Noncardiac Patients Research Articles

Effect of different durations of preoperative computerised cognitive training on postoperative delirium in older patients undergoing cardiac surgery: a study protocol for a prospective, randomised controlled trial

IntroductionPostoperative delirium (POD) is a common neurological complication after surgery among older patients, characterised by acute disturbances in consciousness, attention and cognition, usually occurring within 24–72 hours after surgery. POD...

Abstract 4118341: Outcomes of Heart Failure with Preserved Ejection Fraction Patients With Concurrent Opioid Use: Insights From the National Inpatient Sample

Background: Opioid use has increased significantly in the past few decades, impacting cardiac and non-cardiac patients. As heart failure with preserved ejection fraction (HFpEF) comprises half of all heart failure cases, understanding its management and effect on outcomes is crucial. This study aims to evaluate the outcomes of chronic opioid therapy on HFpEF patients. Methods: Studying the National Inpatient Sample (2016-2020), we identified adult HFpEF patients using the appropriate ICD-10 codes -after excluding patients with end-stage renal disease (ESRD)- and compared outcomes between chronic opioid users and non-users. Multivariate logistic and linear regression analyses were performed, adjusting for multiple patient and hospital confounders. The primary outcome was all-cause in-hospital mortality while secondary outcomes included acute kidney injury/hemodialysis (AKI/HD), cardiogenic shock, cardiac arrest, mechanical ventilation, length of stay, and total charges. Results: Among 1,557,344 HFpEF patients, 21,655 (1.4%) were on opioids chronically. Inpatient mortality was not significantly different between patients who were on opioids and those who were not. (adjusted odds ratio [aOR] 1.01, 95% CI 0.85 - 1.2, p=0.89). There was a non-significant increased risk of cardiogenic shock (aOR 1.14, 95% CI 0.87 - 1.5, p=0.35) and cardiac arrest (aOR 1.05, 95% CI 0.8 - 1.36, p=0.74) in patients on chronic opioids. Chronic opioids were associated with increased risk of AKI/HD (aOR 1.12, 95% CI 1.04 - 1.2, p=0.002) and mechanical ventilation (aOR 1.29, 95% CI 1.16 - 1.43, p< 0.001). Opioid use was also associated with longer hospital stay (adjusted MD [aMD] 1.07 days, 95% CI 0.75 - 1.39, p<0.001) and a non-significant increase in total charges (aMD $2,593, 95% CI -$2,044 - $7,229, p=0.27). Conclusions: While chronic opioid use in hospitalized HFpEF patients did not significantly impact in-hospital mortality, it was associated with increased risk of other adverse events and longer hospital stay. Further research is needed to understand the impact of chronic opioid use on HFpEF patients.

Long-term risk of heart failure in patients with postoperative atrial fibrillation following non-cardiac surgery: Insights from a nationwide cohort.

Atrial fibrillation (AF) is associated with heart failure (HF). However, it is unclear if postoperative AF (POAF) following non-cardiac surgery differs from non-surgical AF in terms of the risk of HF. We compared the long-term rate of incident HF in patients developing new-onset POAF following non-cardiac surgery with patients who did not develop POAF following non-cardiac surgery and patients with non-surgical non-valvular AF (NVAF). Using Danish nationwide registries, all patients aged ≥30 years who developed POAF following non-cardiac surgery (1996-2020) were identified and matched in a 1:3 ratio by age, sex, surgery type (only for the surgery group), selected comorbidities, and inclusion year with patients without POAF following non-cardiac surgery and individuals with NVAF, respectively. A total of 2270 patients with POAF were matched with 6810 patients without POAF following non-cardiac surgery, and 1846 patients with POAF were matched with 5538 patients with NVAF. The median follow-up was 7.2 years. Compared with patients without POAF, those with POAF had a higher associated long-term rate of incident HF (2.6 vs. 1.2 events per 100 person-years; adjusted hazard ratio [HR] 2.39, 95% confidence interval [CI] 2.06-2.78). Compared with individuals with NVAF, patients with POAF did not have a significantly different rate of incident HF (2.7 vs. 3.0 events per 100 person-years; adjusted HR 0.89, 95% CI 0.78-1.03). Patients with new-onset POAF following non-cardiac surgery had a higher associated long-term rate of incident HF compared to those without POAF, with no significant difference in the rate of incident HF when compared to patients with NVAF.

Boston Naming Test as a Screening Tool for Early Postoperative Cognitive Dysfunction in Elderly Patients After Major Noncardiac Surgery.

