Jose, Thulasee

Abstract Introduction We determined whether a tobacco cessation intervention targeting brief perioperative abstinence (“quit for a bit”) increased engagement of surgical patients with treatment compared with an intervention targeting long-term postoperative abstinence (“quit for good”). Aims and Methods Surgical patients who smoke were stratified according to intended duration of postoperative abstinence, and then randomized within strata to receive either a “quit for a bit” or a “quit for good” intervention. Both employed initial brief counseling and short message service (SMS) to deliver treatment up to 30 days after surgery. The primary outcome of treatment engagement was defined as the rate at which subjects actively responded to system requests delivered via SMS. Results The engagement index did not differ between intervention groups (median [25th, 75th] of 23.7% [8.8, 46.0] for “quit for a bit” group (n = 48) and 22.2% [4.8, 46.0] for “quit for good” group (n = 50), p = .74), nor did the proportion of patients continuing SMS use after study completion (33% and 28%, respectively). Exploratory abstinence outcomes on the morning of surgery and 7 and 30 days after surgery did not differ between groups. Program satisfaction was high in both groups and did not differ. There was no significant interaction between intended abstinence duration and any outcome, ie, alignment of intent with intervention did not affect engagement. Conclusions Tobacco cessation treatment delivered via SMS was well accepted by surgical patients. Tailoring an SMS intervention to focus on the benefits of short-term abstinence for surgical patients did not increase engagement in treatment or perioperative abstinence rates. Implications Treatment of surgical patients for tobacco use is efficacious and reduces postoperative complications. However, implementation in clinical practice has proved challenging, and new methods of engaging these patients in cessation treatment are needed. We found that tobacco use treatment delivered via SMS was feasible and well utilized by surgical patients. Tailoring an SMS intervention to focus on the benefits of short-term abstinence for surgical patients did not increase engagement in treatment or perioperative abstinence rates. Clinical Trial Number NCT03839043. Registry URL: https://clinicaltrials.gov/ct2/show/NCT03839043

Background This study aims to assess the association of postoperative stroke with intraoperative hemodynamic variability and transfusion management. Methods In this case-control study, adult patients (≥ 18 years) who had a stroke within 72 hours of a surgical procedure were matched to 2 control patients according to age, sex, and procedure type. Primary risk factors assessed were intraoperative fluid administration, blood product transfusion, vasopressor use, and measures of variability in systolic and diastolic blood pressure and heart rate: maximum, minimum, range, SD, and average real variability. The variables were analyzed with conditional logistic regression, which accounted for the 1:2 matched case-control study design. Results Among 687 581 procedures, we identified 64 postoperative strokes (incidence, 9.3 [95% CI, 7.2-11.9] strokes per 100 000 procedures). These cases were matched with 128 controls. Stroke cases had higher Charlson cmorbidity index scores than did controls (P = .046). Blood pressure and heart rate variability measures were not associated with stroke. The risk of stroke was increased with red blood cell (RBC) transfusion (odds ratio [OR], 14.82; 95% CI, 3.40-64.66; P < .001), vasopressor use (OR, 3.91; 95% CI, 1.59-9.60; P = .003), and longer procedure duration (OR, 1.23/h; 95% CI, 1.01-1.51; P = .04). Multivariable analysis of procedure duration, RBC transfusion, and vasopressor use showed that only RBC transfusion was independently associated with an increased risk of stroke (OR, 10.10; 95% CI, 2.14-47.72; P = .004). Conclusions Blood pressure variability was not associated with an increased risk of postoperative stroke; however, RBC transfusion was an independent risk factor.

AbstractIntroductionAvailable evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown.MethodsElectronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission.ResultsCurrent (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06–1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04–1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50–0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16–0.66) and former smokers (aOR, 0.47; 95% CI, 0.39–0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66–0.83) than never smokers (aOR, 0.87; 95% CI, 0.79–0.97).ConclusionsFormer but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers.ImplicationsPrior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

Abstract Background: There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics. Methods: Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined. Results: 6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46–1.70] and 1.04 (95% CI, 0.96–1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53–0.90). Conclusions: Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types. Impact: This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3

Abstract Introduction Continued cigarette smoking is a critical determinant of outcome in oncology patients, but how the separate events of cancer diagnosis, cancer treatment, and completion of treatment affect smoking behavior in cancer survivors is unknown. This study described such changes, hypothesizing that they would be more pronounced for smoking-related cancers. Methods The Cancer Patient Tobacco Use Questionnaire (CTUQ) was sent to every cancer patient ≥ 18 y old scheduled for outpatient visits at the Mayo Clinic Cancer Center with a current or former history of tobacco use. Results From September 2019 to September 2020, 33,831 patients received the CTUQ, and 20,818 (62%) responded. Of the 3007 current smokers analyzed, 34% quit at diagnosis; those with smoking-related cancers were more likely to quit (40% vs. 29%, respectively, p &lt; .001). Among those who did not quit at diagnosis, 31% quit after starting cancer treatment, and those with smoking-related cancers were more likely to quit (35% and 28%, respectively, p = .002) Among those who had quit before the completion of treatment, 13% resumed smoking after treatment ended. In multivariable analysis, patients with smoking-related cancers were more likely to report 30-d point prevalence abstinence from pre-diagnosis to the completion of treatment (adjusted OR 1.98 [95% CI 1.65, 2.36], p &lt; .001). Conclusions Both cancer diagnosis and treatment prompt smoking abstinence, with most maintaining abstinence after treatment is completed. Those with smoking-related cancers are more likely to quit. These results emphasize the need to provide access to tobacco treatment services that can further support cancer patients who smoke. Implications Approximately one-third of cancer patients who smoke quit smoking at the time of diagnosis, an additional one-third of patients who had not yet quit did so at the initiation of treatment, and most sustained this abstinence after treatment completion. Patients with smoking-related cancers are more likely to quit. Thus, there are multiple opportunities within the cancer care continuum to intervene and support quit attempts or continued abstinence.

