Comparison of Mammography and Mammography with Supplemental Whole-Breast US Tomography for Cancer Detection in Patients with Dense Breasts.

BACKGROUND: Women with dense breasts benefit from supplemental cancer screening with US, but US has low specificity. PURPOSE: To evaluate the performance of breast US tomography (UST) combined with full-field digital mammography (FFDM) compared with FFDM alone for breast cancer screening in women with dense breasts. MATERIALS AND METHODS: This retrospective multireader multicase study included women with dense breasts who underwent FFDM and UST at 10 centers between August 2017 and October 2019 as part of a prospective case collection registry. All patients in the registry with cancer were included; patients with benign biopsy or negative follow-up imaging findings were randomly selected for inclusion. Thirty-two Mammography Quality Standards Act-qualified radiologists independently evaluated FFDM followed immediately by FFDM plus UST for suspicious findings and assigned a Breast Imaging Reporting and Data System (BI-RADS) category. The superiority of FFDM plus UST versus FFDM alone for cancer detection (assessed with area under the receiver operating characteristic curve [AUC]), BI-RADS 4 sensitivity, and BI-RADS 3 sensitivity and specificity were evaluated using the two-sided significance level of α = .05. Noninferiority of BI-RADS 4 specificity was evaluated at the one-sided significance level of α = .025 with a -10% margin. RESULTS: Among 140 women (mean age, 56 years ±10 [SD]; 36 with cancer, 104 without), FFDM plus UST achieved superior performance compared with FFDM alone (AUC, 0.60 [95% CI: 0.51, 0.69] vs 0.54 [95% CI: 0.45, 0.64]; P = .03). For FFDM plus UST versus FFDM alone, BI-RADS 4 mean sensitivity was superior (37% [428 of 1152] vs 30% [343 of 1152]; P = .03) and BI-RADS 4 mean specificity was noninferior (82% [2741 of 3328] vs 88% [2916 of 3328]; P = .004). For FFDM plus UST versus FFDM, no difference in BI-RADS 3 mean sensitivity was observed (40% [461 of 1152] vs 33% [385 of 1152]; P = .08), but BI-RADS 3 mean specificity was superior (75% [2491 of 3328] vs 69% [2299 of 3328]; P = .04). CONCLUSION: In women with dense breasts, FFDM plus UST improved cancer detection by radiologists versus FFDM alone. Clinical trial registration nos. NCT03257839 and NCT04260620 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Mann in this issue.

Computerized assessment of background parenchymal enhancement on breast dynamic contrast-enhanced-MRI including electronic lesion removal.

Purpose: Current clinical assessment qualitatively describes background parenchymal enhancement (BPE) as minimal, mild, moderate, or marked based on the visually perceived volume and intensity of enhancement in normal fibroglandular breast tissue in dynamic contrast-enhanced (DCE)-MRI. Tumor enhancement may be included within the visual assessment of BPE, thus inflating BPE estimation due to angiogenesis within the tumor. Using a dataset of 426 MRIs, we developed an automated method to segment breasts, electronically remove lesions, and calculate scores to estimate BPE levels. Approach: A U-Net was trained for breast segmentation from DCE-MRI maximum intensity projection (MIP) images. Fuzzy c-means clustering was used to segment lesions; the lesion volume was removed prior to creating projections. U-Net outputs were applied to create projection images of both, affected, and unaffected breasts before and after lesion removal. BPE scores were calculated from various projection images, including MIPs or average intensity projections of first- or second postcontrast subtraction MRIs, to evaluate the effect of varying image parameters on automatic BPE assessment. Receiver operating characteristic analysis was performed to determine the predictive value of computed scores in BPE level classification tasks relative to radiologist ratings. Results: Statistically significant trends were found between radiologist BPE ratings and calculated BPE scores for all breast regions (Kendall correlation, p<0.001). Scores from all breast regions performed significantly better than guessing (p<0.025 from the z-test). Results failed to show a statistically significant difference in performance with and without lesion removal. BPE scores of the affected breast in the second postcontrast subtraction MIP after lesion removal performed statistically greater than random guessing across various viewing projections and DCE time points. Conclusions: Results demonstrate the potential for automatic BPE scoring to serve as a quantitative value for objective BPE level classification from breast DCE-MR without the influence of lesion enhancement.