The Boston naming test (BNT), as a simple, fast, and easily administered neuropsychological test, was demonstrated to be useful in detecting language function. In this study, BNT was investigated whether it could be a screening tool for early postoperative cognitive dysfunction (POCD). This prospective observational cohort study included 132 major noncardiac surgery patients and 81 nonsurgical controls. All participants underwent a mini-mental state examination (MMSE) and BNT 1 day before and 7 days after surgery. Early POCD was assessed by reliable change index and control group results. Seven days after surgery, among 132 patients, POCD was detected in 30 (22.7%) patients (95% CI, 15.5%-30.0%) based on MMSE, and 45 (34.1%) patients (95% CI, 26.3%-41.9%) were found with postoperative language function decline based on BNT and MMSE. Agreement between the BNT spontaneous naming and MMSE total scoring was moderate (Kappa .523), and the sensitivity of BNT spontaneous naming for detecting early POCD was .767. Further analysis showed that areas under receiver operating characteristics curves (AUC) did not show statistically significant differences when BNT spontaneous naming (AUC .862) was compared with MMSE language functional subtests (AUC .889), or non-language functional subtests (AUC .933). This study indicates the feasibility of implementing the BNT spontaneous naming test to screen early POCD in elderly patients after major noncardiac surgery.

Relationship between sST2 and NT-proBNP levels and postoperative atrial fibrillation in patients having non-cardiac surgery.

We explored the link between sST2 and NT-proBNP levels and postoperative atrial fibrillation (POAF) incidence in non-cardiac surgery patients in this study. The research involved 302 participants over 40 years old who underwent medium and/or high-risk non-cardiac surgeries. These patients were divided into two groups: those who developed POAF and those who did not. The study cohort consisted of a total of 302 patients, with 14 (4.6%) experiencing POAF. POAF was more common in patients with previous heart failure, a high Left Atrial Volume Index (LAVI), and elevated ASA and RCRI scores (all P<0.05). LAVI, sST2, NT-proBNP, and RCRI scores were found to be independent predictors of POAF in patients undergoing non-cardiac surgeries (all P<0.05). The area under the curve (AUC) for sST2 and NT-proBNP in predicting POAF was 0.707 (95% CI 0.544-0.869; P=0.009) and 0.727 (95% CI 0.598-0.857; P=0.004), respectively. Combined elevation of sST2 and NT-proBNP increased the likelihood of developing POAF by approximately 8.5 times (OR: 8.65, CI 95% 1.06-35.3, P=0.044). sST2 and NT-proBNP are valuable predictors of POAF in patients undergoing non-cardiac surgery. Identifying these predictors can help in recognizing high-risk patient groups for POAF.

An interrater reliability analysis of preoperative mortality risk calculators used for elective high-risk noncardiac surgical patients shows poor to moderate reliability

BackgroundMultiple preoperative calculators are available online to predict preoperative mortality risk for noncardiac surgical patients. However, it is currently unknown how these risk calculators perform across different raters. The current study investigated the interrater reliability of three preoperative mortality risk calculators in an elective high-risk noncardiac surgical patient population to evaluate if these calculators can be safely used for identification of high-risk noncardiac surgical patients for a preoperative multidisciplinary team discussion.MethodsFive anesthesiologists assessed the preoperative mortality risk of 34 high-risk patients using the preoperative score to calculate postoperative mortality risks (POSPOM), the American College of Surgeons surgical risk calculator (SRC), and the surgical outcome risk tool (SORT). In total, 170 calculations per calculator were gathered.ResultsInterrater reliability was poor for SORT (ICC (C.I. 95%) = 0.46 (0.30–0.63)) and moderate for SRC (ICC = 0.65 (0.51–0.78)) and POSPOM (ICC = 0.63 (0.49–0.77). The absolute range of calculated mortality risk was 0.2–72% for POSPOM, 0–36% for SRC, and 0.4–17% for SORT. The coefficient of variation increased in higher risk classes for POSPOM and SORT. The extended Bland–Altman limits of agreement suggested that all raters contributed to the variation in calculated risks.ConclusionThe current results indicate that the preoperative risk calculators POSPOM, SRC, and SORT exhibit poor to moderate interrater reliability. These calculators are not sufficiently accurate for clinical identification and preoperative counseling of high-risk surgical patients. Clinicians should be trained in using mortality risk calculators. Also, clinicians should be cautious when using predicted mortality estimates from these calculators to identify high-risk noncardiac surgical patients for elective surgery.

