults aged ≥45 years hospitalized for noncardiac surgery in 2018 were identified. Perioperative bleeding was defined using ICD-10 diagnosis and procedure codes. Clinical characteristics, in-hospital outcomes, and first hospital readmission within 6 months were assessed by perioperative bleeding status.

RESULTS

We identified 2,298,757 individuals undergoing noncardiac surgery, among which 35,429 (1.54%) had perioperative bleeding. Patients with bleeding were older, less likely to be female, and more likely to have renal and cardiovascular disease. All-cause, in-hospital mortality was higher in patients with vs without perioperative bleeding (6.0% vs 1.3%; adjusted OR [aOR] 2.38, 95% CI 2.26-2.50). Patients with vs without bleeding had a prolonged inpatient length of stay (6 [IQR 3-13] vs 3 [IQR 2-6] days, P < .001). Among those who were discharged alive, hospital readmission was more common within 6 months among patients with bleeding (36.0% vs 23.6%; adjusted HR 1.21, 95% CI 1.18-1.24). The risk of in-hospital death or readmission was greater in patients with vs without bleeding (39.8% vs 24.5%; aOR 1.33, 95% CI 1.29-1.38). When stratified by revised cardiac risk index , there was a stepwise increase in surgical bleeding risk with increasing perioperative cardiovascular risks.

CONCLUSIONS

Perioperative bleeding is reported in 1 out of every 65 noncardiac surgeries, with a higher incidence in patients at elevated cardiovascular risk. Among postsurgical inpatients with perioperative bleeding, approximately 1 of every 3 patients died during hospitalization or were readmitted within 6-months. Strategies to reduce perioperative bleeding are warranted to improve outcomes following non-cardiac surgery.

Dexmedetomidine attenuates myocardial ischemia-reperfusion injury via inhibiting ferroptosis by the cAMP/PKA/CREB pathway

This study is to investigate the effects of dexmedetomidine on myocardial ischemia-reperfusion (I/R) injury and its molecular mechanisms. H9c2 cell injury model was constructed by the hypoxia/normoxia (H/R) conditions. Besides, cAMP response element-binding protein (CREB) overexpression and knockdown cell lines were constructed. Cell viability was determined by cell-counting kit 8. Biochemical assays were used to detect oxidative stress-related biomarkers, cell apoptosis, and ferroptosis-related markers. Our results showed that dexmedetomidine's protective effects on H/R-induced cell damage were reversed by the inhibition of protein kinase A (PKA), CREB, and extracellular signal regulated kinase 1/2 (ERK1/2). Treatment of dexmedetomidine ameliorated oxidative stress in the cardiomyocytes induced by H/R, whereas inhibition of PKA, CREB, or ERK1/2 reversed these protective effects. Cell death including cell necrosis, apoptosis, and ferroptosis was found in the cells under H/R insult. Interestingly, targeting CREB ameliorated ferroptosis and oxidative stress in these cells. In conclusion, dexmedetomidine attenuates myocardial I/R injury by suppressing ferroptosis through the cAMP/PKA/CREB signaling pathway.

¿Es seguro el ácido tranexámico en la cirugía de reemplazo total de rodilla de pacientes con enfermedad coronaria?

Introducción: El ácido tranexámico reduce la pérdida sanguínea y los requerimientos de transfusiones luego de un reemplazo total de rodilla. Una de sus contraindicaciones relativas son los antecedentes de colocación de prótesis intravasculares coronarias, por un supuesto aumento de eventos tromboembólicos. Materiales y Métodos: Análisis retrospectivo de pacientes sometidos a un reemplazo total de rodilla primario y de revisión que recibieron ácido tranexámico y tenían antecedente de colocación de prótesis intravascular coronaria. Se los comparó con un grupo sin estas prótesis. Se analizó la presencia de cualquier cambio clínico o electrocardiográfico de oclusión coronaria aguda, eventos tromboembólicos, el requerimiento de transfusión sanguínea y el nivel de hemoglobina pre y posoperatorio. Resultados: 57 pacientes (59 cirugías, 56 reemplazos primarios y 3 revisiones) con colocación de prótesis intravascular coronaria, al menos, un año antes de la artroplastia. Un paciente tuvo síntomas de síndromecoronario agudo y cambios en el electrocardiograma. No hubo diferencias en la cantidad de eventos tromboembólicos. Solo un paciente del grupo de control recibió una transfusión de glóbulos rojos. El sangrado relativo fue menor en el grupo coronario independientemente del uso crónico de aspirina y clopidogrel antes de la cirugía (2,09 vs. 3,06 grupo de control; p = 0,01). En pacientes del alto riesgo, el ácido tranexámico no se asoció con más eventos tromboembólicos. Conclusiones: El ácido tranexámico impresionó ser seguro y efectivo en nuestro grupo de pacientes con prótesis intravasculares coronarias; sin embargo, se necesita un estudio prospectivo con más casos para confirmar estos resultados

Preoperative evaluation and perioperative management of patients undergoing major vascular surgery

Patients undergoing major vascular surgery have an increased risk of perioperative major adverse cardiovascular events (MACE). Accordingly, in this population, it is of particular importance to appropriately risk stratify patients' risk for these complications and optimize risk factors prior to surgical intervention. Comorbidities that portend a higher risk of perioperative MACE include coronary artery disease, heart failure, left-sided valvular heart disease, and significant arrhythmic burden. In this review, we provide a current approach to risk stratification prior to major vascular surgery and describe the strengths and weaknesses of different cardiac risk indices; discuss the role of noninvasive and invasive cardiac testing; and review perioperative pharmacotherapies.