Identifying trusted local sources and predicting behavior change pathways according to COVID-19 vaccination status: Results of a 2022 statewide survey of Alaskan adults.

BACKGROUND: Low rates of COVID-19 vaccination remain a substantial public health challenge. Despite early successes, vaccinations of Alaskans trail the US average, drawing attention to the need for better-designed and targeted vaccine confidence interventions. Our objective was to assess levels of community trust and theory-driven predictors of vaccination status to inform the design of future programs. METHODS: We conducted a cross-sectional, telephone-based survey of 940 Alaskan adults between May and June 2022. Data were collected on vaccination status (including initial vaccination and receipt of booster shots), trust in local community members, demographic characteristics, and thematic questions designed using the Capability, Opportunity, Motivation - Behavior (COM-B) model to examine possible predictors (barriers/facilitators) of vaccination status. FINDINGS: Among those who are not fully vaccinated and boosted, we observe significantly lower trust placed in many immediate community members, especially health workers (e.g., doctors, nurses, specialty care physicians, health administrators). Firefighters and emergency medical technicians enjoy the most community trust, followed by medical professionals. Among those who received only a primary vaccine series, we find that perceptions of whether close friends are vaccinated, a sense of professional responsibility, and age were the strongest predictors vaccination status. Among the unvaccinated, we find significant predictive power from the same variables, as well as perceptions of whether family members are vaccinated, perceived risks from non-vaccination and whether vaccination is a healthy choice. CONCLUSIONS: These findings will help inform the design and targeting of future vaccine promotion interventions to adult populations in Alaska. Interventions that leverage reflective motivation and social opportunity domains of the COM-B framework may be most effective. Local community members including firefighters and emergency medical technicians, as well as medical professionals may be perceived as the most trustworthy and influential messengers among those who are not fully vaccinated and boosted.

Engagement with mHealth Alcohol Interventions: User Perspectives on an App or Chatbot-Delivered Program to Reduce Drinking.

Research suggests participant engagement is a key mediator of mHealth alcohol interventions' effectiveness in reducing alcohol consumption among users. Understanding the features that promote engagement is critical to maximizing the effectiveness of mHealth-delivered alcohol interventions. The purpose of this study was to identify facilitators and barriers to mHealth alcohol intervention utilization among hazardous-drinking participants who were randomized to use either an app (Step Away) or Artificial Intelligence (AI) chatbot-based intervention for reducing drinking (the Step Away chatbot). We conducted semi-structured interviews from December 2019 to January 2020 with 20 participants who used the app or chatbot for three months, identifying common facilitators and barriers to use. Participants of both interventions reported that tracking their drinking, receiving feedback about their drinking, feeling held accountable, notifications about high-risk drinking times, and reminders to track their drinking promoted continued engagement. Positivity, personalization, gaining insight into their drinking, and daily tips were stronger facilitator themes among bot users, indicating these may be strengths of the AI chatbot-based intervention when compared to a user-directed app. While tracking drinking was a theme among both groups, it was more salient among app users, potentially due to the option to quickly track drinks in the app that was not present with the conversational chatbot. Notification glitches, technology glitches, and difficulty with tracking drinking data were usage barriers for both groups. Lengthy setup processes were a stronger barrier for app users. Repetitiveness of the bot conversation, receipt of non-tailored daily tips, and inability to self-navigate to desired content were reported as barriers by bot users. To maximize engagement with AI interventions, future developers should include tracking to reinforce behavior change self-monitoring and be mindful of repetitive conversations, lengthy setup, and pathways that limit self-directed navigation.

U-Net breast lesion segmentations for breast dynamic contrast-enhanced magnetic resonance imaging.

