Noncardiac Surgical Patients Research Articles

The effect of comorbidity on 28-day perioperative mortality rate among non-cardiac surgical patients in Northwest Ethiopia: a prospective cohort study using propensity score matching

The effect of comorbidity on 28-day perioperative mortality rate among non-cardiac surgical patients in Northwest Ethiopia: a prospective cohort study using propensity score matching

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.

The Correlation of Level of Surgical Risk with High Sensitivity Cardiac Troponin in Non-Cardiac Surgical Patients

The Correlation of Level of Surgical Risk with High Sensitivity Cardiac Troponin in Non-Cardiac Surgical Patients

Perioperative approaches to prevent delayed neurocognitive recovery and postoperative neurocognitive disorder in older surgical patients: A systematic review and meta-analysis of randomized controlled trials

Abstract Background and and Aims: Delayed neurocognitive recovery (DNR) and postoperative neurocognitive disorder (P-NCD) are common postoperative complications affecting older patients. This review evaluates perioperative approaches for preventing DNR and P-NCD in older noncardiac surgical patients. Material and Methods: We searched databases for relevant articles from inception through June 2022 and updated in May 2023 (PROSPERO ID CRD42022359289). Randomized controlled trials (RCTs) utilizing intervention for DNR and/or P-NCD were included. Results: We included 39 RCTs involving anesthetic (25 RCTs, 7422 patients) and other pharmacological and nonpharmacological approaches (14 RCTs, 2210 patients). Seventeen trials investigating four interventions were included in the meta-analysis for DNR. Perioperative dexmedetomidine (relative risk [RR]: 0.59, 95% confidence interval [CI]: 0.35–0.97; P = 0.04) and propofol-based total intravenous anesthesia (TIVA) (RR: 0.81, 95% CI: 0.66–0.98; P = 0.03) significantly decreased the risk of DNR versus control. There was no significant decrease in the risk of DNR with regional anesthesia (RA) versus general anesthesia (GA) (RR: 0.89, 95% CI: 0.63–1.26) or bispectral index (BIS) monitoring (RR: 0.79, 95% CI: 0.60–1.04) versus the control groups. Evidence regarding the effects of interventions on P-NCD is limited. Although all included trials were at low risk of bias, the quality of meta-analysis pooled estimates was low. Conclusions: Our meta-analysis of RCTs showed that dexmedetomidine and TIVA decrease the risk of DNR in older patients undergoing noncardiac surgery by 41% and 20%, respectively, versus control. Further RCTs of adequate power and methodology on the effects of interventions on DNR and P-NCD are warranted. Key Messages: Our meta-analysis of RCTs showed that dexmedetomidine and TIVA decrease the risk of DNR in older patients undergoing noncardiac surgery by 41% and 20%, respectively, versus controls, whereas RA and BIS monitoring do not.

Association between intraoperative tidal volume and postoperative acute kidney injury in non-cardiac surgical patients using a propensity score-weighted analysis

Acute kidney injury (AKI) is related to adverse clinical outcomes. Therefore, identifying patients at increased risk of postoperative AKI and proactively providing appropriate care is crucial. However, only a limited number of modifiable risk factors have been recognized to mitigate AKI risk. We retrospectively analyzed adult patients who underwent endotracheal intubation and mechanical ventilation of more than 2 h during non-cardiac surgery at Seoul National University Hospital from January 2011 to November 2022. Patients were grouped into low- or high-tidal volume groups based on their intraoperative tidal volume relative to their predicted body weight (PBW) of 8 ml/kg. The association between intraoperative tidal volume and postoperative AKI was evaluated using inverse probability of treatment weighting (IPTW), adjusting for various preoperative confounders. Among the 37,726 patients included, the incidence of postoperative AKI was 4.1%. The odds of postoperative AKI risk were significantly higher in the high-tidal volume group than in the low-tidal volume group before and after IPTW (odds ratio [OR] 1.20, 95% confidence interval [CI] 1.08–1.32, P = 0.001 and OR: 1.10, 95% CI 1.02–1.19, P = 0.010, respectively). In the multivariable logistic regression analysis after IPTW, a high tidal volume was independently associated with an increased risk of postoperative AKI (OR: 1.21, 95% CI 1.12–1.30, P < 0.001). In this propensity score-weighted analysis, an intraoperative high tidal volume of more than 8 ml/kg PBW was significantly associated with an increased risk of postoperative AKI after IPTW in non-cardiac surgical patients. Intraoperative tidal volume showed potential as a modifiable risk factor for preventing postoperative AKI.

