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Presurgical Psychological and Neuroendocrine Predictors of Psychiatric Morbidity After Major Vascular Surgery: A Prospective Longitudinal Study.

ABSTRACT: Major life stressors, including major surgeries, are often followed by psychiatric symptoms and disorders. Prior retrospective work found abdominal aortic aneurysm (AAA) repair is followed by increased psychiatric morbidity, which may adversely influence physical and functional recovery. Identifying risk factors before surgery, such as dysregulation in stress response systems, might be useful in improving preventative intervention.Two hundred sixteen patients receiving open AAA or aortofemoral bypass surgeries, endovascular AAA repair, or nonsurgical AAA treatment were recruited from two vascular surgery services. Psychiatric symptoms and salivary cortisol measures (waking, 4 PM, and 11 PM, before and after low-dose dexamethasone) were obtained at intake and 3- and 9-month follow-ups.After open surgeries, 18% of patients had new psychiatric disorders, compared with 4% of patients receiving endovascular AAA repair or nonsurgical treatment (odds ratio = 6.0, 95% confidence interval = 1.6-22.1, p = .007). Having a history of major depression predicted the onset of new disorders in surgical patients. Presurgical cortisol levels were associated with both baseline (r = 0.23, p < .05) and 9-month (r = 0.32, p < .01) psychiatric symptoms (cortisol B = 1.0, standard error = 0.48, p < .05, in repeated-measures mixed model).Open AAA repair surgery is prospectively linked to the development of psychiatric morbidity, and history of depression elevates risk. Cortisol measures before surgery are associated with current and future psychological functioning, suggesting potential neurobiological mechanisms that may contribute to vulnerability. These results can help identify surgical patients at risk and point to potential targets for risk reduction interventions.

SUBMITTER: King AP

PROVIDER: S-EPMC4643324 | biostudies-literature | 2015 Nov-Dec

REPOSITORIES: biostudies-literature

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Presurgical Psychological and Neuroendocrine Predictors of Psychiatric Morbidity After Major Vascular Surgery: A Prospective Longitudinal Study.

King Anthony P AP Abelson James L JL Gholami Bardia B Upchurch Gilbert R GR Henke Peter P Graham Linda L Liberzon Israel I

Psychosomatic medicine 20151101 9

<h4>Objectives</h4>Major life stressors, including major surgeries, are often followed by psychiatric symptoms and disorders. Prior retrospective work found abdominal aortic aneurysm (AAA) repair is followed by increased psychiatric morbidity, which may adversely influence physical and functional recovery. Identifying risk factors before surgery, such as dysregulation in stress response systems, might be useful in improving preventative intervention.<h4>Methods</h4>Two hundred sixteen patients r ...[more]

PMID: 26461854

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Project description:Surgical site infection (SSI) is one of the most common postoperative complications after vascular reconstruction, producing significant morbidity and hospital readmission. In contrast to SSI that develops while patients are still hospitalized, little is known about the cohort of patients who develop SSI after discharge. In this study, we explore the factors that lead to postdischarge SSI, investigate the differences between risk factors for in-hospital vs postdischarge SSI, and develop a scoring system to identify patients who might benefit from postdischarge monitoring of their wounds.Patients who underwent major vascular surgery from 2005 to 2012 for aneurysm and lower extremity occlusive disease were identified from the American College of Surgeons National Surgical Quality Improvement Program Participant Use Files. Patients were categorized as having no SSI, in-hospital SSI, or SSI after hospital discharge. Predictors of postdischarge SSI were determined by multivariable logistic regression and internally validated by bootstrap resampling. Risk scores were assigned to all significant variables in the model. Summative risk scores were collapsed into quartile-based ordinal categories and defined as low, low/moderate, moderate/high, and high risk. Multivariable logistic regression was used to determine predictors of in-hospital SSI.Of the 49,817 patients who underwent major vascular surgery, 4449 (8.9%) were diagnosed with SSI (2.1% in-hospital SSI; 6.9% postdischarge SSI). By multivariable analysis, factors significantly associated with increased odds of postdischarge SSI include female gender, obesity, diabetes, smoking, hypertension, coronary artery disease, critical limb ischemia, chronic obstructive pulmonary disease, dyspnea, neurologic disease, prolonged operative time >4 hours, American Society of Anesthesiology class 4 or 5, lower extremity revascularization or aortoiliac procedure, and groin anastomosis. The model exhibited moderate discrimination (bias-corrected C statistic, 0.691) and excellent internal calibration. The postdischarge SSI rate was 2.1% for low-risk patients, 5.1% for low/moderate-risk patients, 7.8% for moderate/high-risk patients, and 14% for high-risk patients. In a comparative analysis, comorbidities were the primary driver of postdischarge SSI, whereas in-hospital factors (operative time, emergency case status) and complications predicted in-hospital SSI.The majority of SSIs after major vascular surgery develop following hospital discharge. We have created a scoring system that can select a cohort of patients at high risk for SSI after discharge. These patients can be targeted for transitional care efforts focused on early detection and treatment with the goal of reducing morbidity and preventing readmission secondary to SSI.