Readmission Following Perioperative Myocardial Injury: Clinical Predictors and Impact on Mortality

Background. Perioperative myocardial injury (PMI) following noncardiac surgery is associated with a high risk for mortality, and readmission within 30 days of PMI increases this risk. Identifying risk factors for readmission among survivors of PMI is critical to improving outcomes in PMI. We examined risk factors for readmission following discharge after surgery complicated by PMI and the effect of readmission on 1-year mortality. Methods. The study is a retropective cohort analysis of patients diagnosed with PMI in a single health system over a 10-year period. Univariate predictors of readmission were used to construct a multivariable logistic regression model. Mortality was assessed using Kaplan–Meyer survival analysis. Results. Of the 207,729 surgical patients, 5159 (2.5%) had PMI. By 30 days following PMI, 1254 patients (24.3%) died, 1142 (22.2%) were readmitted but alive at 30 days, and 2763 patients (53.5%) were alive and had not been readmitted. Readmitted patients were older, had higher peak troponin levels, and were more likely to have prior coronary, neoplastic, lung, and kidney disease. Multivariable logistic regression revealed increasing age and peak troponin, prior cancer diagnosis, and chronic lung and kidney disease as independent predictors of readmission. Readmitted patients had higher 1-year mortality than those not readmitted (33.9% vs. 22.2%, $p<0.001$ ). Conclusions. Readmission following PMI is associated with increased mortality in the following year. Patients suffering from PMI who are at risk of readmission are older, have a greater extent of myocardial injury, and are more likely to have chronic comorbidities. Identification of patients at risk of readmission following PMI is critical to improving both outcomes and utilization of hospital resources.

Alcohol Abuse, Morbid Obesity, Depression, Congestive Heart Failure, and Chronic Pulmonary Disease are Risk Factors for 90-Day Readmission After Arthroscopic Rotator Cuff Repair

Purpose

The purpose of this study was to report the rate and causes of 90-day readmissions after arthroscopic rotator cuff repair.

Methods

A retrospective query from January 2005 to March 2014 was performed using a nationwide administrative claims registry. Patients and complications were identified using International Classification of Disease, Ninth Revision (ICD-9) and Current Procedural Terminology (CPT) codes. Patients who underwent arthroscopic rotator cuff repair (RCR) and were readmitted within 90 days after their index procedure were identified. Patients not readmitted represented controls. Patients readmitted were stratified into separate cohorts depending on the primary cause of readmission, which included cardiac, endocrine, hematological, infectious, gastrointestinal, musculoskeletal (MSK), neoplastic, neurological or psychiatric, pulmonary, and renal. Risk factors assessed were comorbidities comprising the Elixhauser-Comorbidity Index (ECI). Primary outcomes analyzed and compared included cause for readmission, patient demographics, risk factors, in-hospital length of stay (LOS), and costs. Pearson’s chi-square was used to compare patient demographics, and multivariate binomial logistic regression was used to calculate odds ratios (OR) on patient-related risk factors for 90-day readmissions.

Results

10,425 readmitted patients and 301,625 control patients were identified, representing a 90-day readmission rate of 3.5%. The causes of readmissions were primarily related to infectious diseases (15%), MSK (15%), and cardiac (14%) complications. The most common MSK readmissions were osteoarthrosis of the leg or shoulder (24.8%) and spinal spondylosis (8.4%). Multivariate binomial logistic regression analyses demonstrated patients with alcohol abuse (OR, 1.42; P < .0001), morbid obesity (OR, 1.38; P < .0001), depression (OR, 1.35; P < .0001), congestive heart failure (OR, 1.34; P < 0.0001), and chronic pulmonary disease (OR, 1.28; P < .0001) were at the greatest risk of readmissions after RCR.

Conclusions

Significant differences exist among patients readmitted, and those patients who do not require hospital readmission within 90 days following arthroscopic rotator cuff repairs. Readmissions are associated with significant patient comorbidities and were primarily related to medically based complications.

Level of Evidence

Level III, prognostic, retrospective cohort study.

Chest pain in patients recovering from noncardiac surgery: A retrospective analysis

STUDY OBJECTIVE

Chest pain is relatively common postoperatively. Myocardial infarction (MI) is one cause of chest pain after surgery, but chest pain also results from less severe conditions. Because of its potential severity, chest pain usually prompts the activation of Rapid Response Systems (RRS). While chest pain is a cardinal symptom of myocardial ischemia in the non-surgical setting, the significance and relevance of chest pain after noncardiac surgery remains unclear.

DESIGN

We conducted a retrospective analysis of noncardiac surgical inpatients for whom postoperative chest pain triggered our multidisciplinary RRS.

SETTING

Surgical wards at Cleveland Clinic, Cleveland, OH.

PATIENTS

Postsurgical patients after noncardiac surgery in whom the RSS system was activated for chest pain.

INTERVENTIONS

RRS specified interventions like ECG readings, troponin measurements, transfer to ICU.

MEASUREMENTS

Our primary outcome was MI. Secondary outcomes included the proportion of patients who had an ECG performed, troponin measurements, echocardiography, cardiac catheterization, and were admitted to the Intensive Care Unit (ICU).