Concomitant cardiac arrest on cardiogenic shock patients. Differences in clinical profile and outcomes with non-cardiac arrest patients. The Shock CAT Study

Abstract Background Mortality on cardiogenic shock (CS) remains undesirable, although CS patients with or without concomitant CA may have different prognoses and clinical profile. Purpose The aim is to analyse differences in clinical profile, management, in-hospital prognosis and mid-term mortality in CS patients with and without cardiac arrest on admission in a Mediterranean cohort. Method Shock CAT study was a multicentre, prospective, observational study conducted between December 2018 and December 2019 in eight public University hospitals in Catalonia (Spain), including CS patients of different aetiologies. Data on clinical presentation, biomarkers, management, including mechanical cardiac/circulatory support (MCS), in-hospital and 6 months mortality were analysed comparing patients with and without CA at admission. Results A total of 382 CS patients (p) were included: CA 34.8% (n=133 p) and non-CA 65.2% (n=249 p). CA patients were younger than non-CA (61.9 vs 67.4 years, p&amp;lt;0.001) with higher prevalence of men (82% vs 71.8%, p= 0.024). Acute coronary syndrome was the main CS cause (60.7%) and ST elevation myocardial infarction (STEMI) was higher in CA patients than non-CA (55.6% vs 42.6%, p&amp;lt;0.001). In CA group, time to recover of spontaneous circulation was 24 min (IQR: 14-40 min) and hypothermia was performed in 55% of cases. CA patients had less prevalence of cardiovascular risk factors (hypertension, diabetes and dyslipidaemia) and lower pH at admission (7.19 vs 7.31, p&amp;lt;0.001) and higher lactate peak (6.9 vs 5.0, p=0.001) than non-CA patients. MCS was implanted in 35.3% of all CS patients, with lower use in CA patients (23.3% vs 41.8%, p&amp;lt;0.001), mainly due to lower intraaortic balloon pump (19.5% vs 35.5%, p=0.001), without differences in the use of extracorporeal membrane oxygenation (ECMO) (11.4% vs 8.7%, p=0.40) or Impella (10.6% vs 12.8%. p=0.54). Cardshock score was higher in CA patients than non-CA (4.68 vs 4.2, p=0.038), without differences in IABP score (2.31 vs 2.20, p= 0.621) or SCAI D/E (42.1% vs 33.3%, p= 0.090). In-hospital mortality was higher in CA patients (42.9% vs 27.7%, p=0&amp;lt;0.001). Moreover, 6-months mortality remains higher in CA than non-CA patients, although without statistical significance (47.7% vs 38.3%, p=0.079). Conclusions In a Mediterranean CS cohort, concomitant CA patients were younger, with higher prevalence in men with STEMI. MCS had a lower used in CA patients, although without differences in ECMO or Impella. In-hospital mortality was 35% higher in CA patients than non-CA, although 6-months mortality only trend to be higher in CA group.

Defining Postinduction Hemodynamic Instability With an Automated Classification Model.

Postinduction hypotension (PIH) may be associated with increased morbidity and mortality. In earlier studies, the definition of PIH is solely based on different absolute or relative thresholds. However, the time-course (eg, how fast blood pressure drops during induction) is rarely incorporated, whereas it might represent the hemodynamic instability of a patient. We propose a comprehensive model to distinguish hemodynamically unstable from stable patients by combining blood pressure thresholds with the magnitude and speed of decline. This prospective study included 375 adult elective noncardiac surgery patients. Noninvasive blood pressure was continuously measured between 5 minutes before up to 15 minutes after the first induction agent had been administered. An expert panel rated whether the patient experienced clinically relevant hemodynamic instability or not. Interrater correlation coefficient and intraclass correlation were computed to check for consistency between experts. Next, an automated classification model for clinically relevant hemodynamic instability was developed using mean, maximum, minimum systolic, mean, diastolic arterial blood pressure (SAP, MAP, and DAP, respectively) and their corresponding time course of decline. The model was trained and tested based on the hemodynamic instability labels provided by the experts. In total 78 patients were classified as having experienced hemodynamic instability and 279 as not. The hemodynamically unstable patients were significantly older (7 years, 95% confidence interval (CI), 4-11, P < .001), with a higher prevalence of chronic obstructive pulmonary disease (COPD) (3% higher, 95% CI, 1-8, P = .036). Before induction, hemodynamically unstable patients had a higher SAP (median (first-third quartile): 161 (145-175) mm Hg vs 150 (134-166) mm Hg, P < .001) compared to hemodynamic stable patients. Interrater agreement between experts was 0.92 (95% CI, 0.89-0.94). The random forest classifier model showed excellent performance with an area under the receiver operating curve (AUROC) of 0.96, a sensitivity of 0.84, and specificity of 0.94. Based on the high sensitivity and specificity, the developed model is able to differentiate between clinically relevant hemodynamic instability and hemodynamic stable patients. This classification model will pave the way for future research concerning hemodynamic instability and its prevention.