Project description:Psychiatric co-morbidity, in particular major depression and anxiety, is common in patients with Crohn's disease (CD) and ulcerative colitis (UC). Prior studies examining this may be confounded by the co-existence of functional bowel symptoms. Limited data exist examining an association between depression or anxiety and disease-specific endpoints such as bowel surgery.To examine the frequency of depression and anxiety (prior to surgery or hospitalisation) in a large multi-institution electronic medical record (EMR)-based cohort of CD and UC patients; to define the independent effect of psychiatric co-morbidity on risk of subsequent surgery or hospitalisation in CD and UC, and to identify the effects of depression and anxiety on healthcare utilisation in our cohort.Using a multi-institution cohort of patients with CD and UC, we identified those who also had co-existing psychiatric co-morbidity (major depressive disorder or generalised anxiety). After excluding those diagnosed with such co-morbidity for the first time following surgery, we used multivariate logistic regression to examine the independent effect of psychiatric co-morbidity on IBD-related surgery and hospitalisation. To account for confounding by disease severity, we adjusted for a propensity score estimating likelihood of psychiatric co-morbidity influenced by severity of disease in our models.A total of 5405 CD and 5429 UC patients were included in this study; one-fifth had either major depressive disorder or generalised anxiety. In multivariate analysis, adjusting for potential confounders and the propensity score, presence of mood or anxiety co-morbidity was associated with a 28% increase in risk of surgery in CD (OR: 1.28, 95% CI: 1.03-1.57), but not UC (OR: 1.01, 95% CI: 0.80-1.28). Psychiatric co-morbidity was associated with increased healthcare utilisation.Depressive disorder or generalised anxiety is associated with a modestly increased risk of surgery in patients with Crohn's disease. Interventions addressing this may improve patient outcomes.

Project description:ObjectiveHeart rate (HR) parameters are known indicators of cardiovascular complications after cardiac surgery, but there is little evidence of their role in predicting outcome after major vascular surgery. The purpose of this study was to determine whether arrival HR (AHR) and highest intraoperative HR are associated with mortality or major adverse cardiac events (MACEs) after elective vascular surgery in the Vascular Quality Initiative (VQI).MethodsPatients undergoing elective lower extremity bypass (LEB), aortofemoral bypass (AFB), and open abdominal aortic aneurysm (AAA) repair in the VQI were analyzed. MACE was defined as any postoperative myocardial infarction, dysrhythmia, or congestive heart failure. Controlled HR was defined as AHR <75 beats/min on operating room arrival. Delta HR (DHR) was defined as highest intraoperative HR - AHR. Procedure-specific MACE models were derived for risk stratification, and generalized estimating equations were used to account for clustering of center effects. HR, beta-blocker exposure, cardiac risk, and their interactions were explored to determine association with MACE or 30-day mortality. A Bonferroni correction with P < .004 was used to declare significance.ResultsThere were 13,291 patients reviewed (LEB, n = 8155 [62%]; AFB, n = 2629 [18%]; open AAA, n = 2629 [20%]). Rates of any preoperative beta-blocker exposure were as follows: LEB, 66.5% (n = 5412); AFB, 57% (n = 1342); and open AAA, 74.2% (n = 1949). AHR and DHR outcome association was variable across patients and procedures. AHR <75 beats/min was associated with increased postoperative myocardial infarction risk for LEB patients across all risk strata (odds ratio [OR], 1.4; 95% confidence interval [CI], 1.03-1.9; P = .03), whereas AHR <75 beats/min was associated with decreased dysrhythmia risk (OR, 0.42; 95% CI, 0.28-0.63; P = .0001) and 30-day death (OR, 0.50; 95% CI, 0.33-0.77; P = .001) in patients at moderate and high cardiac risk. These HR associations disappeared in controlling for beta-blocker status. For AFB and open AAA repair patients, there was no significant association between AHR and MACE or 30-day mortality, irrespective or cardiac risk or beta-blocker status. DHR and extremes of highest intraoperative HR (>90 or 100 beats/min) were analyzed among all three operations, and no consistent associations with MACE or 30-day mortality were detected.ConclusionsThe VQI AHR and highest intraoperative HR variables are highly confounded by patient presentation, operative variables, and beta-blocker therapy. The discordance between cardiac risk and HR as well as the lack of consistent correlation to outcome makes them unreliable predictors. The VQI has elected to discontinue collecting AHR and highest intraoperative HR data, given insufficient evidence to suggest their importance as an outcome measure.