MAIN RESULTS

5850 surgical patients experienced postoperative chest pain and triggered an RRS activation between 2009 and 2019. A total of 3110 patients had troponin T measured within 6 h after RRS activation, and 538 of them (17%) had elevated troponin, meeting the Fourth Universal Definition criteria for MI. Additionally, 2 patients had ST-segment elevation infarction (STEMI) without troponin measurement. Among the 540 patients with MI, only 19 (3.5%) were diagnosed with a STEMI by ECG, 388 (72%) had echocardiography, 43 patients (8%) had cardiac catheterization, 8 patients (1.5%) required emergent cardiac surgery, and 424 (79%) were admitted to an ICU.

CONCLUSION

Chest pain is a serious clinical sign, often indicating a postoperative myocardial infarction, and therefore should be taken seriously. Troponin screening should be routinely considered in postsurgical patients who report chest pain.

Myocardial Infarction Complications After Surgery in Vietnam: Estimates of Incremental Cost, Readmission Risk, and Length of Hospital Stay

Myocardial infarction is a considerable burden on public health. However, there is a lack of information about its economic impact on both the individual and national levels. This study aims to estimate the incremental cost, readmission risk, and length of hospital stay due to myocardial infarction as a post-operative complication. We used data from a standardized national system managed by the Vietnam Social Insurance database. The original sample size was 1,241,893 surgical patients who had undergone one of seven types of surgery. A propensity score matching method was applied to create a matched sample for cost analysis. A generalized linear model was used to estimate direct treatment costs, the length of stay, and the effect of the complication on the readmission of surgical patients. Myocardial infarction occurs most frequently after vascular surgery. Patients with a myocardial infarction complication were more likely to experience readmission within 30 and 90 days, with an OR of 3.45 (95%CI: 2.92–4.08) and 4.39 (95%CI: 3.78–5.10), respectively. The increments of total costs at 30 and 90 days due to post-operative myocardial infarction were 4,490.9 USD (95%CI: 3882.3–5099.5) and 4,724.6 USD (95%CI: 4111.5–5337.8) per case, while the increases in length of stay were 4.9 (95%CI: 3.6–6.2) and 5.7 (95%CI: 4.2–7.2) per case, respectively. Perioperative myocardial infarction contributes significantly to medical costs for the individual and the national economy. Patients with perioperative myocardial infarction are more likely to be readmitted and face a longer treatment duration.

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.

Trends in early postoperative major adverse cardiovascular and cerebrovascular events associated with bariatric surgery: an analysis of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program data registry

BACKGROUND

The population undergoing bariatric surgery (BaS) has many cardiovascular risk factors that can lead to significant perioperative cardiovascular morbidity.

OBJECTIVES

We aimed to examine trends in the incidence of major adverse cardiovascular and cerebrovascular events (MACCE) after BaS.

SETTING

Academic Hospital, United States METHODS: We performed a retrospective analysis of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) data registry for patients aged ≥18 years undergoing laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB) from 2015 to 2019. Data on demographics, co-morbidities, and type of procedure were collected. MACCE was defined as a composite variable including perioperative acute myocardial infarction (AMI), cardiac arrest requiring cardiopulmonary resuscitation, acute stroke, and all-cause mortality. We utilized the Cochrane-Armitage and Jonckheere-Terpstra tests to assess for significant trend changes throughout the years.

RESULTS

A total of 752,722 patients were included in our analysis (LSG = 73.2%, LRYGB = 26.8%). Postoperative MACCE occurred in 1058 patients (.14%), and was more frequent in patients undergoing LRYGB (.20%). The frequency of MACCE declined from .17% to .14% (P = .053), driven by a decline in the frequency of AMI (.04% to .02%, P = .002), cardiac arrest (.05% to .04%, P = .897), and all-cause death (.11% to .08%, P = .040), but with an increase in perioperative stroke (.01% to .02%, P = .057).

CONCLUSION

The overall risk of MACCE after BaS is .14% and has been declining in the last 5 years. This trend is likely multifactorial and further analysis is necessary to provide a detailed explanation.

Causes, risk factors, and costs associated with ninety-day readmissions following primary total hip arthroplasty for femoral neck fractures

INTRODUCTION

Risk factors associated with primary THA readmissions have not yet been thoroughly analyzed when stratified by underlying indication. Given that a majority of THAs are done electively in the context of osteoarthritis (OA), it remains to be explored whether or not THAs performed non-electively in the trauma setting have different readmission patterns. Therefore, the aims of this study were to identify: 1) causes of readmissions; 2) patient-related risk-factors for readmissions; and 3) costs associated with the reasons for readmissions.

MATERIALS AND METHODS

Patients who sustained a femoral neck fracture and underwent primary THA from 2005 to 2014 were identified. Those subsequently readmitted within 90-days following the procedure comprised the study cohort whereas those not readmitted served as the comparison cohort. Primary outcomes included identifying causes of readmissions, identifying patient-related risk-factors associated with readmissions and determining healthcare expenditures associated with the different readmission etiologies. A regression analysis was used to calculate the odds (OR) for readmissions. A p-value less than 0.01 was considered to be statistically significant.

