Preoperative alcohol interventions for elective surgical patients: Results from a randomized pilot trial

Study protocol for a sequential multiple assignment randomized trial to decrease alcohol use before and after surgery

BACKGROUND

High-risk alcohol consumption in the weeks before and after surgery poses significant risks for postoperative recovery. Despite this, elective surgical patients are rarely offered alcohol-focused education, interventions, or treatment. This paper describes the protocol of a research study designed to evaluate the effectiveness of brief, non-pharmacological, therapeutic approaches to reduce alcohol use before and after surgery.

METHODS

The Alcohol Screening and Preoperative Intervention Research (ASPIRE-2) study trial includes 440 elective, non-cancer, surgery patients ages 21-75 years-old who report high-risk alcohol use. This trial uses a Sequential, Multiple Assignment, Randomized Trial (SMART) design to test the effectiveness of adaptive interventions that include preoperative Virtual Health Coaching (VHC) or Enhanced Usual Care (EUC) followed by postoperative intervention strategies tailored to participant response to the preoperative study condition. Intervention "response" is defined as achieving low-risk alcohol use following the preoperative intervention. The primary aims of this study are to: 1) examine the effectiveness of adaptive interventions that begin with preoperative VHC compared to EUC in reducing high-risk alcohol use among elective surgical patients; and 2) identify the most effective postoperative strategy for lasting alcohol use reduction over a period of 12 months. Secondary and exploratory aims will identify the best performing pre-specified adaptive interventions, identify baseline and time-varying moderators of intervention effectiveness, and evaluate surgical outcomes.

CONCLUSION

The ASPIRE-2 study is an innovative approach to develop adaptive interventions to reduce alcohol use proximal to elective surgery when alcohol use poses short- and long-term risks to surgery and health.

Incidence of Hospitalizations Involving Alcohol Withdrawal Syndrome in a Primary Care Population

Importance

Alcohol withdrawal syndrome (AWS) is an important cause and complication of hospitalizations. Although common and preventable, the incidence of AWS during hospitalizations is poorly described.

Objective

To evaluate the incidence and proportional incidence of hospitalizations involving AWS in an adult primary care population overall and across patient characteristics.

Design, Setting, and Participants

This retrospective cohort study used electronic health records and insurance claims from Kaiser Permanente Washington (KPWA) between July 1, 2018, and June 30, 2022. The study included adults with 1 or more primary care visits during this period or the year prior, where primary care included annual standardized alcohol screening using the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C).

Exposures

Age, sex, race, Hispanic ethnicity, AUDIT-C scores, and comorbid diagnoses.

Main Outcome and Measures

Hospitalizations involving AWS were defined by diagnosis codes documented during hospitalizations (incidence numerator). Time enrolled in KPWA determined person-enrolled-years (incidence denominator). Proportional incidence was calculated as the incidence of hospitalizations involving AWS divided by the incidence of all-cause hospitalizations. Proportional incidence was also estimated for hospitalizations involving other common chronic conditions (chronic obstructive pulmonary disease, diabetes, heart failure, and hypertension), which were also defined using hospital diagnosis codes.

Results

Among 544 825 adults engaged in primary care (mean [SD] age, 47.0 [17.9] years; 310 069 [56.9%] female; 3656 [0.7%] American Indian or Alaska Native, 55 206 [10.1%] Asian, 25 406 [4.7%] Black, 5204 [1.0%] Native Hawaiian or Other Pacific Islander, 365 780 [67.1%] White, 19 791 [3.6%] multiracial, 15 963 [2.9%] other races, and 53 819 [9.9%] unknown race; 33 987 [6.2%] Hispanic, 414 269 [76.0%] not Hispanic, and 96 569 [17.7%] unknown ethnicity), incidence of hospitalizations involving AWS was 169 (95% CI, 159-179) per 100 000 person-enrolled-years overall but as high as 15 347 (95% CI, 13 502-17 331) in patients with other alcohol-attributable diagnoses. The proportional incidence of hospitalizations involving AWS was 2.3% overall, with variation by age, sex, and AUDIT-C scores (eg, 9%-11% in male patients aged 30-49 years and 23%-44% in patients with high-risk AUDIT-C scores of 7-12 points). In most cases, among adults younger than 60 years, proportional incidence of hospitalizations involving AWS matched or surpassed that of other common chronic conditions (chronic obstructive pulmonary disease, diabetes, heart failure, and hypertension).

Conclusions and Relevance

In this cohort study of a large primary care population served by an integrated health system, AWS hospitalizations were common, especially in male patients, younger age groups, and individuals with high-risk alcohol use. During hospitalizations, the burden of AWS was similar to or exceeded complications of other chronic diseases that receive greater medical attention.

Identification of Alcohol Use Prior to Major Cancer Surgery: Timeline Follow Back Interview Compared to Four Other Markers

BACKGROUND

The postoperative complication rate is 30-64% among patients undergoing muscle-invasive and recurrent high-risk non-muscle-invasive bladder cancer surgery. Preoperative risky alcohol use increases the risk. The aim was to evaluate the accuracy of markers for identifying preoperative risky alcohol.