Objective: To evaluate the performance of an Electronic Health Record (EHR) integrated risk score for COVID-19 positive outpatients to predict 30-day risk of hospitalization. Patients and Methods: A retrospective observational study of 67 470 patients with COVID-19 confirmed by polymerase chain reaction (PCR) test between March 12, 2020 and February 8, 2021. Risk scores were calculated based on data in the chart at the time of the incident infection. Results: The Mayo Clinic COVID-19 risk score consisted of 13 components included age, sex, chronic lung disease, congenital heart disease, congestive heart failure, coronary artery disease, diabetes mellitus, end stage liver disease, end stage renal disease, hypertension, immune compromised, nursing home resident, and pregnant. Univariate analysis showed all components, except pregnancy, have significant ( P < .001) association with admission. The Mayo Clinic COVID-19 risk score showed a Receiver Operating Characteristic Area Under Curve (AUC) of 0.837 for the prediction of admission for this large cohort of COVID-19 positive patients. Conclusion: The Mayo Clinic COVID-19 risk score is a simple score that is easily integrated into the EHR with excellent predictive performance for severe COVID-19. It can be leveraged to stratify risk for severe COVID-19 at initial contact, when considering therapeutics or in the allocation of vaccine supply.

This analysis tested the hypothesis that current e-cigarette use was associated with an increased risk of SARS-CoV-2 infection in patients seeking medical care. E-cigarette and conventional cigarette use were ascertained using a novel electronic health record tool, and COVID-19 diagnosis was ascertained by a validated institutional registry. Logistic regression models were fit to assess whether current e-cigarette use was associated with an increased risk of COVID-19 diagnosis. A total of 69,264 patients who were over the age of 12 years, smoked cigarettes or vaped, and were sought medical care at Mayo Clinic between September 15, 2019 and November 30, 2020 were included. The average age was 51.5 years, 62.1% were females and 86.3% were white; 11.1% were currently smoking cigarettes or using e-cigarettes and 5.1% tested positive for SARS-CoV-2. Patients who used only e-cigarettes were not more likely to have a COVID-19 diagnosis (OR 0.93 [0.69-1.25], P = .628), whereas those who used only cigarettes had a decreased risk (OR 0.43 [0.35-0.53], P < .001). The OR for dual users fell between these 2 values (OR 0.67 [0.49-0.92], P = .013). Although e-cigarettes have the well-documented potential for harm, they do not appear to increase susceptibility to SARS-CoV-2 infection. This result suggests the hypothesis that any beneficial effects of conventional cigarette smoking on susceptibility are not mediated by nicotine.

The use of electronic cigarettes (e-cigarettes) can affect patient health and clinical care. However, the current documentation of e-cigarette use in the electronic health records (EHR) is inconsistent. This report outlines how the ambulatory clinical practices of a large U.S. hospital system optimized its electronic health records (EHR) framework to better record e-cigarettes used by patients. The new EHR section for e-cigarette information was implemented for outpatient appointments. During a 30-week evaluation period post-implementation, 638,804 patients (12 yrs and older) completed ambulatory appointments within the health system; of these, the new section contained e-cigarette use information for 37,906 (6%) patients. Among these patients, 1005 (2.7%) were identified as current e-cigarette users (current every day or current some day e-cigarette use), 941 (2.5%) were reported as former e-cigarette users, and 35,960 (94%) had never used e-cigarettes. A separate EHR section to document e-cigarette use is feasible within existing clinical practice models. Utilization of the new section was modest in routine clinical practice, indicating the need for more intensive implementation strategies that emphasize the health effects of e-cigarette use, and how consistent ascertainment could improve clinical practice.

Continued tobacco use after cancer diagnosis is detrimental to treatment and survivorship. The current reach of evidence-based tobacco treatments in cancer patients is low. As a part of the National Cancer Institute Cancer Center Cessation Initiative, the Mayo Clinic Cancer Center designed an electronic health record (EHR, Epic©)-based process to automatically refer ambulatory oncology patients to tobacco use treatment, regardless of intent to cease tobacco use(“opt out”). The referral and patient scheduling, accomplished through a best practice advisory (BPA) directed to staff who room patients, does not require a co-signature from clinicians. This process was piloted for a six-week period starting in July of 2019 at the Division of Medical Oncology, Mayo Clinic, Rochester, MN. All oncology patients who were tobacco users were referred for tobacco treatment by the rooming staff (n = 210). Of these, 150 (71%) had a tobacco treatment appointment scheduled, and 25 (17%) completed their appointment. We conclude that an EHR-based “opt-out” approach to refer patients to tobacco dependence treatment that does not require active involvement by clinicians is feasible within the oncology clinical practice. Further work is needed to increase the proportion of scheduled patients who attend their appointments.