Outcomes of Dexmedetomidine with Local Regional Anesthesia in Carotid Endarterectomy.

BACKGROUND: Adequate sedation to complement regional techniques in carotid endarterectomy (CEA) can be challenging. Dexmedetomidine has both analgesic and amnesic properties and is reported to be a safe and acceptable alternative to conventional general endotracheal anesthesia (GETA). Outcomes observing dexmedetomidine in conjunction with regional anesthesia in CEA are not well described or known. OBJECTIVE: Compare the immediate (during hospitalization) and short-term (within 30 days of hospitalization) postoperative outcomes in patients who underwent CEA using GETA versus local regional anesthesia (LRA) alone versus dexmedetomidine with LRA at a single institution to determine whether dexmedetomidine is a safe adjunct and if there are anesthesia advantages over LRA alone. METHODS: A retrospective cohort study from January 2015 to December 2019 at Saint Joseph Mercy Ann Arbor. Patients were stratified into three groups based on anesthesia type: GETA, LRA, and dexmedetomidine (D) + LRA. Primary outcomes included stroke, myocardial infarction (MI), and death. Patient demographics were characterized and adjusted using propensity score weighting. RESULTS: Three hundred seventy nine patients met inclusion criteria; 182 patients in the GETA group, 66 in the D + LRA, and 131 in LRA. There were no significant differences across anesthesia groups in primary outcomes of stroke, MI, and death during the admission. The GETA group had significantly longer length of stay (LOS) compared to the D + LRA group (LOS = 1.51 days versus 0.85 days; P = 0.011) and the LRA group (LOS = 1.08 days; P = 0.003). However, there was no significant difference in hospital LOS between the D + LRA group and LRA only groups (P = 0.952). There was no significant difference between stroke (LRA 0.87%, GETA 0.85%, and LRA + Dex 3.52%), MI (LRA 0%, GETA 0.49%, LRA + Dex 0%), or death (LRA 5.24%, GETA 1.16%, LRA + Dex 0%), within 30 days between all three of the anesthesia groups. There was no significant difference in postoperative pain scores when comparing the GETA group (mean 1.3, standard deviation [SD] 2.5) to LRA (mean 1.2, SD 2.1) and between LRA and D + LRA (mean 0.9, SD 2.1). Procedure time (time of skin incision to closure) and total room time were comparable among all three anesthesia groups (LRA 2.2 hr, SD 2.2; GETA 2.1 hr, SD 0.5; LRA + Dex 2.1 hr, SD 0.5). CONCLUSIONS: The use of dexmedetomidine in addition to LRA is a safe and acceptable alternative to conventional GETA or LRA alone in CEA with shorter length of hospital stay when compared with GETA, improved patient tolerance based on physician observation, and similar rates of immediate and short-term complications and postoperative pain scores.

Machine Learning Identification of Modifiable Predictors of Patient Outcomes After Transcatheter Aortic Valve Replacement.

Background: Transcatheter aortic valve replacement (TAVR) is an important treatment option for patients with severe symptomatic aortic stenosis. It is important to identify predictors of excellent outcomes (good clinical outcomes, more time spent at home) after TAVR that are potentially amenable to improvement. Objectives: The purpose of the study was to use machine learning to identify potentially modifiable predictors of clinically relevant patient-centered outcomes after TAVR. Methods: We used data from 8,332 TAVR cases (January 2016-December 2021) from 21 hospitals to train random forest models with 57 patient characteristics (demographics, comorbidities, surgical risk score, lab values, health status scores) and care process parameters to predict the end point, a composite of parameters that designated an excellent outcome and included no major complications (in-hospital or at 30 days), post-TAVR length of stay of 1 day or less, discharge to home, no readmission, and alive at 30 days. We used recursive feature elimination with cross-validation and Shapley Additive Explanation feature importance to identify parameters with the highest predictive values. Results: The final random forest model retained 29 predictors (15 patient characteristics and 14 care process components); the area under the curve, sensitivity, and specificity were 0.77, 0.67, and 0.73, respectively. Four potentially modifiable predictors with relatively high Shapley Additive Explanation values were identified: type of anesthesia, direct movement to stepdown unit post-TAVR, time between catheterization and TAVR, and preprocedural length of stay. Conclusions: This study identified four potentially modifiable predictors of excellent outcome after TAVR, suggesting that machine learning combined with hospital-level data can inform modifiable components of care, which could support better delivery of care for patients undergoing TAVR.

Early emergency department discharge for intermediate heart score patients presenting for chest pain.