The impact of comorbidities on outcomes of concomitant mitral valve intervention with ascending aortic surgery

IntroductionThe Charlson Comorbidity Index (CCI) is widely utilized for risk stratification for non-cardiac surgical patients, yet it has not been broadly validated in patients undergoing cardiac surgery. We aim to assess its ability to predict early and late outcomes of concomitant mitral valve intervention with ascending aortic surgery. MethodsPatients who underwent surgery between 1997 and 2022 were reviewed. Age-adjusted CCI scores were calculated based on clinical status at a time of index operation. The primary endpoint was all causes mortality while secondary outcomes were major adverse events (MAE) that included combined perioperative mortality, dialysis, myocardial infarction, and stroke in addition to the individual outcomes and take back for bleeding and tracheostomy. Chi-square test, Logistic and Cox regression analysis, and Kaplan-Meier curves were used. Maximally selected rank statistics were used to identify best cutoff of CCI for late mortality. Results186 patients (median age 65 [interquartile range (IQR): 54–76] and 69% males) were included with a median CCI of 4 [IQR: 3–6]. Five and ten-years overall survival were 95.9% and 67.1% vs 59.7%, and 19.9% in CCI ≤ 5 vs >5 (P < 0.001).On multivariate Cox regression analysis, higher CCI (HR 1.60 [1.17;2.18], P = 0.00), and lower EF (HR 0.89 [0.83;0.96], P = 0.002) were associated with late mortality. There was a trend to lower mortality in recent surgery years (HR 0.91 [0.83;1.01], P = 0.070)).Perioperative MAE was higher in CCI >5 (11.0% vs 2.1%, P = 0.017), and postoperative need for tracheostomy and CVA had a trend to be higher in CCI > 5 (P = 0.055).Logistic regression revealed that higher CCI, as a continuous variable, was associated with significantly higher odds of MAE, postoperative dialysis, and need for tracheostomy. ConclusionsThe CCI can be a helpful tool in predicting outcomes of patients undergoing concomitant mitral valve intervention with ascending aortic surgery.

Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study

Background: Despite low mortality for elective procedures in the United States and developed countries, some patients have unexpected care escalations (UCE) following post-anesthesia care unit (PACU) discharge. Studies indicate patient risk factors for UCE, but determining which factors are most important is unclear. Machine learning (ML) can predict clinical events. We hypothesized that ML could predict patient UCE after PACU discharge in surgical patients and identify specific risk factors. Methods: We conducted a single center, retrospective analysis of all patients undergoing non-cardiac surgery (elective and emergent). We collected data from pre-operative visits, intra-operative records, PACU admissions, and the rate of UCE. We trained a ML model with this data and tested the model on an independent data set to determine its efficacy. Finally, we evaluated the individual patient and clinical factors most likely to predict UCE risk. Results: Our study revealed that ML could predict UCE risk which was approximately 5% in both the training and testing groups. We were able to identify patient risk factors such as patient vital signs, emergent procedure, ASA Status, and non-surgical anesthesia time as significant variable. We plotted Shapley values for significant variables for each patient to help determine which of these variables had the greatest effect on UCE risk. Of note, the UCE risk factors identified frequently by ML were in alignment with anesthesiologist clinical practice and the current literature. Conclusions: We used ML to analyze data from a single-center, retrospective cohort of non-cardiac surgical patients, some of whom had an UCE. ML assigned risk prediction for patients to have UCE and determined perioperative factors associated with increased risk. We advocate to use ML to augment anesthesiologist clinical decision-making, help decide proper disposition from the PACU, and ensure the safest possible care of our patients.