Purpose: Given the dependence of radiomic-based computer-aided diagnosis artificial intelligence on accurate lesion segmentation, we assessed the performances of 2D and 3D U-Nets in breast lesion segmentation on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) relative to fuzzy c-means (FCM) and radiologist segmentations. Approach: Using 994 unique breast lesions imaged with DCE-MRI, three segmentation algorithms (FCM clustering, 2D and 3D U-Net convolutional neural networks) were investigated. Center slice segmentations produced by FCM, 2D U-Net, and 3D U-Net were evaluated using radiologist segmentations as truth, and volumetric segmentations produced by 2D U-Net slices and 3D U-Net were compared using FCM as a surrogate reference standard. Fivefold cross-validation by lesion was conducted on the U-Nets; Dice similarity coefficient (DSC) and Hausdorff distance (HD) served as performance metrics. Segmentation performances were compared across different input image and lesion types. Results: 2D U-Net outperformed 3D U-Net for center slice (DSC, HD p<0.001) and volume segmentations (DSC, HD p<0.001). 2D U-Net outperformed FCM in center slice segmentation (DSC p<0.001). The use of second postcontrast subtraction images showed greater performance than first postcontrast subtraction images using the 2D and 3D U-Net (DSC p<0.05). Additionally, mass segmentation outperformed nonmass segmentation from first and second postcontrast subtraction images using 2D and 3D U-Nets (DSC, HD p<0.001). Conclusions: Results suggest that 2D U-Net is promising in segmenting mass and nonmass enhancing breast lesions from first and second postcontrast subtraction MRIs and thus could be an effective alternative to FCM or 3D U-Net.

Factors associated with receiving an initial COVID-19 vaccine among Alaskan residents: results from an online cross-sectional survey.

We conducted an online survey of Alaskan adults between May and June, 2022 to identify factors associated with vaccine hesitancy. Of the 948 respondents, approximately 80% reported having received a COVID-19 vaccine. The factors significantly associated with ever receiving COVID-19 vaccine include perceived risk of harm if not vaccinated (PRH), the vaccination status of the respondent's social network (SNW), gender, and education. For each point increase in PRH score, there was more than three times the odds of having ever been vaccinated (OR = 3.42, p < 0.001); and for every point increase in SNW score, there was more than two times the odds of having ever been vaccinated (OR = 2.15, p < 0.001). Males had more than four times the odds of having ever been vaccinated compared to females (OR = 4.55, p < 0.001). Those with a college degree (OR = 2.80, p < 0.05) had greater odds of ever being vaccinated compared to their counterparts. Findings from this sample suggest that, among Alaskans, ever receiving a COVID-19 vaccine is associated with having a majority of their close social networks who have received COVID-19 vaccine and perceiving that not obtaining a COVID-19 vaccine can pose greater risk of harm to themselves than not getting vaccinated. Practical implications of these findings are provided.

Feasibility of a Supportive Text Messaging Intervention in Northwest Alaska.

Suicide disproportionately impacts young Alaska Native people in the northwestern region of Alaska. As part of its efforts to address this challenge, Maniilaq Association developed a program to determine the feasibility of sending short text messages of caring and support. Process evaluation measures included the number of enrollees and the number of text messages sent each month. To determine participant satisfaction and seek recommendations for improvements, a short, online survey was disseminated to enrollees via text message in 2021 and 2022. Between January 2020 and September 2021, text messages were sent each month to about 100 participants, each with an accompanying image. Messages included "You are capable of amazing things" and "You are enough". Twenty-five individuals completed the 2021 survey and 11 the 2022 survey; three quarters lived in Northwest Arctic. Respondents said the messages improved their mood and made them feel like they mattered a lot or a great deal. The intervention was well-received by participants, inspiring individuals to reach out to others and reach out for help for themselves. Recommendations for improvements included increasing culturally relevant and meaningful quotes and the frequency and consistency of messages. Due to concerns around confidentiality, it is unclear if the initiative reached those most at-risk for suicide. However, participants sharing the messages among the small population of the region may have facilitated a broader reach than would otherwise be expected. Supplementary Information: The online version contains supplementary material available at 10.1007/s41347-022-00293-z.

Contraceptive Implant-Associated Bleeding in Adolescent/Young Adult Clinical Practice: Associated Factors, Management, and Rates of Discontinuation.