RESULTS

The regression model demonstrated the greatest patient-related risk factors included: electrolyte and fluid disorders (OR: 1.80, p < 0.0001), morbid obesity (OR: 1.60, p < 0.0001), pathologic weight loss (OR: 1.58, p < 0.0001), congestive heart failure (OR: 1.41, p < 0.0001), were the leading risk factors for readmissions. Pulmonary-related causes ($42,357.71) of readmission were the leading driver of costs of care.

CONCLUSION

Orthopaedic surgeons should identify and optimize pre-operative management of patient-related risk factors that increase readmissions following primary THA for femoral neck fractures. Additionally, pulmonary-related causes of readmission lead to the highest costs of care.

LEVEL OF EVIDENCE

III.

Potentially modifiable risk factors for 30-day unplanned hospital readmission preventive intervention-A data mining and statistical analysis

Unplanned hospital readmissions have a high prevalence and substantial healthcare costs. Preventive intervention during hospitalization holds the potential for reducing readmission risk. However, it is challenging to develop individualized interventions during hospitalization because the causes of readmissions have not been clearly known and because patients are heterogeneous. This work aimed to identify potentially modifiable risk factors of readmission to help clinicians better plan and prioritize interventions for different patient subgroups during hospitalization. We performed the analysis of associations between the changes of potentially modifiable risk factors and the change of readmission status with association rule mining and statistical methods. Twenty-nine risk factors were identified from the association rules, and twenty-five of them were potentially modifiable. The association rules with potentially modifiable risk factors can be recommended to different patient subgroups to support the development of customized readmission preventive interventions.

Perioperative cardiovascular outcomes among older adults undergoing in-hospital noncardiac surgery

BACKGROUND

Older adults undergoing noncardiac surgery have a high risk of major adverse cardiovascular events (MACE). This study aims to estimate the magnitude of increased perioperative risk, and examine national trends in perioperative MACE following in-hospital noncardiac surgery in older adults compared to middle-aged adults.

DESIGN

Time-series analysis of retrospective longitudinal data.

SETTING

The United States Agency for Healthcare Research and Quality National Inpatient Sample (NIS).

PARTICIPANTS

Hospitalizations for major noncardiac surgery among adults age ≥45 years between January 2004 and December 2014.

MEASUREMENTS

Inpatient perioperative MACE was defined as a composite of in-hospital death, myocardial infarction (MI), and ischemic stroke. In hospital death was determined from the NIS discharge disposition. MI and ischemic stroke were defined by International Classification of Diseases, Ninth Revision codes.

RESULTS

Of an estimated 55,349,978 surgical hospitalizations, 26,423,039 (47.7%) were for adults age 45-64, 14,231,386 (25.7%) age 65-74, 10,621,029 (19.2%) age 75-84 years, and 4,074,523 (7.4%) age ≥85 years. MACE occurred in 1,601,022 surgical hospitalizations (2.9%). Adults 65-74 (2.8%; aOR 1.16, 95% CI 1.14-1.17), 75-84 years (4.5%; aOR 1.30, 95% CI 1.28-1.32), and ≥85 years (6.9%; aOR 1.55, 95% CI 1.52-1.57) had greater risk of MACE than those 45-64 years (1.7%). From 2004 to 2014, MACE declined among adults 65-74 (3.1-2.5%, p < 0.001), 75-85 years (4.9-3.9%, p < 0.001), and ≥85 years (7.7-6.1%, p < 0.001), but was unchanged for adults age 45-64. Declines in MACE were driven by decreased MI and mortality despite increased stroke.

CONCLUSION

Older adults accounted for half of hospitalizations, but experienced the majority of MACE. Older adults had greater adjusted odds of MACE than younger individuals. The proportion of perioperative MACE declined over time, despite increases in ischemic stroke. These data highlight risks of noncardiac surgery in older adults that warrant increased attention to improve perioperative outcomes.

Pre-operative anaemia and myocardial injury after noncardiac surgery: A retrospective study

BACKGROUND

Pre-operative anaemia is associated with adverse outcomes of noncardiac surgery, but its association with myocardial injury after noncardiac surgery (MINS) has not been fully investigated.

OBJECTIVE

The association between pre-operative anaemia and MINS.

DESIGN

A single-centre retrospective cohort study.

SETTING

Tertiary care referral centre.

PATIENTS

Patients with measured cardiac troponin (cTn) I levels after noncardiac surgery.

INTERVENTIONS

Patients were separated according to pre-operative anaemia (haemoglobin <13 g dl-1 in men and <12 g dl-1 in women). Anaemia was further stratified into mild and moderate-to-severe at a haemoglobin level threshold of 11 g dl-1.

MAIN OUTCOME MEASURES

The primary outcome was MINS, defined as a peak cTn I level more than 99th percentile of the upper reference limit within 30 postoperative days.

RESULTS

Data from a total of 35 170 patients were collected, including 22 062 (62.7%) patients in the normal group and 13 108 (37.3%) in the anaemia group. After propensity score matching, 11919 sets of patients were generated, and the incidence of MINS was significantly associated with anaemia [14.5 vs. 21.0%, odds ratio (OR) 1.57, 95% confidence interval (CI) 1.47 to 1.68, P < 0.001]. For the entire population, multivariable analysis showed a graded association between anaemia severity and MINS (OR 1.32, 95% CI 1.22 to 1.43, P < 0.001 for mild anaemia and OR 1.80, 95% CI 1.66 to 1.94, P < 0.001 for moderate-to-severe anaemia compared with the normal group) and a significantly higher incidence of MINS for moderate-to-severe anaemia than mild anaemia (18.6 vs. 28.6%, OR 1.37, 95% CI 1.25 to 1.50, P < 0.001). The estimated threshold for pre-operative haemoglobin associated with MINS was 12.2 g dl-1, with an area under the curve of 0.622.