Risk Factors, Pathogens, and Outcomes of Ventilator-Associated Pneumonia in Non-Cardiac Surgical Patients: A Retrospective Analysis.

Ventilator-associated pneumonia (VAP) is a critical hospital-acquired infection following non-cardiac surgeries, leading to poor outcomes. This study identifies VAP risk factors in non-cardiac surgical patients and determines the causative pathogens. A retrospective analysis with 1:4 propensity-score matching was conducted on patients in a surgical intensive care unit (ICU) from 2010 to 2020 at a private tertiary medical center. Among 99 VAP patients, the mortality rate was 64.7%. VAP risk factors included prolonged mechanical ventilation (odds ratio [OR] 6.435; p < 0.001), repeat intubation (OR 6.438; p < 0.001), lower oxygenation levels upon ICU admission (OR 0.950; p < 0.001), and undergoing gastrointestinal surgery (OR 2.257; p = 0.021). The 30-day mortality risk factors in the VAP group were late-onset VAP (OR 3.450; p = 0.022), inappropriate antibiotic treatment (OR 4.083; p = 0.041), and undergoing gastrointestinal surgeries (OR 4.776; p = 0.019). Nearly half of the Gram-negative infections were resistant strains, and a third were polymicrobial infections. Non-cardiac surgical patients with VAP face adverse hospital outcomes. Identifying high-risk patients and understanding VAP's resistant and microbial nature are crucial for appropriate treatment and improved health outcomes.

Outcomes associated with postoperative cognitive dysfunction: a systematic review and meta-analysis.

Postoperative cognitive dysfunction (POCD) manifests as a subtle decline in cognition, potentially leading to unfavourable postoperative outcomes. We explored the impact of POCD on physical function, length of hospital stay (LOS), dementia and mortality outcomes. PubMed and Scopus were searched until May 2023. All studies of major surgical patients that assessed POCD and outcomes of interest were included. POCD effects were stratified by surgery type (cardiac and noncardiac) and time of POCD assessment (<30 and ≥30days postsurgery). Of 2316 studies, 20 met the inclusion criteria. POCD was not associated with functional decline postsurgery. Patients who experienced POCD postcardiac surgery had an increased relative risk (RR) of death of 2.04 [(95% CI: 1.18, 3.50); I2= 0.00%]. Sensitivity analyses showed associations with intermediate-term mortality among noncardiac surgical patients, with an RR of 1.84 [(95% CI: 1.26, 2.71); I2= 0.00%]. Patients who developed POCD <30days postcardiac and noncardiac surgeries experienced longer LOS than those who did not [mean difference (MD) = 1.37days (95% CI: 0.35, 2.39); I2= 92.38% and MD = 1.94days (95% CI: 0.48, 3.40); I2= 83.29%, respectively]. Postoperative delirium (POD) may contribute to the heterogeneity observed, but limited data were reported within the studies included. Patients undergoing cardiac and noncardiac surgeries who developed POCD <30days postsurgery had poorer outcomes and an increased risk of premature death. Early recognition of perioperative neurocognitive disorders in at-risk patients may enable early intervention. However, POD may confound our findings, with further studies necessary to disentangle the effects of POD from POCD on clinical outcomes.

The exploration of perioperative hypotension subtypes: a prospective, single cohort, observational pilot study.