PURPOSE: To identify factors associated with bothersome implant-associated uterine bleeding, and to evaluate the impact of bleeding management on implant discontinuation. METHODS: We analyzed a quality improvement database of implant insertions (n = 825) at three adolescent/young adult programs and described individuals with and without reported bothersome bleeding. We utilized logistic regression to assess for factors associated with bleeding. RESULTS: Implant recipient mean age was 18.9 ± 2.6 years, and 27% reported having subsequent bothersome uterine bleeding. Recipients had increased odds of reporting such bleeding if they had previously irregular menses (odds ratio [OR] = 1.36; 95% confidence interval [CI]: 1.11-1.68 irregular and infrequent, OR = 1.41; 95% CI: 1.07-1.86 irregular and frequent) or sought the implant for menstrual management purposes exclusively (OR = 1.67; 95% CI 1.42-1.96) or in combination with contraceptive need (OR 1.65; 95%: CI 1.57-1.72). Prior use of the progestin injection or implant was associated with lower odds of subsequent bleeding report (OR = 0.63; 95% CI: 0.54-0.73; OR = 0.54; 95% CI: 0.39-0.75, respectively). Medication management of bleeding was associated with the likelihood of implant discontinuation at 1 year compared to those with untreated bleeding (hazard ratio 1.98 times, 95% CI: 1.39-2.81). The implant was continued for 3 years in over 50% of recipients with ever-managed bothersome bleeding. DISCUSSION: Individuals with historically irregular menses and those seeking the implant for menstrual management more often reported bothersome bleeding. Treating such bleeding with medication was associated with higher 1-year discontinuation rates, although many continued implant use for 3 years. Such findings may influence implant preinsertion counseling and/or postinsertion bleeding management.

The association between anxiety and cardiac interoceptive accuracy: A systematic review and meta-analysis.

Anxiety is often conceptualised as the prototypical disorder of interoception (one's perception of bodily states). Whilst theoretical models predict an association between interoceptive accuracy and anxiety, empirical work has produced mixed results. This manuscript presents a pre-registered systematic review (https://osf.io/2h5xz) and meta-analysis of 55 studies, obtained via a Pubmed search on 9th November 2020, examining the relationship between state and trait anxiety and objectively measured cardiac interoceptive accuracy as assessed by heartbeat counting and discrimination tasks. Potential moderators of this relationship - the age, gender and clinical diagnoses of participants, the anxiety measures used and the study design - were also explored. Overall, we found no evidence for an association between cardiac interoceptive accuracy and anxiety, with none of the factors examined moderating this finding. We discuss the implications these findings have for future research, with a particular focus on the need for further investigation of the relationship between anxiety and other facets of interoception.

Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset.

Purpose: We demonstrate continuous learning and assess its impact on the performance of artificial intelligence of breast dynamic contrast-enhanced magnetic resonance imaging in the task of distinguishing malignant from benign lesions on an independent clinical test dataset. Approach: The study included 1979 patients with 1990 lesions who underwent breast MR imaging during 2015, 2016, and 2017, retrospectively collected under an IRB-approved protocol; there were 1494 malignant and 496 benign lesions based on histopathology. AI was conducted in the task of distinguishing malignant and benign lesions, and independent testing was performed to assess the effect of increasing the numbers of training cases. Five training sets mimicking clinical implementation of continuous AI learning included cases from (1) first quarter of 2015, (2) first half of 2015, (3) all 2015, (4) all 2015 and first half of 2016, and (5) all 2015 and 2016. All classifiers were evaluated on the 2017 independent test set. The area under the ROC curve (AUC) served as the performance metric and was calculated over all lesions in the test set, as well as only mass lesions and only non-mass enhancements. The Mann-Kendall test was used to determine if continuous learning resulted in a positive trend in classification performance. P < 0.05 was considered to be statistically significant. Results: Over the continuous training period, the selected feature subsets tended to become more similar and stable. Performance of the five training conditions on the independent test dataset yielded AUCs of 0.86 (95% CI: [0.83,0.90]), 0.87 (95% CI: [0.83,0.90]), 0.88 (95% CI: [0.84,0.91]), 0.89 (95% CI: [0.85,0.92]), and 0.89 (95% CI: [0.86,0.92]). The Mann-Kendall test indicated a statistically significant positive trend ( P = 0.0167 ) in classification performance with continuous learning. Conclusions: Improved diagnostic performance over time was observed when continuous learning of AI was implemented on an independent clinical test dataset.