CONCLUSIONS

Pre-operative anaemia was independently associated with MINS, suggesting that MINS may be related to the association between anaemia and postoperative mortality.

TRIAL REGISTRATION

SMC 2019-08-048.

Capturing rich person-centred discharge information: exploring the challenges in developing a new model

Purpose

Capture, consumption and use of person-centred information presents challenges for hospitals when operating within the scope of limited resources and the push for organisational routines and efficiencies. This paper explores these challenges for patients with Acute Coronary Syndrome (ACS) and the examination of information that supports successful hospital discharge. It aims to determine how the likelihood of readmission may be prevented through the capturing of rich, person-specific information during in-patient care to improve the process for discharge to home.

Design/methodology/approach

The authors combine four research data collection and analysis techniques: one, an analysis of the patient record; two, semi-structured longitudinal interviews; three, an analysis of the patient's journey using process mining to provide analytics about the discharge process, and four, a focus group with nurses to validate and confirm our findings.

Findings

The authors’ contribution is to show that information systems which support discharge need to consider models focused on individual patient stressors. The authors find that current discharge information capture does not provide the required person-centred information to support a successful discharge. Data indicate that rich, detailed information about the person acquired through additional nursing assessments are required to complement data provided about the patient's journey in order to support the patients’ post-discharge recovery at home.

Originality/value

Prior research has focused on information collection constrained by pre-determined limitations and barriers of system design. This work has not considered the information provided by multiple sources during the whole patient journey as a mechanism to reshape the discharge process to become more person-centred. Using a novel combination of research techniques and theory, the authors have shown that patient information collected through multiple channels across the patient care journey may significantly extend the quality of patient care beyond hospital discharge. Although not assessed in this study, rich, person-centred discharge information may also decrease the likelihood of patient readmission.

Dexmedetomidine attenuates myocardial ischemia-reperfusion injury in vitro by inhibiting NLRP3 Inflammasome activation

Background

Myocardial ischemia-reperfusion injury (MIRI) is the most common cause of death worldwide. The NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) inflammasome plays an important role in the inflammatory response to MIRI. Dexmedetomidine (DEX), a specific agonist of α2-adrenergic receptor, is commonly used for sedation and analgesia in anesthesia and critically ill patients. Several studies have shown that dexmedetomidine has a strong anti-inflammatory effect in many diseases. Here, we investigated whether dexmedetomidine protects against MIRI by inhibiting the activation of the NLRP3 inflammasome in vitro.

Methods

We established an MIRI model in cardiomyocytes (CMs) alone and in coculture with cardiac fibroblasts (CFs) by hypoxia/reoxygenation (H/R) in vitro. The cells were treated with dexmedetomidine with or without MCC950 (a potent selective NLRP3 inhibitor). The beating rate and cell viability of cardiomyocytes, NLRP3 localization, the expression of inflammatory cytokines and NLRP3 inflammasome-related proteins, and the expression of apoptosis-related proteins, including Bcl2 and BAX, were determined.

Results

Dexmedetomidine treatment increased the beating rates and viability of cardiomyocytes cocultured with cardiac fibroblasts. The expression of the NLRP3 protein was significantly upregulated in cardiac fibroblasts but not in cardiomyocytes after H/R and was significantly attenuated by dexmedetomidine treatment. Expression of the inflammatory cytokines IL-1β, IL-18 and TNF-α was significantly increased in cardiac fibroblasts after H/R and was attenuated by dexmedetomidine treatment. NLRP3 inflammasome activation induced the increased expression of cleaved caspase1, mature IL-1β and IL-18, while dexmedetomidine suppressed H/R-induced NLRP3 inflammasome activation in cardiac fibroblasts. In addition, dexmedetomidine reduced the expression of Bcl2 and BAX in cocultured cardiomyocytes by suppressing H/R-induced NLRP3 inflammasome activation in cardiac fibroblasts.

Conclusion

Dexmedetomidine treatment can suppress H/R-induced NLRP3 inflammasome activation in cardiac fibroblasts, thereby alleviating MIRI by inhibiting the inflammatory response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12871-021-01334-5.

Cardiovascular Risk Factors and Perioperative Myocardial Infarction After Noncardiac Surgery

BACKGROUND

Perioperative cardiovascular events are a leading cause of morbidity and mortality after noncardiac surgery. We propose a simplified method for perioperative risk stratification.

METHODS

In a retrospective cohort study we identified patients who underwent noncardiac surgery between 2009 and 2015 in the US National Surgical Quality Improvement Program. Multivariable logistic regression models adjusted for age, sex, race, and surgery type were generated to estimate the effect of traditional cardiovascular risk factors (hypertension, diabetes mellitus, current smoking) on odds of perioperative myocardial infarction (MI). Time to event analysis was conducted using competing risk analysis, with MI as the outcome event and death as the competing risk.