METHODS

Diagnostic test sub-study of a randomized controlled trial (STOP-OP trial), based on a cohort of 94 patients scheduled for major bladder cancer surgery. Identification of risky alcohol use using Timeline Follow Back interviews (TLFB) were compared to the AUDIT-C questionnaire and three biomarkers: carbohydrate-deficient transferrin in plasma (P-CDT), phosphatidyl-ethanol in blood (B-PEth), and ethyl glucuronide in urine (U-EtG).

RESULTS

The correlation between TLFB and AUDIT-C was strong (ρ = 0.75), while it was moderate between TLFB and the biomarkers (ρ = 0.55-0.65). Overall, sensitivity ranged from 56 to 82% and specificity from 38 to 100%. B-PEth showed the lowest sensitivity at 56%, but the highest specificity of 100%. All tests had high positive predictive values (79-100%), but low negative predictive values (42-55%).

CONCLUSIONS

Despite high positive predictive values, negative predictive values were weak compared to TLFB. For now, TLFB interviews seem preferable for preoperative identification of risky alcohol use.

Automated-detection of risky alcohol use prior to surgery using natural language processing

BACKGROUND

Preoperative risky alcohol use is one of the most common surgical risk factors. Accurate and early identification of risky alcohol use could enhance surgical safety. Artificial Intelligence-based approaches, such as natural language processing (NLP), provide an innovative method to identify alcohol-related risks from patients' electronic health records (EHR) before surgery.

METHODS

Clinical notes (n = 53,629) from pre-operative patients in a tertiary care facility were analyzed for evidence of risky alcohol use and alcohol use disorder. One hundred of these records were reviewed by experts and labeled for comparison. A rule-based NLP model was built, and we assessed the clinical notes for the entire population. Additionally, we assessed each record for the presence or absence of alcohol-related International Classification of Diseases (ICD) diagnosis codes as an additional comparator.

RESULTS

NLP correctly identified 87% of the human-labeled patients classified with risky alcohol use. In contrast, diagnosis codes alone correctly identified only 29% of these patients. In terms of specificity, NLP correctly identified 84% of the non-risky cohort, while diagnosis codes correctly identified 90% of this cohort. In the analysis of the full dataset, the NLP-based approach identified three times more patients with risky alcohol use than ICD codes.

CONCLUSIONS

NLP, an artificial intelligence-based approach, efficiently and accurately identifies alcohol-related risk in patients' EHRs. This approach could supplement other alcohol screening tools to identify patients in need of intervention, treatment, and/or postoperative withdrawal prophylaxis. Alcohol-related ICD diagnosis had limited utility relative to NLP, which extracts richer information within clinical notes to classify patients.

Perioperative Concerns in the Patient with History of Alcohol Use

Alcohol use is common in patients presenting for surgery and can result in significant physiologic changes and postoperative complications. Anesthesia providers must be aware of the potential risks associated with alcohol consumption and take steps to minimize them. Perioperative management includes assessing patients for alcohol use, providing alcohol cessation interventions, adjusting the anesthetic plan according to the patient's alcohol use history, providing appropriate pain management strategies, and closely monitoring patients during and after surgery for signs of alcohol withdrawal.

Reducing Alcohol Use Before and After Surgery: Qualitative Study of Two Treatment Approaches

BACKGROUND

High-risk alcohol use is a common preventable risk factor for postoperative complications, admission to intensive care, and longer hospital stays. Short-term abstinence from alcohol use (2 to 4 weeks) prior to surgery is linked to a lower likelihood of postoperative complications.

OBJECTIVE

The study aimed to explore the acceptability and feasibility of 2 brief counseling approaches to reduce alcohol use in elective surgical patients with high-risk alcohol use in the perioperative period.

METHODS

A semistructured interview study was conducted with a group of "high responders" (who reduced alcohol use ≥50% postbaseline) and "low responders" (who reduced alcohol use by ≤25% postbaseline) after their completion of a pilot trial to explore the acceptability and perceived impacts on drinking behaviors of the 2 counseling interventions delivered remotely by phone or video call. Interview transcripts were analyzed using thematic analysis.

RESULTS

In total, 19 participants (10 high responders and 9 low responders) from the parent trial took part in interviews. Three main themes were identified: (1) the intervention content was novel and impactful, (2) the choice of intervention modality enhanced participant engagement in the intervention, and (3) factors external to the interventions also influenced alcohol use.

CONCLUSIONS

The findings support the acceptability of both high- and low-intensity brief counseling approaches. Elective surgical patients are interested in receiving alcohol-focused education, and further research is needed to test the effectiveness of these interventions in reducing drinking before and after surgery.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03929562; https://clinicaltrials.gov/ct2/show/NCT03929562.