Contrasting a Mobile App With a Conversational Chatbot for Reducing Alcohol Consumption: Randomized Controlled Pilot Trial.

BACKGROUND: Mobile apps have shown considerable promise for reducing alcohol consumption among problem drinkers, but like many mobile health apps, they frequently report low utilization, which is an important limitation, as research suggests that effectiveness is related to higher utilization. Interactive chatbots have the ability to provide a conversational interface with users and may be more engaging and result in higher utilization and effectiveness, but there is limited research into this possibility. OBJECTIVE: This study aimed to develop a chatbot alcohol intervention based on an empirically supported app (Step Away) for reducing drinking and to conduct a pilot trial of the 2 interventions. Included participants met the criteria for hazardous drinking and were interested in reducing alcohol consumption. The study assessed utilization patterns and alcohol outcomes across the 2 technology conditions, and a waitlist control group. METHODS: Participants were recruited using Facebook advertisements. Those who met the criteria for hazardous consumption and expressed an interest in changing their drinking habits were randomly assigned to three conditions: the Step Away app, Step Away chatbot, and waitlist control condition. Participants were assessed on the web using the Alcohol Use Disorders Identification Test, Adapted for Use in the United States, Readiness to Change Questionnaire, Short Inventory of Problems-Revised, and Timeline Followback at baseline and at 12 weeks follow-up. RESULTS: A total of 150 participants who completed the baseline and follow-up assessments were included in the final analysis. ANOVA results indicated that participants in the 3 conditions changed their drinking from baseline to follow-up, with large effect sizes noted (ie, η2=0.34 for change in drinks per day across conditions). However, the differences between groups were not significant across the alcohol outcome variables. The only significant difference between conditions was in the readiness to change variable, with the bot group showing the greatest improvement in readiness (F2,147=5.6; P=.004; η2=0.07). The results suggested that the app group used the app for a longer duration (mean 50.71, SD 49.02 days) than the bot group (mean 27.16, SD 30.54 days; P=.02). Use of the interventions was shown to predict reduced drinking in a multiple regression analysis (ß=.25, 95% CI 0.00-0.01; P=.04). CONCLUSIONS: Results indicated that all groups in this study reduced their drinking considerably from baseline to the 12-week follow-up, but no differences were found in the alcohol outcome variables between the groups, possibly because of a combination of small sample size and methodological issues. The app group reported greater use and slightly higher usability scores than the bot group, but the bot group demonstrated improved readiness to change scores over the app group. The strengths and limitations of the app and bot interventions as well as directions for future research are discussed. TRIAL REGISTRATION: ClinicalTrials.gov NCT04447794; https://clinicaltrials.gov/ct2/show/NCT04447794.

Teen Birth Across Generations Among Non-Latino Whites and African-American Women: The Effect of Race and Neighborhood Income.

OBJECTIVES: To examine the extent to which lifelong neighborhood income modifies the generational association of teen birth among White and AA women in Cook County, IL. METHODS: Stratified and multilevel logistic regression analyses were conducted on the Illinois transgenerational dataset of singleton births (1989-1991) to non-Latina White and AA mothers (born 1956-1976) with appended U.S. census income information. We calculated rates and risks of teen births according to race, maternal age, and lifelong neighborhood economic environment. RESULTS: Teen birth occurred at a rate of 9.5% and 52.9% for White and AA women, respectively. White women whose mothers were teens when they were born had an over five-fold increased risk of becoming teen mothers themselves. For AA women, the risk was smaller, but statistically significant. For both races, women who experienced downward economic mobility had the highest risk of teen birth, while women with upward mobility had the lowest risk, even compared to women in lifelong high income neighborhoods. While White women exposed to lifelong low income had almost threefold increased risk of teen birth compared to those in lifelong high income neighborhoods, AA women in lifelong high and lifelong low income neighborhoods had similar risk of teen birth. CONCLUSIONS FOR PRACTICE: Understanding the racial differences in intergenerational patterns of teen birth is important for effective program planning and policy making, given that interventions targeted at daughters of teen mothers may differ in effectiveness for White and AA teens.