RESULTS

A total of 3,848,501 noncardiac surgeries were identified. Postoperative MI occurred in 0.37% of patients and 1.04% of patients died. The 30-day event rate of perioperative MI increased in a stepwise fashion with additional risk factors (0.42% for 1, 0.82% for 2, and 1.08% for 3; P for trend < 0.001) after accounting for the competing risk of death. Compared with those with no risk factors, patients with 1, 2, and 3 risk factors had increased odds of MI (adjusted odds ratio [aOR], 2.07 [95% confidence interval (CI), 1.96-2.19]; aOR, 3.63 [95% CI, 3.43-3.85]; and aOR, 5.54 [95% CI, 5.09-6.04], respectively). Perioperative MI was rare (0.10%) in patients without risk factors.

CONCLUSIONS

Patients with cardiovascular risk factors are at increased risk of perioperative MI, those without risk factors are at low risk. Further evaluation is needed to determine the effect of a simplified risk score in the perioperative setting.

Perioperative Myocardial Infarction/Myocardial Injury Is Associated with High Hospital Mortality in Elderly Patients Undergoing Hip Fracture Surgery

Cardiovascular complications in patients undergoing non-cardiac surgery are associated with longer hospital stays and higher in-hospital mortality. The aim of this study was to assess the incidence of in-hospital myocardial infarction and/or myocardial injury in patients undergoing hip fracture surgery and their association with mortality. Moreover, we evaluated the prognostic value of troponin increase stratified on the basis of peak troponin value. The electronic records of 1970 consecutive hip fracture patients were reviewed. Patients <70 years, those with myocardial infarction <30 days, and those with sepsis or active cancer were excluded from the study. Troponin and ECG were obtained at admission and then at 12, 24, and 48 h after surgery. Echocardiography was made before and within 48 h after surgery. Myocardial injury was defined by peak troponin I levels > 99th percentile. A total of 1854 patients were included. An elevated troponin concentration was observed in 754 (40.7%) patients in the study population. Evidence of myocardial ischemia, fulfilling diagnosis of myocardial infarction, was found in 433 (57%). ECG and echo abnormalities were more frequent in patients with higher troponin values; however, mortality did not differ between patients with and without evidence of ischemia. Peak troponin was between 0.1 and 1 µg/L in 593 (30.3%). A total of 191 (10%) had peak troponin I ≥ 1 µg/L, and 98 died in hospital (5%). Mortality was significantly higher in both groups with troponin increase (HR = 1.37, 95% CI 1.1–1.7, p < 0.001 for peak troponin I between 0.1 and 1 µg/L; HR = 2.28, 95% CI 1.72–3.02, p < 0.0001 for peak troponin ≥1 µg/L) in comparison to patients without myocardial injury. Male gender, history of coronary heart disease, heart failure, and chronic kidney disease were also associated with in-hospital mortality. Myocardial injury/infarction is associated with increased mortality after hip fracture surgery. Elevated troponin values, but not ischemic changes, are related to early worse outcome.

Morbidity and Mortality After Acute Myocardial Infarction After Elective Major Noncardiac Surgery

OBJECTIVES

To develop parsimonious models of in-hospital mortality and morbidity risk after perioperative acute myocardial infarction (AMI).

DESIGN

Retrospective data analysis.

SETTING

National Inpatient Sample (2008-2013), a 20% sample of all non-federal in-patient hospitalizations in the United States.

PARTICIPANTS

Patients 45 years or older who experienced perioperative AMI during elective admission for noncardiac surgery.

INTERVENTIONS

The study used a mixed principal components analysis and multivariate logistic regression to identify risk factors for in-hospital mortality after perioperative AMI. A model incorporating only preoperative risk factors, defined by the Revised Cardiac Risk Index (RCRI), was compared with a "full risk factor" model, incorporating a large set of preoperative AMI risk factors. The risk of post-AMI disposition to an intermediate care or skilled nursing facility, a marker of functional impairment, then was evaluated.

MEASUREMENTS AND MAIN RESULTS

In the present study, 15,574 cases of AMI after elective noncardiac surgery were identified (0.42%, corresponding with 78,122 cases nationally), with a 12.4% in-hospital mortality rate. The "RCRI-only" model was the best-fit model of post-AMI in-hospital mortality risk, without loss of predictive accuracy compared with the "full risk factor" model (area under the receiver operator characteristic curve 0.80, 95% confidence interval [CI] [0.77-0.82] v area under the receiver operator characteristic curve 0.81, 95% CI [0.77-0.83], respectively). Post-AMI mortality risk was the highest for perioperative complications, including sepsis (odds ratio 4.95, 95% CI [4.32-5.67]). Conversely, functional impairment was best predicted by the "full-risk factor" model and depended strongly on chronic preoperative comorbidities.

CONCLUSIONS

The RCRI provides a simple but adequate model of preoperative risk factors for in-hospital mortality after perioperative AMI.

Prior bariatric surgery and perioperative cardiovascular outcomes following noncardiac surgery in patients with type 2 diabetes mellitus: hint from National Inpatient Sample Database

Background

Both diabetes and obesity are risk factors for perioperative major adverse events. This study aims to evaluate the association between prior bariatric surgery (prior-BS) and perioperative cardiovascular outcomes following noncardiac surgery in patients with type 2 diabetes mellitus (T2DM).