A comparison between invasive and noninvasive measurement of the Hypotension Prediction Index: A post hoc analysis of a prospective cohort study.

Clinical trials and validation studies demonstrate promising hypotension prediction capability by the Hypotension Prediction Index (HPI). Most studies that evaluate HPI derive it from invasive blood pressure readings, but a direct comparison with the noninvasive alternative remains undetermined. Such a comparison could provide valuable insights for clinicians in deciding between invasive and noninvasive monitoring strategies. Evaluating predictive differences between HPI when obtained through noninvasive versus invasive blood pressure monitoring. Post hoc analysis of a prospective observational study conducted between 2018 and 2020. Single-centre study conducted in an academic hospital in the Netherlands. Adult noncardiac surgery patients scheduled for over 2 h long elective procedures. After obtaining informed consent, 91 out of the 105 patients had sufficient data for analysis. The primary outcome was the difference in area under the receiver-operating characteristics (ROC) curve (AUC) obtained for HPI predictions between the two datasets. Additionally, difference in time-to-event estimations were calculated. AUC (95% confidence interval (CI)) results revealed a nonsignificant difference between invasive and noninvasive HPI, with areas of 94.2% (90.5 to 96.8) and 95.3% (90.4 to 98.2), respectively with an estimated difference of 1.1 (-3.9 to 6.1)%; P = 0.673. However, noninvasive HPI demonstrated significantly longer time-to-event estimations for higher HPI values. Noninvasive HPI is reliably accessible to clinicians during noncardiac surgery, showing comparable accuracy in HPI probabilities and the potential for additional response time. Clinicaltrials.gov (NCT03795831) on 10 January 2019. https://clinicaltrials.gov/study/NCT03795831.

Elevated Cardiac Troponin Levels as a Predictor of Increased Mortality Risk in Non-Cardiac Critically Ill Patients Admitted to a Medical Intensive Care Unit.

Background: Cardiac troponin I (TnI) is a specific marker of myocardial damage used in the diagnosis of acute coronary syndrome (ACS). TnI levels can also be elevated in patients without ACS, which is linked to a worse prognosis and mortality. We evaluated the clinical implications and prognostic significance of serum TnI levels in critically ill non-cardiac patients admitted to the intensive care unit (ICU) at a tertiary-level hospital. Materials and Methods: A three-year retrospective study including the years 2017-2020 was conducted to evaluate in-hospital mortality during ICU stay and mortality rates at 28 and 90 days, as well as one and two years after admission, in 557 patients admitted to the medical ICU for non-cardiac causes. Results: TnI levels were elevated in 206 (36.9%) patients. Patients with elevated TnI levels were significantly older and had higher rates of comorbidities, including chronic heart failure, coronary heart disease, and chronic kidney disease (p < 0.05 for all). Patients with elevated TnI levels required more invasive mechanical ventilation, vasopressor infusion, and dialysis in the ICU and experienced more shock within the first 72 h (p = 0.001 for all). High TnI levels were associated with higher Acute Physiological and Chronic Health Evaluation (APACHE) II (27.6 vs. 20.3, p = 0.001) and Sequential Organ Failure assessment (8.8 vs. 5.26, p = 0.001) scores. Elevated TnI levels were associated with higher mortality rates at 28 days (58.3% vs. 19.4%), 90 days (69.9% vs. 35.0%), one year (78.6% vs. 46.2%), and two years (82.5% vs. 55.6%) (p < 0.001 for all). Univariate logistic regression analysis revealed that high TnI levels were a strong independent predictor of mortality at all time points: 28 days (OR = 1.2, 95% CI: 1.108-1.3, p < 0.001), 90 days (OR = 1.207, 95% CI: 1.095-1.33, p = 0.001), one year (OR = 1.164, 95% CI: 1.059-1.28, p = 0.002), and two year (OR = 1.119, 95% CI: 1.026-1.22, p = 0.011). Multivariate analysis revealed that age, albumin level, APACHE II score, and requirements for dialysis and vasopressor use in the ICU were important predictors of mortality across all timeframes, but elevated TnI levels were not. Conclusions: Elevated TnI levels in critically ill non-cardiac patients are markers of disease severity. While elevated TnI levels were significant predictors of mortality in the univariate analysis, they lost significance in the multivariate model when adjusted for other factors. Patients with elevated TnI levels had higher mortality rates across all timeframes, from 28 days to two years.