Pulse pressure as a predictor of response to treatment for severe hypertension in pregnancy.

BACKGROUND: Pulse pressure is a proposed means of tailoring antihypertensive therapy for treatment of acute-onset, severe hypertension in pregnancy. OBJECTIVE: This study aimed to determine whether pulse pressure predicts response to the various first-line antihypertensive medications. STUDY DESIGN: This is a retrospective cohort study from a single academic tertiary care center between 2015 and 2018. Patients were screened for inclusion if they had severe hypertension (defined as systolic blood pressure of ≥160 mm Hg or diastolic blood pressure of ≥110 mm Hg) lasting at least 15 minutes and were initially treated with intravenous labetalol, intravenous hydralazine, or immediate-release oral nifedipine. If a patient had multiple episodes of acute treatment during the pregnancy, only one episode was included in the analysis. The primary outcome was time to resolution (in minutes) of severe hypertension. To adjust for factors that may have affected time to resolution, we first compared baseline characteristics on the basis of the antihypertensive agent received. We then assessed the association between baseline characteristics and resolution of severe hypertension within 60 minutes of treatment. Regression analysis incorporated pulse pressure and antihypertensive agents into a model to predict resolution within 60 minutes of onset of severe hypertension. RESULTS: A total of 479 women hospitalized with severe maternal hypertension met the inclusion criteria. Hydralazine was the initial antihypertensive agent administered to 113 women, whereas 233 received labetalol, and 133 received nifedipine. Those who initially received nifedipine had a shorter mean time to resolution of severe hypertension (32.6 minutes vs 46.3 for hydralazine and 50.3 for labetalol; P<.01) and were more likely to have resolution of severe hypertension within 60 minutes (91.0% vs 77.9% for hydralazine and 76.8% for labetalol; P<.01). Nifedipine also resulted in a lower mean posttreatment blood pressure. Regression analysis revealed that a lack of resolution of severe hypertension within 60 minutes was independently associated with 2 measures of hypertension severity (mean arterial pressure of ≥125 mm Hg and the need for ≥2 doses of medication) and pulse pressure of >75 mm Hg at the time of treatment, initial treatment with labetalol, and gestational age of <37 weeks at the time of the hypertensive event (or at delivery if treatment was after delivery). The model's bias-corrected bootstrapped area under the receiver operating characteristic curve was 0.85 (95% confidence interval, 0.79-0.88). Interaction terms between pulse pressure and each antihypertensive agent were not significant and therefore not incorporated into the final model. CONCLUSION: Pulse pressure did not predict response to the various first-line antihypertensive agents. Initial treatment with oral nifedipine was associated with a higher likelihood of resolution of severe hypertension within 60 minutes of treatment than with intravenous labetalol.

Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths.

Radiomic features extracted from breast lesion images have shown potential in diagnosis and prognosis of breast cancer. As medical centers transition from 1.5 T to 3.0 T magnetic resonance (MR) imaging, it is beneficial to identify potentially robust radiomic features across field strengths because images acquired at different field strengths could be used in machine learning models. Dynamic contrast-enhanced MR images of benign breast lesions and hormone receptor positive/HER2-negative (HR+/HER2-) breast cancers were acquired retrospectively, yielding 612 unique cases: 150 and 99 benign lesions imaged at 1.5 T and 3.0 T, and 223 and 140 HR+/HER2- cancerous lesions imaged at 1.5 T and 3.0 T, respectively. In addition, an independent set of seven lesions imaged at both field strengths, three benign lesions and four HR+/HER2- cancers, was analyzed separately. Lesions were automatically segmented using a 4D fuzzy c-means method; thirty-eight radiomic features were extracted. Feature value distributions were compared by cancer status and imaging field strength using the Kolmogorov-Smirnov test. Features that did not demonstrate a statistically significant difference were considered to be potentially robust. The area under the receiver operating characteristic curve (AUC), for the task of classifying lesions as benign or HR+/HER2- cancer, was determined for each feature at each field strength. Three features were found to be both potentially robust across field strength and of high classification performance, i.e., AUCs statistically greater than 0.5 in the classification task: one shape feature (irregularity), one texture feature (sum average) and one enhancement variance kinetics features (enhancement variance increasing rate). In the demonstration set of lesions imaged at both field strengths, two of the three potentially robust features showed qualitative agreement across field strength. These findings may contribute to the development of computer-aided diagnosis models that are robust across field strength for this classification task.