Hypotension is a risk factor for postoperative complications, but evidence from randomized trials does not support that a higher blood pressure target always leads to optimized outcomes. The heterogeneity of underlying hemodynamics during hypotension may contribute to these contradictory results. Exploring the subtypes of hypotension can enable optimal management of intraoperative hypotension. This is a prospective, observational pilot study. Patients who were ≥ 45 years old and scheduled to undergo moderate-to-high-risk noncardiac surgery were enrolled in this study. The primary objective of this pilot study was to investigate the frequency and distribution of perioperative hypotension and its subtypes (hypotension with or without cardiac output reduction). The exposure of hypotension and its subtypes in patients with and without myocardial or acute kidney injury were also explored. Sixty patients were included in the analysis. 83% (50/60) of the patients experienced perioperative hypotension. The median duration of hypotension for each patient was 8.0 [interquartile range, 3.1-23.3] minutes. Reduced cardiac output was present during 77% of the hypotension duration. Patients suffering from postoperative myocardial or acute kidney injury displayed longer duration and more extensive exposure in all hypotension subtypes. However, the percentage of different hypotension subtypes did not differ in patients with or without postoperative myocardial or acute kidney injury. Perioperative hypotension was frequently accompanied by cardiac output reduction in moderate-to-high-risk noncardiac surgical patients. However, due to the pilot nature of this study, the relationship between hypotension subtypes and postoperative myocardial or acute kidney injury still needs further exploration. https://www.chictr.org.cn/showprojEN.html?proj=134260, CTR2200055929.

A Review of Chlorhexidine Oral Care in Patients Receiving Mechanical Ventilation.

Chlorhexidine gluconate has been considered the criterion standard of oral care for patients receiving mechanical ventilation because of its ability to reduce the incidence of ventilator-associated events. Optimal concentrations and frequencies remain unclear, as do adverse events related to mortality in various intensive care unit populations. To examine the current evidence for the efficacy of chlorhexidine gluconate in reducing the incidence of ventilator-associated events, mortality, intensive care unit length of stay, and duration of mechanical ventilation in patients receiving ventilator support. In this integrative review, CINAHL (Cumulative Index to Nursing and Allied Health Literature), MEDLINE, and Health Source: Nursing/Academic Edition were searched using terms related to mechanical ventilation and chlorhexidine gluconate oral care with dates ranging from 2012 to 2023. Seventeen articles were included in this review: 8 systematic reviews, 8 randomized clinical trials (3 of which were not included in any systematic review), and 1 quasi-experimental study. Chlorhexidine gluconate oral care was associated with a reduced incidence of ventilator-associated events, but efficacy depended on concentration and frequency of administration. With stratification by intensive care unit population type, a nonsignificant trend toward increased mortality was found among non-cardiac surgical patients who received this care. The evidence regarding the efficacy of chlorhexidine gluconate oral care in reducing ventilator-associated events in specific intensive care unit populations is contradictory. Recently published guidelines recommend de-implementation of chlorhexidine gluconate oral care in all patients receiving mechanical ventilation. Such care may be beneficial only in the cardiac surgical population.

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

BackgroundPostoperative acute kidney injury (AKI) is a common and costly complication after non-cardiac surgery. Patients with or without diabetes could develop hyperglycemia before surgery, and preoperative hyperglycemia was closely associated with postoperative poor outcomes, but the association between preoperative fasting blood glucose level and postoperative AKI is still unclear.MethodsData from patients undergoing non-cardiac surgery in Chongqing University Cancer Hospital from January 1, 2017, to May 31, 2023, were collected, preoperative glucose value and perioperative variables were extracted, the primary exposure of interest was preoperative glucose value, and the outcome was postoperative AKI.ResultsData from 39,986 patients were included in the final analysis, 741(1.9%) patients developed AKI, 134(5.6%) in the cohort with DM, and 607(1.6%) in the cohort without DM(OR 1.312, 95% CI 1.028–1.675, P = 0.029). A significant non-linear association between preoperative glucose and AKI exists in the cohort without DM after covariable adjustment (P = 0.000), and every 1 mmol/L increment of preoperative glucose level increased OR by 15% (adjusted OR 1.150, 95% CI 1.078–1.227, P = 0.000), the optimal cut-point of preoperative fasting glucose level to predict AKI was 5.39 mmol/L (adjusted OR 1.802, 95%CI 1.513–2.146, P = 0.000). However, in the cohort with DM, the relation between preoperative glucose and postoperative AKI was not significant after adjusting by covariables (P = 0.437). No significance exists between both cohorts in the risk of AKI over the range of preoperative glucose values.ConclusionA preoperative fasting glucose value of 5.39 mmol/L can predict postoperative acute kidney injury after non-cardiac surgery in patients without diagnosed diabetes, but it is not related to AKI in patients with the diagnosis.