Association of preoperative red blood cell width and postoperative 30-day mortality in patients undergoing non-cardiac surgery: a retrospective cohort study using propensity-score matching

BackgroundIn terms of predicting surgery mortality, it is controversial whether red blood cell width works independently. In non-cardiac surgery patients older than 18 years, we intend to examine the relationship between red blood cell width and postoperative 30-day mortality.MethodsIn this retrospective cohort study, 90,785 Singapore General Hospital patients were matched by propensity score between January 1, 2012 and October 31, 2016. It was determined that red blood cell width at baseline and mortality within 30 days after surgery were the independent and dependent variables. We used a non-parametric multivariate logistic regression to balance the confounders among 7807 patients with high RDW and 7807 patients with non-high RDW in the propensity score matching. We investigated the association between RDW and 30-day mortality after surgery using the doubly robust estimation method.ResultsCohorts matched according to propensity score, the risk of 30-day mortality after surgery increased by 114.6.0% among the high RDW group (OR = 2.146, 95% CI 1.645–2.799, P < 0.00001). In the crude model, there was a significant association between RDW and 30-day mortality after surgery (OR = 1.877, 95% CI 1.476–2.388, P < 0.00001). In the propensity-score adjusted model, the risk of 30-day mortality after surgery in the high RDW group compared to the control group was not as high as in the non-adjusted model (OR = 1.867, 95% CI 1.467–2.376, P < 0.00001). Compared to non-high RDW group, the risk of 30-day mortality after surgery increased by 117.0% and 127.7% among high RDW group in the original cohort (OR 2.170, 95% CI 1.754–2.683, P < 0.00001) and the weighted cohort (OR 2.272, 95% CI 2.009–2.580, P < 0.00001), respectively.ConclusionsAccording to the results of this observational, propensity score-matched cohort study, uncontrolled high RDW before surgery is associated with an increased risk of death within 30 days after surgery, that is to say, patients over the age of 18 with high preoperative RDW who undergo non-cardiac surgery have a worse postoperative prognosis than those with normal RDW.

Optimizing anesthesia management based on early identification of electroencephalogram burst suppression risk in non-cardiac surgery patients: a visualized dynamic nomogram

Background Burst suppression (BS) is a specific electroencephalogram (EEG) pattern that may contribute to postoperative delirium and negative outcomes. Few prediction models of BS are available and some factors such as frailty and intraoperative hypotension (IOH) which have been reported to promote the occurrence of BS were not included. Therefore, we look forward to creating a straightforward, precise, and clinically useful prediction model by incorporating new factors, such as frailty and IOH. Materials and methods We retrospectively collected 540 patients and analyzed the data from 418 patients. Univariate analysis and backward stepwise logistic regression were used to select risk factors to develop a dynamic nomogram model, and then we developed a web calculator to visualize the process of prediction. The performance of the nomogram was evaluated in terms of discrimination, calibration, and clinical utility. Results According to the receiver operating characteristic (ROC) analysis, the nomogram showed good discriminative ability (AUC = 0.933) and the Hosmer–Lemeshow goodness-of-fit test demonstrated the nomogram had good calibration (p = 0.0718). Age, Clinical Frailty Scale (CFS) score, midazolam dose, propofol induction dose, total area under the hypotensive threshold of mean arterial pressure (MAP_AUT), and cerebrovascular diseases were the independent risk predictors of BS and used to construct nomogram. The web-based dynamic nomogram calculator was accessible by clicking on the URL: https://eegbsnomogram.shinyapps.io/dynnomapp/ or scanning a converted Quick Response (QR) code. Conclusions Incorporating two distinctive new risk factors, frailty and IOH, we firstly developed a visualized nomogram for accurately predicting BS in non-cardiac surgery patients. The model is expected to guide clinical decision-making and optimize anesthesia management.

The Impact of Frailty and Gender Differences on Hospitalization and Complications in Proximal Femoral Pathological Fractures: A Cross-Sectional Study.