Methods

We used the National Inpatient Sample Database to identify T2DM patients undergoing major noncardiac surgery from 2006 to 2014. The primary outcome was major perioperative adverse cardiovascular and cerebrovascular events (MACCEs), which include death, acute myocardial infarction and acute ischaemic stroke. In-hospital outcomes between patients with prior BS and morbid obesity were compared using unadjusted logistic, multivariable logistic and propensity score matching analyses.

Results

A weighted of 1,526,820 patients diagnosed with T2DM who underwent noncardiac surgery were included. The rates of both prior BS and morbid obesity significantly increased during the study period (P < 0.0001). Patients with prior BS were younger, were more likely to be female, and had lower rates of cardiovascular risk factors but had higher rates of smoking, alcohol abuse, anaemia, prior venous thromboembolism and prior percutaneous coronary intervention. The incidence of MACCEs was 1.01% and 3.25% in patients with prior BS and morbid obesity, respectively. After multivariable adjustment, we found that prior BS was associated with a reduced risk of MACCEs (odds ratio [OR] = 0.71; 95% confidence interval [CI] 0.62–0.81), death (OR = 0.64, 95% CI 0.52–0.78), acute kidney injury (OR = 0.66, 95% CI 0.62–0.70) and acute respiratory failure (OR: 0.46; 95% CI 0.42–0.50).

Conclusions

Prior bariatric surgery in T2DM patients undergoing noncardiac surgery is associated with a lower risk of MACCEs. Prospective studies are needed to verify the benefits of bariatric surgery in patients undergoing noncardiac surgery.

Risks of noncardiac surgery early after percutaneous coronary intervention

BACKGROUND

Prior registry data suggest that 4%-20% of patients require noncardiac surgery (NCS) within 2 years of percutaneous coronary intervention (PCI). Contemporary data on NCS after PCI in the United States among women and men are limited. We determined the rate of early hospital readmission for NCS and associated outcomes in a large cohort of patients who underwent PCI in the United States.

METHODS

Adults undergoing PCI between January 1 and June 30, 2014, were identified from the Nationwide Readmission Database. Patients readmitted for NCS within 6 months of PCI were identified. Outcomes of interest were in-hospital death, myocardial infarction (MI), and bleeding defined by International Classification of Diseases, Ninth Revision, codes.

RESULTS

Among 221,379 patients who underwent PCI and survived to hospital discharge, 3.5% (n = 7,696) were readmitted for NCS within 6 months post-PCI, and 41% of these hospitalizations were elective. Early NCS was complicated by MI in 4.7% of cases, and 21% of perioperative MIs were fatal. Bleeding was recorded in 32.0% of patients. All-cause mortality occurred in 4.4% of patients (n = 339) readmitted for surgery. The risk of death or MI was greatest when NCS was performed within the first month after PCI.

CONCLUSIONS

Despite clear guidelines to avoid surgery early after PCI, NCS was performed in 1 of every 29 patients with recent PCI, corresponding to as many as ~30,000 patients each year nationwide. Surgical mortality and perioperative MI were high in this setting. Strategies to minimize perioperative thrombotic and bleeding risks during readmission for NCS after PCI are necessary.

90-day Readmission in Elective Primary Lumbar Spine Surgery in the Inpatient Setting: A Nationwide Readmissions Database Sample Analysis

STUDY DESIGN

Secondary analysis of a large administrative database.

OBJECTIVE

The objectives of this study are to: 1) identify the incidence and cause of 90-day readmissions following primary elective lumbar spine surgery, 2) offer insight into potential risk factors that contribute to these readmissions, and 3) quantify the cost associated with these readmissions.

SUMMARY OF BACKGROUND DATA

As bundled-payment models for the reimbursement of surgical services become more popular in spine, the focus is shifting toward long-term patient outcomes in the context of 90-day episodes of care. With limited data available on national 90-day readmission statistics available, we hope to provide evidence that will aid in the development of more cost-effective perioperative care models.

METHODS

Using ICD-9 coding, we identified all patients 18 years of age and older in the 2014 Nationwide Readmissions Database (NRD) who underwent an elective, inpatient, primary lumbar spine surgery. Using multivariate logistic regression, we identified independent predictors of 90-day readmission while controlling for a multitude of confounding variables and completed a comparative cost analysis.

RESULTS

We identified 169,788 patients who underwent a primary lumbar spine procedure. In total 4268 (2.5%) were readmitted within 90 days. There was no difference in comorbidity burden between cohorts (readmitted vs. not readmitted) as quantified by the Elixhauser Comorbidity index. Independent predictors of increased odds of 90-day readmission were: anemia, uncomplicated diabetes and diabetes with chronic complications, surgical wound disruption and acute myocardial infarction at the time of the index admission, self-pay status, and an anterior surgical approach. Implant complications were identified as the primary related cause of readmission. These readmissions were associated with a significant cost increase.

CONCLUSION

There are clearly identifiable risk factors that increase the odds of hospital readmission within 90 days of primary lumbar spine surgery. An overall 90-day readmission rate of 2.5%, while relatively low, carries significantly increased cost to both the patient and hospital.

LEVEL OF EVIDENCE

3.

Development of a bariatric surgery specific risk assessment tool for perioperative myocardial infarction

BACKGROUND

Perioperative myocardial infarction (PMI) is a feared complication after surgery. Bariatric surgery, due to its intraabdominal nature, is traditionally considered an intermediate risk procedure. However, there are limited data on MI rates and its predictors in patients undergoing bariatric surgery.

