The Incidence and Outcomes of Breast Implants Among 1696 Women over more than 50 Years.

OBJECTIVE: To investigate the incidence of women with breast implants in 1964-2017 MATERIALS AND METHODS: All women with breast implants in Olmsted County, MN between January 1, 1992 and December 31, 2017 were identified, and a comprehensive review of individual medical records was performed, adding to a previously identified cohort of women with breast implants in 1964-1991. Incidence rates were calculated and were age- and sex-adjusted to the US white female 2010 population. RESULTS: In 1992-2017, 948 women with breast implants were identified, totaling 1696 Olmsted County, MN women with breast implants in 1964-2017. Overall incidence was 63.3 (95% CI 60.2-66.4) per 100,000 women, but incidence varied significantly over time. Women in 1964-1991 were more likely to have implants for cosmetic reasons and more likely to have silicone implants compared to the 1992-2017 cohort. The overall standardized mortality ratio was 1.17 (95% CI 0.99-1.38) in 1964-1991 and 0.94 (95% CI 0.66-1.29) in 1992-2017. In 1992-2017, breast reconstruction patients had a significantly elevated risk of implant rupture and implant removal versus breast augmentation patients. CONCLUSION: The incidence of breast implants among women in Olmsted County, MN has varied drastically over the past five decades, with significant changes in the trends for implant type and reason. The findings of this study may provide further insight regarding how risks associated with implants may vary over time. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Smoking Behaviors Among Indigenous Pregnant People Compared to a Matched Regional Cohort.

INTRODUCTION: Smoking commercial tobacco products is highly prevalent in American Indian and Alaska Native (Indigenous) pregnancies. This disparity directly contributes to maternal and fetal mortality. Our objective was to describe cigarette smoking prevalence, cessation intervention uptake, and cessation behaviors of pregnant Indigenous people compared to sex and age-matched regional cohort. AIMS AND METHODS: Pregnancies from an Indigenous cohort in Olmsted County, Minnesota, identified in the Rochester Epidemiology Project, were compared to pregnancies identified in a sex and age-matched non-Indigenous cohort from 2006 to 2019. Smoking status was defined as current, former, or never. All pregnancies were reviewed to identify cessation interventions and cessation events. The primary outcome was smoking prevalence during pregnancy, with secondary outcomes measuring uptake of smoking cessation interventions and cessation. RESULTS: The Indigenous cohort included 57 people with 81 pregnancies, compared to 226 non-Indigenous people with 358 pregnancies. Smoking was identified during 45.7% of Indigenous pregnancies versus 11.2% of non-Indigenous pregnancies (RR: 3.25, 95% CI = 1.98-5.31, p ≤ .0001). Although there was no difference in uptake of cessation interventions between cohorts, smoking cessation was significantly less likely during Indigenous pregnancies compared to non-Indigenous pregnancies (OR: 0.23, 95% CI = 0.07-0.72, p = .012). CONCLUSIONS: Indigenous pregnant people in Olmsted County, Minnesota were more than three times as likely to smoke cigarettes during pregnancy compared to the non-indigenous cohort. Despite equivalent uptake of cessation interventions, Indigenous people were less likely to quit than non-Indigenous people. Understanding why conventional smoking cessation interventions were ineffective at promoting cessation during pregnancy among Indigenous women warrants further study. IMPLICATIONS: Indigenous pregnant people in Olmsted County, Minnesota, were greater than three times more likely to smoke during pregnancy compared to a regional age matched non-Indigenous cohort. Although Indigenous and non-Indigenous pregnant people had equivalent uptake of cessation interventions offered during pregnancy, Indigenous people were significantly less likely to quit smoking before fetal delivery. This disparity in the effectiveness of standard of care interventions highlights the need for further study to understand barriers to cessation in pregnant Indigenous people.

Indigenous Smoking Behaviors in Olmsted County, Minnesota: A Longitudinal Population-Based Study.

OBJECTIVE: To describe smoking behaviors and pharmaceutical cessation aid uptake in a population-based Indigenous cohort compared with an age- and sex-matched non-Indigenous cohort. PATIENTS AND METHODS: Using the health record-linkage system of the Rochester Epidemiology Project (January 1, 2006, to December 31, 2019), smoking data of Indigenous residents of Olmsted County in Minnesota were abstracted to define the smoking prevalence, incidence, cessation, relapse after cessation, and pharmaceutical smoking cessation aid uptake compared with a matched non-Indigenous cohort. Prevalence was analyzed with a modified Poisson regression; cessation and relapse were evaluated with generalized estimating equations. Incidence was evaluated with a Cox proportional hazards model. RESULTS: Smoking prevalence was higher in the Indigenous cohort (39.0% to 47.0%; n=898) than the matched cohort (25.6% to 30.3%; n=1780). Pharmaceutical uptake was higher among the Indigenous cohort (35.8% of n=584 ever smokers vs 16.3% of n=778 ever smokers; P<.001). Smoking cessation events occurred more frequently in the Indigenous cohort (relative risk, 1.10; 95% CI, 1.06 to 1.13; P<.001). Indigenous former smokers were more likely to resume smoking (relative risk, 3.03; 95% CI, 2.93 to 3.14; P<.001) compared with the matched cohort. These findings were independent of socioeconomic status, age, and sex. CONCLUSION: Smoking in this Indigenous cohort was more prevalent compared with a sex- and age-matched non-Indigenous cohort despite more smoking cessation events and higher use of smoking cessation aids in the Indigenous cohort. The relapse rate after achieving cessation in the Indigenous cohort was more than three times higher than the non-Indigenous cohort. This finding has not been previously described and represents a potential target for relapse prevention efforts in US Indigenous populations.

Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial.

BACKGROUND: Previous atrial fibrillation screening trials have highlighted the need for more targeted approaches. We did a pragmatic study to evaluate the effectiveness of an artificial intelligence (AI) algorithm-guided targeted screening approach for identifying previously unrecognised atrial fibrillation. METHODS: For this non-randomised interventional trial, we prospectively recruited patients with stroke risk factors but with no known atrial fibrillation who had an electrocardiogram (ECG) done in routine practice. Participants wore a continuous ambulatory heart rhythm monitor for up to 30 days, with the data transmitted in near real time through a cellular connection. The AI algorithm was applied to the ECGs to divide patients into high-risk or low-risk groups. The primary outcome was newly diagnosed atrial fibrillation. In a secondary analysis, trial participants were propensity-score matched (1:1) to individuals from the eligible but unenrolled population who served as real-world controls. This study is registered with ClinicalTrials.gov, NCT04208971. FINDINGS: 1003 patients with a mean age of 74 years (SD 8·8) from 40 US states completed the study. Over a mean 22·3 days of continuous monitoring, atrial fibrillation was detected in six (1·6%) of 370 patients with low risk and 48 (7·6%) of 633 with high risk (odds ratio 4·98, 95% CI 2·11-11·75, p=0·0002). Compared with usual care, AI-guided screening was associated with increased detection of atrial fibrillation (high-risk group: 3·6% [95% CI 2·3-5·4] with usual care vs 10·6% [8·3-13·2] with AI-guided screening, p<0·0001; low-risk group: 0·9% vs 2·4%, p=0·12) over a median follow-up of 9·9 months (IQR 7·1-11·0). INTERPRETATION: An AI-guided targeted screening approach that leverages existing clinical data increased the yield for atrial fibrillation detection and could improve the effectiveness of atrial fibrillation screening. FUNDING: Mayo Clinic Robert D and Patricia E Kern Center for the Science of Health Care Delivery.

Association Between Area-Level Socioeconomic Deprivation and Diabetes Care Quality in US Primary Care Practices.

Importance: Diabetes management operates under a complex interrelationship between behavioral, social, and economic factors that affect a patient's ability to self-manage and access care. Objective: To examine the association between 2 complementary area-based metrics, area deprivation index (ADI) score and rurality, and optimal diabetes care. Design, Setting, and Participants: This cross-sectional study analyzed the electronic health records of patients who were receiving care at any of the 75 Mayo Clinic or Mayo Clinic Health System primary care practices in Minnesota, Iowa, and Wisconsin in 2019. Participants were adults with diabetes aged 18 to 75 years. All data were abstracted and analyzed between June 1 and November 30, 2020. Main Outcomes and Measures: The primary outcome was the attainment of all 5 components of the D5 metric of optimal diabetes care: glycemic control (hemoglobin A1c <8.0%), blood pressure (BP) control (systolic BP <140 mm Hg and diastolic BP <90 mm Hg), lipid control (use of statin therapy according to recommended guidelines), aspirin use (for patients with ischemic vascular disease), and no tobacco use. The proportion of patients receiving optimal diabetes care was calculated as a function of block group-level ADI score (a composite measure of 17 US Census indicators) and zip code-level rurality (calculated using Rural-Urban Commuting Area codes). Odds of achieving the D5 metric and its components were assessed using logistic regression that was adjusted for demographic characteristics, coronary artery disease history, and primary care team specialty. Results: Among the 31 934 patients included in the study (mean [SD] age, 59 [11.7] years; 17 645 men [55.3%]), 13 138 (41.1%) achieved the D5 metric of optimal diabetes care. Overall, 4090 patients (12.8%) resided in the least deprived quintile (quintile 1) of block groups and 1614 (5.1%) lived in the most deprived quintile (quintile 5), while 9193 patients (28.8%) lived in rural areas and 2299 (7.2%) in highly rural areas. The odds of meeting the D5 metric were lower for individuals residing in quintile 5 vs quintile 1 block groups (odds ratio [OR], 0.72; 95% CI, 0.67-0.78). Patients residing in rural (OR, 0.84; 95% CI, 0.73-0.97) and highly rural (OR, 0.81; 95% CI, 0.72-0.91) zip codes were also less likely to attain the D5 metric compared with those in urban areas. Conclusions and Relevance: This cross-sectional study found that patients living in more deprived and rural areas were significantly less likely to attain high-quality diabetes care compared with those living in less deprived and urban areas. The results call for geographically targeted population health management efforts by health systems, public health agencies, and payers.