Association between perioperative non-steroidal anti-inflammatory drug use and cardiovascular complications after non-cardiac surgery in older adult patients.

We investigated in older adult non-cardiac surgical patients whether receipt of perioperative non-steroidal anti-inflammatory drugs (NSAIDs) is associated with increased incidence of postoperative cardiovascular complications. We retrospectively extracted the information for patients with age ≥ 65years who had inpatient non-cardiac surgery with a duration of ≥ 1h from the American College of Surgeons-National Surgical Quality Improvement Program registry data acquired at the University of Washington Medical Center. We compared patients who received NSAIDs perioperatively to those who did not receive NSAIDs, on the two composite outcomes: (1) the incidence of postoperative cardiovascular complications within 30days of the surgery, and (2) the incidence of combined postoperative gastrointestinal and renal complications, and length of postoperative hospital stay. We used separate multivariable logistic regression models to analyze the two composite outcomes and a Poisson regression model for the length of hospital stay. The receipt of perioperative NSAIDs was not associated with postoperative cardiovascular complications (estimated odds ratio (OR), 1.78; 95% confidence interval (CI), 0.97 to 3.25; P = 0.06), combined renal and gastrointestinal complications (estimated OR, 1.30; 95% CI, 0.53 to 3.20; P = 0.57), and length of postoperative hospital stay in days (incidence rate ratio, 1.06; 95% CI, 0.93 to 1.21; P = 0.39). In older adult non-cardiac surgical patients, receipt of perioperative NSAIDs was not associated with increased incidences of postoperative cardiovascular complications, and renal and gastrointestinal complications within 30days after surgery, or length of postoperative hospital stay.

Development and multicentre validation of the FLEX score: personalised preoperative surgical risk prediction using attention-based ICD-10 and Current Procedural Terminology set embeddings

BackgroundPreoperative knowledge of surgical risks can improve perioperative care and patient outcomes. However, assessments requiring clinician examination of patients or manual chart review can be too burdensome for routine use. MethodsWe conducted a multicentre retrospective study of 243 479 adult noncardiac surgical patients at four hospitals within the Mass General Brigham (MGB) system in the USA. We developed a machine learning method using routinely collected coding and patient characteristics data from the electronic health record which predicts 30-day mortality, 30-day readmission, discharge to long-term care, and hospital length of stay. ResultsOur method, the Flexible Surgical Set Embedding (FLEX) score, achieved state-of-the-art performance to identify comorbidities that significantly contribute to the risk of each adverse outcome. The contributions of comorbidities are weighted based on patient-specific context, yielding personalised risk predictions. Understanding the significant drivers of risk of adverse outcomes for each patient can inform clinicians of potential targets for intervention. ConclusionsFLEX utilises information from a wider range of medical diagnostic and procedural codes than previously possible and can adapt to different coding practices to accurately predict adverse postoperative outcomes.

Prognostic value of high-sensitivity cardiac troponin in non-cardiac surgical patients in intensive care units

Type II myocardial injury following surgical procedures is associated with adverse outcomes. The prognostic value of high-sensitivity cardiac troponin (hs-cTn) due to type II myocardial injury in surgical patients admitted to intensive care unit (ICU) remains unclear. The aim of this study was to assess prognostic value of hs-cTn in type II acute myocardial injury in non-cardiac surgical patients requiring post-operative ICU admission. Retrospective analysis of patients admitted to two level III ICUs following surgery and had hs-cTn measured on the day of ICU admission. Patients who had type I acute myocardial infarction (AMI) during their admission were excluded from the study. The primary outcome was hospital mortality. Secondary outcomes included ICU mortality, ICU length of stay (LOS) and hospital LOS. A total of 420 patients were included. On univariable analysis, higher hs-cTn was associated with increased hospital mortality (14.6% vs 6.3%, p = 0.008), ICU LOS (41.1 h, vs 25 h, p = 0.004) and hospital LOS (253 h vs 193 h, p = 0.02). On multivariable analysis, hs-cTn was not independently associated with increased risk of hospital mortality. However, in patients who had elective surgery, hs-cTn was associated with increased risk (OR 1.048; 95% CI 1.004–1.094; p = 0.031) of hospital mortality with area under the receiver operating characteristic curve of 0.753 (95% CI 0.598–0.908). In elective surgical patients, hs-cTn was associated with increased risk of mortality. Larger multicentre studies are required to confirm this association that may assist in risk stratification of elective surgical patients requiring ICU admission.