Frailty associated with aging increases the risk of falls, disability, and death. The aim of this study is to explore gender-related disparities in the survival outcomes of pathological femoral fractures in older frail patients, while analyzing potential specific prognostic factors. This study is a retrospective observational analysis conducted at a single medical center. It enrolled all patients aged 65 and above who were admitted to our emergency department between 2016 and 2020 with a diagnosis of pathological femur fracture requiring surgical intervention. The primary study endpoint was evaluating gender-related differences in survival outcomes. The secondary endpoint involves investigating gender-specific prognostic factors through the analysis of clinical and laboratory parameters. The average Charlson Comorbidity Index (CCI) was slightly lower in men, but the difference was not statistically significant (p = 0.53). The Clinical Frailty Scale (CFS) showed similar results, with men and women 5.23 (SD 1.46), also not significant (p = 0.83). An evaluation comparing patients aged 75 years or younger to those older than 75 years found significant differences in health metrics. The average CCI was higher in the over 75 group compared to the under 75 group, with a p-value of 0.001. Similarly, the CFS average was also greater in the over 75 group than in the under 75 group, with a p-value of 0.0001. Complications were more frequent in patients over 75 and those with lower educational qualifications. The evaluation analyzed cardiac patients compared to a control group, revealing that the average age of cardiac patients was 75.22 years, while the control group was younger at 73.98 years (p = 0.5119). The CCI for cardiac patients averaged 6.53, significantly higher than 4.43 for non-cardiac patients (p = 0.0003). Frailty assessment is therefore essential in patients with pathological fracture of the proximal femur and is an important predictor of both gender differences and hospital complications. Enhancing gender analysis in this field is crucial to gather more robust evidence and deeper comprehension of potential sex- and gender-based disparities.

Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.

Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive arterial blood pressure monitors. This study tested whether routine non-invasive monitors could also predict intraoperative hypotension using deep learning algorithms. An open-source database of non-cardiac surgery patients ( https://vitadb.net/dataset ) was used to develop the deep learning algorithm. The algorithm was validated using external data obtained from a tertiary Korean hospital. Intraoperative hypotension was defined as a systolic blood pressure less than 90 mmHg. The input data included five monitors: non-invasive blood pressure, electrocardiography, photoplethysmography, capnography, and bispectral index. The primary outcome was the performance of the deep learning model as assessed by the area under the receiver operating characteristic curve (AUROC). Data from 4754 and 421 patients were used for algorithm development and external validation, respectively. The fully connected model of Multi-head Attention architecture and the Globally Attentive Locally Recurrent model with Focal Loss function were able to predict intraoperative hypotension 5min before its occurrence. The AUROC of the algorithm was 0.917 (95% confidence interval [CI], 0.915-0.918) for the original data and 0.833 (95% CI, 0.830-0.836) for the external validation data. Attention map, which quantified the contributions of each monitor, showed that our algorithm utilized data from each monitor with weights ranging from 8 to 22% for determining hypotension. A deep learning model utilizing multi-channel non-invasive monitors could predict intraoperative hypotension with high accuracy. Future prospective studies are needed to determine whether this model can assist clinicians in preventing hypotension in patients undergoing surgery with non-invasive monitoring.

Intraoperative clinical application of hemodynamic monitoring in noncardiac surgery patients

The current S1guidelines on the intraoperative clinical application of hemodynamic monitoring in patients scheduled for noncardiac surgery are presented based on a case report under the aspect of an optimized intraoperative anesthesiological management. The S1 guidelines were developed with the aim of identifying the questions on the intraoperative hemodynamic monitoring and management which are important for the routine daily clinical practice, to discuss them in a guideline group and to answer them based on the current state of scientific knowledge. The guidelines were written under the auspices of the German Society of Anesthesiology and Intensive Care Medicine (DGAI) and published by the AWMF in 2023 under the register number 001/049.

High body mass index is associated with elevated risk of perioperative ischemic stroke in patients who underwent noncardiac surgery: A retrospective cohort study.