Project description:BackgroundPatients undergoing abdominal surgery for solid tumours frequently develop major postoperative complications, which negatively affect quality of life, costs of care and survival. Few studies have identified the determinants of perioperative complications in this group.MethodsWe performed a prospective observational study including all patients (age?>?18) undergoing abdominal surgery for cancer at a single institution between June 2011 and August 2013. Patients undergoing emergency surgery, palliative procedures, or participating in other studies were excluded. Primary outcome was a composite of 30-day all-cause mortality and infectious, cardiovascular, respiratory, neurologic, renal and surgical complications. Univariate and multiple logistic regression analyses were performed to identify predictive factors for major perioperative adverse events.ResultsOf a total 308 included patients, 106 (34.4%) developed a major complication during the 30-day follow-up period. Independent predictors of postoperative major complications were: age (odds ratio [OR] 1.03 [95% CI 1.01-1.06], p?=?0.012 per year), ASA (American Society of Anesthesiologists) physical status greater than or equal to 3 (OR 2.61 [95% CI 1.33-5.17], p?=?0.003), a preoperative haemoglobin level lower than 12 g/dL (OR 2.13 [95% CI 1.21-4.07], p?=?0.014), intraoperative use of colloids (OR 1.89, [95% CI 1.03-4.07], p?=?0.047), total amount of intravenous fluids (OR 1.22 [95% CI 0.98-1.59], p?=?0.106 per litre), intraoperative blood losses greater than 500 mL (2.07 [95% CI 1.00-4.31], p?=?0.043), and hypotension needing vasopressor support (OR 4.68 [95% CI 1.55-27.72], p?=?0.004). The model had good discrimination with the area under the ROC curve being 0.80 (95% CI 0.75-0.84, p?<?0.001).ConclusionsOur findings suggest that a perioperative strategy aimed at reducing perioperative complications in cancer surgery should include treatment of preoperative anaemia and an optimal fluid strategy, avoiding fluid overload and intraoperative use of colloids.

Project description:BackgroundPostoperative acute kidney injury is common after major vascular surgery and is associated with increased morbidity, mortality, and cost. High-performance risk stratification using a machine learning model can inform strategies that mitigate harm and optimize resource use. It is hypothesized that incorporating intraoperative data would improve machine learning model accuracy, discrimination, and precision in predicting acute kidney injury among patients undergoing major vascular surgery.MethodsA single-center retrospective cohort of 1,531 adult patients who underwent nonemergency major vascular surgery, including open aortic, endovascular aortic, and lower extremity bypass procedures, was evaluated. The validated, automated MySurgeryRisk analytics platform used electronic health record data to forecast patient-level probabilistic risk scores for postoperative acute kidney injury using random forest models with preoperative data alone and perioperative data (preoperative plus intraoperative). The MySurgeryRisk predictions were compared with each other as well as with the American Society of Anesthesiologists physical status classification.ResultsMachine learning models using perioperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification (accuracy: 0.70 vs 0.64 vs 0.62, area under the receiver operating characteristics curve: 0.77 vs 0.68 vs 0.61, area under the precision-recall curve: 0.70 vs 0.58 vs 0.48).ConclusionIn predicting acute kidney injury after major vascular surgery, machine learning approaches that incorporate dynamic intraoperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification. Machine learning methods have the potential for real-time identification of high-risk patients who may benefit from personalized risk-reduction strategies.

Dataset Information

Presurgical Psychological and Neuroendocrine Predictors of Psychiatric Morbidity After Major Vascular Surgery: A Prospective Longitudinal Study.

Publications

Presurgical Psychological and Neuroendocrine Predictors of Psychiatric Morbidity After Major Vascular Surgery: A Prospective Longitudinal Study.

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