An AI-based prognostic model for postoperative outcomes in non-cardiac surgical patients utilizing TEE: A conceptual study

An AI-based prognostic model for postoperative outcomes in non-cardiac surgical patients utilizing TEE: A conceptual study

Development and validation of delirium prediction models for noncardiac surgery patients

Study objectivePostoperative delirium is associated with morbidity and mortality, and its incidence varies widely. Using known predisposing and precipitating factors, we sought to develop postoperative delirium prediction models for noncardiac surgical patients. DesignRetrospective prediction model study. SettingMajor quaternary medical center. PatientsOur January 2016 to June 2020 training dataset included 51,677 patients of whom 2795 patients had delirium. Our July 2020 to January 2022 validation dataset included 14,438 patients of whom 912 patients had delirium. InterventionsNone. MeasurementsWe trained and validated two static prediction models and one dynamic delirium prediction model. For the static models, we used random survival forests and traditional Cox proportional hazard models to predict postoperative delirium from preoperative variables, or from a combination of preoperative and intraoperative variables. We also used landmark modeling to dynamically predict postoperative delirium using preoperative, intraoperative, and postoperative variables before onset of delirium. Main resultsIn the validation analyses, the static random forest model had a c-statistic of 0.81 (95% CI: 0.79, 0.82) and a Brier score of 0.04 with preoperative variables only, and a c-statistic of 0.86 (95% CI: 0.84, 0.87) and a Brier score of 0.04 when preoperative and intraoperative variables were combined. The corresponding Cox models had similar discrimination metrics with slightly better calibration. The dynamic model - using all available data, i.e., preoperative, intraoperative and postoperative data - had an overall c-index of 0.84 (95% CI: 0.83, 0.85). ConclusionsUsing preoperative and intraoperative variables, simple static models performed as well as a dynamic delirium prediction model that also included postoperative variables. Baseline predisposing factors thus appear to contribute far more to delirium after noncardiac surgery than intraoperative or postoperative variables. Improved postoperative data capture may help improve delirium prediction and should be evaluated in future studies.

Development and prospective validation of postoperative pain prediction from preoperative EHR data using attention-based set embeddings

Preoperative knowledge of expected postoperative pain can help guide perioperative pain management and focus interventions on patients with the greatest risk of acute pain. However, current methods for predicting postoperative pain require patient and clinician input or laborious manual chart review and often do not achieve sufficient performance. We use routinely collected electronic health record data from a multicenter dataset of 234,274 adult non-cardiac surgical patients to develop a machine learning method which predicts maximum pain scores on the day of surgery and four subsequent days and validate this method in a prospective cohort. Our method, POPS, is fully automated and relies only on data available prior to surgery, allowing application in all patients scheduled for or considering surgery. Here we report that POPS achieves state-of-the-art performance and outperforms clinician predictions on all postoperative days when predicting maximum pain on the 0–10 NRS in prospective validation, though with degraded calibration. POPS is interpretable, identifying comorbidities that significantly contribute to postoperative pain based on patient-specific context, which can assist clinicians in mitigating cases of acute pain.