Body mass index (BMI) serves as a global metric for assessing obesity and overall health status. However, the impact of BMI, treated as a continuous variable, on the risk of perioperative stroke remains poorly understood. This retrospective cohort study aimed to elucidate the association between BMI and the risk of perioperative ischemic stroke in patients undergoing non-cardiovascular surgery. A cohort of 223,415 patients undergoing noncardiac surgery at the First Medical Center of Chinese PLA General Hospital between January 1, 2008 and August 31, 2019 was screened. Preoperative high BMI, defined as BMI >22.64 kg/m2, was the primary exposure, and the outcome of interest was the new diagnosis of perioperative ischemic stroke within 30 days post-surgery. Robust controls for patient and intraoperative factors were implemented to minimize residual confounding. Logistic regression and propensity score matching were employed, and patients were stratified into subgroups for further investigation. The overall incidence of perioperative ischemic stroke was 0.23% (n = 525) in the cohort. After adjusting for patient-related variables (OR 1.283; 95% CI, 1.04-1.594; p < 0.05), surgery-related variables (OR 1.484; 95% CI, 1.2-1.849; p < 0.001), and all confounding variables (OR 1.279; 95% CI, 1.025-1.607; p < 0.05), patients with BMI >22.64 kg/m2 exhibited a significantly increased risk of perioperative ischemic stroke. This association persisted in the propensity score matched cohort (OR 1.577; 95% CI, 1.203-2.073; p < 0.01). Subgroup analyses indicated that preoperative BMI >22.64 kg/m2 correlated with an elevated risk of perioperative ischemic stroke in female patients, those with coronary heart disease, peripheral vascular diseases, and individuals undergoing neurosurgery. We first identified BMI >22.64 kg/m2 as a substantial and independent risk factor for perioperative ischemic stroke in Chinese noncardiac surgery patients. Normal BMI may not suffice as a universal preventive standard. Instead, a more stringent perioperative weight management approach is recommended, particularly for specific subgroups such as female patients, those with coronary heart disease and peripheral vascular disease, and individuals scheduled for neurosurgery.

Effect of home-based prehabilitation on objectively measured physical activity in patients undergoing elective major cardiac and non-cardiac surgery. Data from a randomized controlled trial

Abstract Background Low functional capacity in patients undergoing major elective surgery is associated with postoperative complications. Prehabilitation aims to increase functional capacity by increasing preoperative physical activity. Low functional capacity in patients eligible for major surgery is associated with high age and comorbid burden. In this population, center-based prehabilitation is a barrier for participation. Therefore, we developed a multimodal home-based prehabilitation intervention. Data regarding the effectiveness of a home-based prehabilitation intervention to increase physical activity before surgery is limited. We hypothesize that home-based prehabilitation leads to an increase in physical activity in patients undergoing major cardiac and non-cardiac surgery. Methods We included patients aged over 65 with a proven low functional capacity and/or ventilatory efficiency measured by preoperative cardiopulmonary exercise testing. Patients were randomized to either standard of care or intervention. The intervention group received a home-based prehabilitation intervention 2-4 weeks before surgery. As part of the multimodal intervention, patients were prescribed a walking regimen according to the physical activity guidelines published by the World Health Organization (WHO). Patients were followed-up with weekly telephone calls by a physiotherapist to increase adherence and motivation. All patients were provided a wrist-worn tri-axial accelerometer at the baseline visit. The accelerometer was collected at the ward once the patient entered the hospital for surgery. Physical activity was estimated by calculating the average Euclidean norm minus one (ENMO, milligravity [mg]) per day. Baseline characteristics were tested by Wilcoxon rank-sum test and a linear model for the primary outcome was performed to adjust for confounders. Data analysis was performed using R Studio. Results 37 patients scheduled for cardiac and 62 for non-cardiac surgery were included (Table 1). Mean group difference of daily physical activity levels in non-cardiac surgery patients was 3.01 mg (p = 0.03, 95% CI [0.3, 5.6]). Mean group difference of daily physical activity levels in cardiac surgery patients was 0.27 mg (p = 0.95, 95% CI [-4.1, 5.0]) (Figure 1). Patients undergoing cardiac surgery had higher overall activity levels compared to non-cardiac also when adjusted for age. Conclusion Home-based prehabilitation increases preoperative physical activity levels in patients undergoing major non-cardiac surgery, but not in patients undergoing major cardiac surgery. Higher activity levels in cardiac surgery patients was unexpected, but may be explained by previous inclusion of patients with cardiac diseases in exercise-based rehabilitation and physical activity recommendations at routine cardiac follow-up visits. Table 1 Figure 1