OBJECTIVES

To enumerate the prevalence of PMI after bariatric surgery and develop a risk assessment tool.

SETTING

Bariatric surgery centers, United States.

METHODS

Patients undergoing bariatric surgery were identified from the MBSAQIP participant use file (PUF) 2016. Preoperative characteristics, which correlated with PMI were identified by multivariable regression analysis. PUF 2015 was used to validate the scoring tool developed from PUF 2016.

RESULTS

We identified 172,017 patients from PUF 2016. Event rate for MI within 30 days of the operation was .03%; with a mortality rate of 17.3% in patients with a PMI. Four variables correlated with PMI on regression, including history of a previous MI (odds ratio [OR] = 8.57, confidence interval [CI] = 3.4-21.0), preoperative renal insufficiency (OR = 3.83, CI = 1.2-11.4), hyperlipidemia (OR = 2.60, CI = 1.3-5.1), and age >50 (OR = 2.15, CI = 1.1-4.2). Each predicting variable was assigned a score and event rate for MI was assessed with increasing risk score in PUF 2015; the rate increased from 9.5 per 100,000 operations with a score of 0 to 3.2 per 100 with a score of 5.

CONCLUSION

The prevalence of MI after bariatric surgery is lower than other intraabdominal surgeries. However, mortality with PMI is high. This scoring tool can be used by bariatric surgeons to identify patients who will benefit from focused perioperative cardiac workup.

Cardiac vagal dysfunction and myocardial injury after non-cardiac surgery: a planned secondary analysis of the measurement of Exercise Tolerance before surgery study

Background

The aetiology of perioperative myocardial injury is poorly understood and not clearly linked to pre-existing cardiovascular disease. We hypothesised that loss of cardioprotective vagal tone [defined by impaired heart rate recovery ≤12 beats min⁻¹ (HRR ≤12) 1 min after cessation of preoperative cardiopulmonary exercise testing] was associated with perioperative myocardial injury.

Methods

We conducted a pre-defined, secondary analysis of a multi-centre prospective cohort study of preoperative cardiopulmonary exercise testing. Participants were aged ≥40 yr undergoing non-cardiac surgery. The exposure was impaired HRR (HRR≤12). The primary outcome was postoperative myocardial injury, defined by serum troponin concentration within 72 h after surgery. The analysis accounted for established markers of cardiac risk [Revised Cardiac Risk Index (RCRI), N-terminal pro-brain natriuretic peptide (NT pro-BNP)].

Results

A total of 1326 participants were included [mean age (standard deviation), 64 (10) yr], of whom 816 (61.5%) were male. HRR≤12 occurred in 548 patients (41.3%). Myocardial injury was more frequent amongst patients with HRR≤12 [85/548 (15.5%) vs HRR>12: 83/778 (10.7%); odds ratio (OR), 1.50 (1.08–2.08); P=0.016, adjusted for RCRI). HRR declined progressively in patients with increasing numbers of RCRI factors. Patients with ≥3 RCRI factors were more likely to have HRR≤12 [26/36 (72.2%) vs 0 factors: 167/419 (39.9%); OR, 3.92 (1.84–8.34); P<0.001]. NT pro-BNP greater than a standard prognostic threshold (>300 pg ml⁻¹) was more frequent in patients with HRR≤12 [96/529 (18.1%) vs HRR>12 59/745 (7.9%); OR, 2.58 (1.82–3.64); P<0.001].

Conclusions

Impaired HRR is associated with an increased risk of perioperative cardiac injury. These data suggest a mechanistic role for cardiac vagal dysfunction in promoting perioperative myocardial injury.

Predictors of Surgical Site Infection After Nonemergent Craniotomy: A Nationwide Readmission Database Analysis

OBJECTIVE

Surgical site infections (SSIs) carry significant patient morbidity and mortality and are a major source of readmissions after craniotomy. Because of their deleterious effects on health care outcomes and costs, identifying modifiable risk factors holds tremendous value. However, because SSIs after craniotomy are rare and most existing data comprise single-institution studies with small sample sizes, many are likely underpowered to discern for such factors. The objective of this study was to use a large hetereogenous patient sample to determine SSI incidence after nonemergent craniotomy and identify factors associated with readmission and subsequent need for wound washout.

METHODS

We used the 2010-2014 Nationwide Readmissions Database cohorts to discern for factors predictive of SSI and washout.

RESULTS

We identified 93,920 nonemergent craniotomies. There were 2079 cases of SSI (2.2%) and 835 reoperations for washout (0.89%) within 30 days of index admission and there were 2761 cases of SSI (3.6%) and 1220 reoperations for washout (1.58%) within 90 days. Several factors were predictive of SSI in multivariate analysis, including tumor operations, external ventricular drain (EVD), age, length of stay, diabetes, discharge to an intermediate-care facility, insurance type, and hospital bed size. Many of these factors were similarly implicated in reoperation for washout.

CONCLUSIONS

SSI incidence in neurosurgery is low and most readmissions occur within 30 days. Several factors predicted SSI after craniotomy, including operations for tumor, younger age, hospitalization length, diabetes, discharge to institutional care, larger hospital bed size, Medicaid insurance, and presence of an EVD. Diabetes and EVD placement may represent modifiable factors that could be explored in subsequent prospective studies for their associations with cranial SSIs.