Study Objective: The use of the HEART score to risk stratify patients for short-term major adverse cardiac events in the emergency department (ED) setting is well established. Although discharge to home for low-risk HEART score patients is widely accepted as safe practice, there are limited outcomes data on moderate-risk HEART score patients discharged to home. We investigated the safety of discharging moderate-risk HEART score patients to home from the ED with established early cardiology follow-up. Methods: We performed a retrospective cohort analysis of patients presenting to the ED with chest pain from April 2020 through December 2020. Patients were evaluated in the ED and underwent serial conventional troponin testing and electrocardiogram (ECG). Clinicians calculated a HEART score and employed shared decision-making with moderate-risk patients (score 4-6), offering hospital admission versus discharge home with a formalized process for rapid cardiology follow-up (within 2 business days). We assessed the frequency of acute myocardial infarction or death at 30 days and before cardiology follow-up. Results: During our study period, 2939 patient encounters were screened for chest pain. Of these, 333 of 547 eligible moderate-risk HEART score patients were referred for rapid follow-up. The median time to follow-up appointment was 2.9 business days (interquartile range 1.3, 6.5), and 264 (79%) of patients kept their follow-up appointment. One patient (0.3%) suffered death within 30 days, before cardiology follow-up. There were no myocardial infarctions. Conclusions: These results suggest that moderate-risk HEART score patients may be considered for discharge from the ED with rapid cardiology follow-up. Formalizing processes to facilitate these early evaluations may represent a viable alternative to hospital admission, without diminishing patient outcomes.

Outcomes and Direct Cost of Isolated Nonemergent CABG in Patients With Low Ejection Fraction.

OBJECTIVE: Preoperative left ventricular ejection fraction (LVEF) is one of the main predictors of outcomes in cardiac surgery. We present current era outcomes and associated direct cost in nonemergent isolated coronary artery bypass surgery (CABG) patients with LVEF <20% over the past 6 years and compare it with higher EF subgroups. METHODS: Six-year data from 2016 to 2022 at hospitals sharing Society of Thoracic Surgeons and financial data with Biome Analytics were analyzed based on 3 EF subgroups (EF ≤20%, EF 21% to 35%, and EF >35%). Outcomes and costs were assessed. RESULTS: Overall 30-day mortality of 12,649 patients was 1.9%. The EF ≤20% (n = 248), EF 21% to 35% (n = 1,408), and EF >35 (n = 10,993) cohorts had mortality of 6.9%, 3.7%, and 1.6%, respectively. The EF ≤20% subgroup had higher use of cardiopulmonary bypass, blood products, and mechanical support. In addition, the EF ≤20% subgroup had higher complication rates in almost all measured categories. Also, the EF ≤20% cohort had significantly higher length of stay, intensive care unit (ICU) hours, ICU and hospital readmissions, and lowest discharge to home rate. The strongest factors associated with mortality were postoperative cardiac arrest, renal failure requiring dialysis, extracorporeal membrane oxygenation, sepsis, prolonged ventilation, and gastrointestinal event. The overall median direct cost of care was $37,387.79 ($27,605.18, $51,720.96), with a median direct cost of care in the EF ≤20%, EF 21% to 35%, and EF >35% subgroups of $52,500.17 ($34,103.52, $80,806.79), $44,108.32 ($31,597.58, $63,788.03), and $36,521.80 ($27,168.91, $50,019.31), respectively. CONCLUSIONS: In nonemergent isolated CABG surgery, low EF continues to have higher surgical risks and higher direct cost of care despite advances in cardiovascular care.

Development of the Socioeconomic Screening, Active Engagement, Follow-up, Education, Discharge Readiness, and Consistency (SAFEDC) Model for Improving Transitions of Care: Participatory Design.

BACKGROUND: Transition to home after hospitalization involves the potential risk of adverse patient events, such as knowledge deficits related to self-care, medication errors, and readmissions. Despite broad organizational efforts to provide better care transitions for patients, there are challenges in implementing interventions that effectively improve care transition outcomes, as evidenced by readmission rates. Collaborative efforts that require health care professionals, patients, and caregivers to work together are necessary to identify gaps associated with transitions of care and generate effective transitional care interventions. OBJECTIVE: This study aims to understand the usefulness of participatory design approaches in identifying the design implications of transition of care interventions in health care settings. Through a series of participatory design workshops, we have brought stakeholders of the health care system together. With a shared understanding of care transition and patient experience, we have provided participants with opportunities to generate possible design implications for care transitions. METHODS: We selected field observations in clinical settings and participatory design workshops to develop transitional care interventions that serve each hospital's unique situation and context. Patient journey maps were created and functioned as tools for creating a shared understanding of the discharge process across different stakeholders in the health care environment. The intervention sustainability was also assessed. By applying thematic analysis methods, we analyzed the problem statements and proposed interventions collected from participatory design workshops. The findings showed patterns of major discussion during the workshop. RESULTS: On the basis of the workshop results, we formalized the transition of care model-the socioeconomic, active engagement, follow-up, education, discharge readiness tool, and consistency (Integrated Michigan Patient-centered Alliance in Care Transitions transition of care model)-which other organizations can apply to improve patient experiences in care transition. This model highlights the most significant themes that should necessarily be considered to improve the transition of care. CONCLUSIONS: Our study presents the benefits of the participatory design approach in defining the challenges associated with transitions of care related to patient discharge and generating sustainable interventions to improve care transitions.