Is a preoperative multidisciplinary team meeting (cost)effective to improve outcome for high-risk adult patients undergoing noncardiac surgery: the PREPARATION study—a multicenter stepped-wedge cluster randomized trial

BackgroundAs a result of increased life expectancy and improved care for patients suffering from chronic disease, the number of patients with multimorbidity requiring surgical intervention is increasing. For complex surgical patients, it is essential to balance the potential benefits of surgical treatment against the risk of permanent loss of functional capacity and quality of life due to complications. European and US guidelines on perioperative care recommend preoperative multidisciplinary team (MDT) discussions for high-risk noncardiac surgical patients. However, the evidence underlying benefits from preoperative MDT meetings with all relevant perioperative specialties present is limited. The current study aims to investigate the effect of implementation of preoperative MDT discussions for high-risk patients undergoing noncardiac surgery on serious adverse events.Methods/designPREPARATION is a stepped-wedge cluster randomized trial in 14 Dutch hospitals without currently established preoperative MDT meeting. The intervention, preoperative MDT meetings, will be implemented sequentially with seven blocks of 2 hospitals switching from control (preoperative screening as usual) to the intervention every 3 months. Each hospital will be randomized to one of seven blocks. We aim to include 1200 patients. The primary outcome is the incidence of serious adverse events at 6 months. Secondary outcomes include (cost)effectiveness, functional outcome, and quality of life for up to 12 months.DiscussionPREPARATION is the first study to assess the effectiveness of a preoperative MDT meeting for high-risk noncardiac surgical patients in the presence of an anesthesiologist. If the results suggest that preoperative MDT discussions for high-risk patients are (cost)-effective, the current study facilitates implementation of preoperative MDT meetings in clinical practice.Trial registrationClinicalTrials.gov NCT05703230. Registered on 11/09/2022.

Mental health changes in elderly patients undergoing non-cardiac surgery during the COVID-19 pandemic in China

BackgroundThe COVID-19 pandemic has a heavy impact on the mental health of elderly surgical patients worldwide. In particular, the elderly patients faced considerable psychological stress due to various environmental and medical factors during the outbreak. This study aims to examine changes in mental health trends among non-cardiac surgical patients aged 65 and above in China during the COVID-19 pandemic. MethodsThis multi-center, convenient sampling, longitudinal observational study was conducted from April 1, 2020 to April 30, 2022. Primary outcome was the prevalence of postoperative depression. Secondary outcome was the prevalence of postoperative anxiety. Follow-up was conducted separately at 7 days and 30 days after surgery. Depression symptoms were assessed using the Patient Health Questionnaire 9 (PHQ-9) scale. Anxiety symptoms were assessed using Generalized Anxiety Disorder-7 (GAD-7) scale, with scores of ≥5 defining positive depression or anxiety symptoms. Multivariate logistic regression analysis was used to investigate risk factors of mental health status in more elderly patients undergoing non-cardiac surgery. ResultsA total of 4639 patients were included, of whom 2279 (46.0 %) were male, 752 (15.2 %) were over the age of 75, and 4346 (93.7 %) were married. The monthly prevalence trends demonstrated that compared to the outbreak period, a significant reduction in the prevalence of depression and anxiety symptoms in elderly patients who underwent surgery during the post-pandemic period. In post-pandemic period, a statistically significant decrease in the prevalence of all severity depression and anxiety patients was noted at the 7-day follow-up, but no significant decrease was observed for severe depression and anxiety in the 30-day follow-up. In COVID-19 low-risk area, a significant overall decrease in prevalence of mental health was observed during the post-pandemic period compared to the outbreak period, including 7-day depression, 7-day anxiety, 30-day depression, and 30-day anxiety (all with P < 0.001). Female and patients with ≥2 comorbidities appeared to be more susceptible to postoperative depression and anxiety during the pandemic. LimitationThe absence of data from the early days of the COVID-19 outbreak. ConclusionsThis study analyzed the prevalence of depression and anxiety in elderly non-cardiac patients during and after the COVID-19 pandemic, focusing on dimensions such as severity, risk-areas, gender, and comorbidity. Our findings revealed a significant decrease in the prevalence of depression and anxiety in elderly surgery patients during the post-pandemic period.