Incidence of Clinically Relevant Thyroid Cancers Remains Stable for Almost a Century: A Population-Based Study.

OBJECTIVE: To examine the trends in incidence of clinically relevant thyroid cancers within the overall rising incidence of thyroid cancers. PATIENTS AND METHODS: This is a population-based cohort study conducted using the Rochester Epidemiology Project database to identify all new cases of thyroid cancer in Olmsted County, Minnesota, between January 1, 1935, and December 31, 2018. We extracted information about demographics and tumor pathologic type, size, and invasiveness. Clinically relevant cancers included aggressive histology or presence of metastatic disease, size larger than 4 cm, and gross extrathyroidal tumor invasion. RESULTS: Between 1935 and 2018, 596 thyroid cancer cases were diagnosed (mean age, 46.4 years; 72% female; 87% papillary cancers; and median tumor size, 1.5 cm). The sex- and age-adjusted incidence of thyroid cancer increased from 1.3 per 100,000 person-years (p-y) from 1935-1949 to 12.0 per 100,000 p-y in 2010-2018, corresponding to an absolute change per decade of 1.4 (95% CI, 0.7 to 2.2). There was a nonsignificant period absolute change for patients with tumor greater than 4 cm (0.03; 95% CI, -0.2 to 0.3), with evidence of tumor invasion (0.1; 95% CI, -0.1 to 0.4), and with aggressive histology or presence of metastatic disease (0.2; 95% CI, -0.1 to 0.6). Thyroid cancer mortality was unchanged over the observation period. CONCLUSION: Incidence rates of clinically relevant thyroid cancers, as defined by histology, size, and invasiveness, have not changed significantly in 80 years. The rising thyroid cancer incidence is driven by indolent thyroid cancers.

Association of Neighborhood Measures of Social Determinants of Health With Breast, Cervical, and Colorectal Cancer Screening Rates in the US Midwest.

Importance: Despite advances in cancer treatment and cancer-related outcomes, disparities in cancer mortality remain. Lower rates of cancer prevention screening and consequent delays in diagnosis may exacerbate these disparities. Better understanding of the association between area-level social determinants of health and cancer screening may be helpful to increase screening rates. Objective: To examine the association between area deprivation, rurality, and screening for breast, cervical, and colorectal cancer in patients from an integrated health care delivery system in 3 US Midwest states (Minnesota, Iowa, and Wisconsin). Design, Setting, and Participants: In this cross-sectional study of adults receiving primary care at 75 primary care practices in Minnesota, Iowa, and Wisconsin, rates of recommended breast, cervical, and colorectal cancer screening completion were ascertained using electronic health records between July 1, 2016, and June 30, 2017. The area deprivation index (ADI) is a composite measure of social determinants of health composed of 17 US Census indicators and was calculated for all census block groups in Minnesota, Iowa, and Wisconsin (11 230 census block groups). Rurality was defined at the zip code level. Using multivariable logistic regression, this study examined the association between the ADI, rurality, and completion of cancer screening after adjusting for age, Charlson Comorbidity Index, race, and sex (for colorectal cancer only). Main Outcomes and Measures: Completion of recommended breast, cervical, and colorectal cancer screening. Results: The study cohorts were composed of 78 302 patients eligible for breast cancer screening (mean [SD] age, 61.8 [7.1] years), 126 731 patients eligible for cervical cancer screening (mean [SD] age, 42.6 [13.2] years), and 145 550 patients eligible for colorectal cancer screening (mean [SD] age, 62.4 [7.0] years; 52.9% [77 048 of 145 550] female). The odds of completing recommended screening were decreased for individuals living in the most deprived (highest ADI) census block group quintile compared with the least deprived (lowest ADI) quintile: the odds ratios were 0.51 (95% CI, 0.46-0.57) for breast cancer, 0.58 (95% CI, 0.54-0.62) for cervical cancer, and 0.57 (95% CI, 0.53-0.61) for colorectal cancer. Individuals living in rural areas compared with urban areas also had lower rates of cancer screening: the odds ratios were 0.76 (95% CI, 0.72-0.79) for breast cancer, 0.81 (95% CI, 0.79-0.83) for cervical cancer, and 0.93 (95% CI, 0.91-0.96) for colorectal cancer. Conclusions and Relevance: Individuals living in areas of greater deprivation and rurality had lower rates of recommended cancer screening, signaling the need for effective intervention strategies that may include improved community partnerships and patient engagement to enhance access to screening in highest-risk populations.