Association between Complications and Death within 30 days after General Surgery

Objective: To determine the epidemiology of post-operative complications among general surgery patients, inform their relationships with 30-day mortality, and determine the attributable fraction of death of each postoperative complication. Background: The contemporary causes of post-operative mortality among general surgery patients are not well characterized. Methods: VISION is a prospective cohort study of adult non-cardiac surgery patients across 28 centres in 14 countries, who were followed for 30 days after surgery. For the subset of general surgery patients, a cox proportional hazards model was used to determine associations between various surgical complications and post-operative mortality. The analyses were adjusted for preoperative and surgical variables. Results were reported in adjusted hazard ratios (HR) with 95% confidence intervals (CI). Results: Among 7950 patients included in the study, 240 (3.0%) patients died within 30 days of surgery. Five post-operative complications (myocardial injury after non-cardiac surgery [MINS], major bleeding, sepsis, stroke, and acute kidney injury resulting in dialysis) were independently associated with death. Complications associated with the largest attributable fraction (AF) of post-operative mortality (i.e., percentage of deaths in the cohort that can be attributed to each complication, if causality were established) were major bleeding (n=1454, 18.3%, HR 2.49 95%CI 1.87-3.33, P&lt;0.001, AF 21.2%), sepsis (n=783, 9.9%, HR 6.52, 95%CI 4.72-9.01, P&lt;0.001, AF 15.6%), and MINS (n=980, 12.3%, HR 2.00, 95%CI 1.50-2.67, P&lt;0.001, AF 14.4%). Conclusion: The complications most associated with 30-day mortality following general surgery are major bleeding, sepsis, and MINS. These findings may guide the development of mitigating strategies, including prophylaxis for perioperative bleeding.

Association between preoperative albumin and length of hospital stay in non-cardiac surgery patients with pulmonary hypertension: A secondary retrospective analysis.

To explore the risk factors affecting the length of hospital stay (LOS) as well as to examine the relationship between preoperative serum albumin levels and LOS following non-cardiac, non-obstetric surgery in patients with pulmonary hypertension (PHTN). This study represents a secondary retrospective analysis based on 287 non-cardiac, non-obstetric procedures performed on 195 PTHN patients at a single institution in the USA between 2007 and 2013. The primary outcome was the LOS. We conducted a multiple logistic regression analysis to compare the LOS between the 2 groups, divided at a serum albumin level of 3.5 g/dL. After adjusting for multiple covariates, the ORs for the long length of stay (LOS > 7 days) for the high group(albumin > 3.5 g/dL) compared with the low group (albumin ≤ 3.5 g/dL) were 0.35 (95%CI: 0.21~0.6), 0.41 (95%CI: 0.22 ~0.76), 0.41 (95%CI: 0.18~0.94) from model 2 to model 4. The stratified analysis results indicate that these findings are stable (p for trend > 0.05). In this study, it was observed that low levels of preoperative albumin were associated with an increased risk of prolonged hospital stay after non-cardiac, non-obstetric surgery in patients with PHTN. This implies that optimizing preoperative nutrition could potentially reduce the LOS for non-cardiac, non-obstetric surgery in patients with PHTN.

The relative merits of using a high-sensitivity cardiac Troponin T assay compared to a nonhigh-sensitivity troponin T assay after noncardiac surgery

Troponin elevation after noncardiac surgery is associated with an elevated risk of 30-day mortality. Little is known about relative merit of using a high-sensitivity Troponin T (hsTnT), the fifth-generation assay, vs the nonhigh sensitivity Troponin T (non-hsTnT), the fourth-generation assay, in the noncardiac surgery setting. We aimed to identify whether hsTnT can identify additional patients at risk that would have gone undetected with non-hsTnT measurement. The VISION Study included 40,004 noncardiac surgery patients with postoperative troponin measurements. Among them, 1,806 patients had both fourth-generation non-hsTnT and fifth-generation hsTnT concomitant measurements (4,451 paired results). We compared the absolute concentrations, the timing, and the impact of different thresholds on predicting 30-day major cardiovascular complications (composite of death, nonfatal cardiac arrest, coronary revascularization, and congestive heart failure). Based on the manufacturers' threshold of 14 ng/L, 580 (32.1%) patients had postoperative hsTnT concentrations greater than the threshold, while their non-hsTnT concentrations were below the manufacturer's threshold. These 580 patients had higher risk of major cardiovascular events (OR 2.33; CI 95% 1.04-5.23; P = .049) than patients with hsTnT concentrations below the manufacturer threshold. Among patients with myocardial injury after noncardiac surgery, only 50% would be detected by the fourth-generation non-hsTnT assay at 6 to 12 hours postoperative as compared to 85% with the fifth-generation hsTnT assay (P-value < .001). Within the first 3 postoperative days, fifth-generation hsTnT identified at least 1 in 3 patients with troponin elevation that would have gone undetected by fourth-generation non-hsTnT using published thresholds in this setting. Furthermore, fifth-generation hsTnT identified patients with an elevation earlier than fourth-generation non-hsTnT, indicating potential to improve postoperative risk stratification.