Fetal overgrowth in pregnancies complicated by diabetes: validation of a predictive index in an external cohort.

PURPOSE: To assess validity of a fetal overgrowth index in an external cohort of women with diabetes in pregnancy METHODS: We performed a retrospective analysis of data derived from women with singleton gestations complicated by diabetes who delivered January 2015-June 2018. The following index variables were used to calculate risk of fetal overgrowth as defined by a customized birthweight ≥ 90th centile: age, history of fetal overgrowth in a prior pregnancy, gestational weight gain, fetal abdominal circumference measurement and fasting glucose between 24 and 30 weeks. RESULTS: In our validation cohort, 21% of 477 pregnancies were complicated by fetal overgrowth. The predictive index had a bias-corrected bootstrapped area under receiver operating characteristic curve of 0.90 (95% CI 0.86-0.93). 55% of the cohort had a low-risk index (≤ 3) which had a negative predictive value of 97% (95% CI 94-98%), while 18% had a high-risk index (≥ 8) that had a positive predictive value of 74% (95% CI 66-81%). CONCLUSION: The fetal overgrowth index incorporates five factors that are widely available in daily clinical practice prior to the period of maximum fetal growth velocity in the third trimester. Despite substantial differences between our cohort and the one studied for model development, we found the performance of the index was strong. This finding lends support for the general use of this tool that may aid counseling and allow for targeted allocation of healthcare resources among women with pregnancies complicated by diabetes.

Artificial Intelligence Applied to Breast MRI for Improved Diagnosis.

Background Recognition of salient MRI morphologic and kinetic features of various malignant tumor subtypes and benign diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patient treatment. Purpose To evaluate whether the diagnostic performance of radiologists in the differentiation of cancer from noncancer at dynamic contrast material-enhanced (DCE) breast MRI is improved when using an AI system compared with conventionally available software. Materials and Methods In a retrospective clinical reader study, images from breast DCE MRI examinations were interpreted by 19 breast imaging radiologists from eight academic and 11 private practices. Readers interpreted each examination twice. In the "first read," they were provided with conventionally available computer-aided evaluation software, including kinetic maps. In the "second read," they were also provided with AI analytics through computer-aided diagnosis software. Reader diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis, with the area under the ROC curve (AUC) as a figure of merit in the task of distinguishing between malignant and benign lesions. The primary study end point was the difference in AUC between the first-read and the second-read conditions. Results One hundred eleven women (mean age, 52 years ± 13 [standard deviation]) were evaluated with a total of 111 breast DCE MRI examinations (54 malignant and 57 nonmalignant lesions). The average AUC of all readers improved from 0.71 to 0.76 (P = .04) when using the AI system. The average sensitivity improved when Breast Imaging Reporting and Data System (BI-RADS) category 3 was used as the cut point (from 90% to 94%; 95% confidence interval [CI] for the change: 0.8%, 7.4%) but not when using BI-RADS category 4a (from 80% to 85%; 95% CI: -0.9%, 11%). The average specificity showed no difference when using either BI-RADS category 4a or category 3 as the cut point (52% and 52% [95% CI: -7.3%, 6.0%], and from 29% to 28% [95% CI: -6.4%, 4.3%], respectively). Conclusion Use of an artificial intelligence system improves radiologists' performance in the task of differentiating benign and malignant MRI breast lesions. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Krupinski in this issue.

Adherence rates and outcomes for 17-hydroxyprogesterone caproate use in women with a previous history of preterm birth.

BACKGROUND: Progesterone has been used for preventing preterm birth with mixed results. The American College of Obstetricians and Gynecologists and Society for Maternal-Fetal Medicine recommended the use of 17-hydroxyprogesterone caproate for risk reduction of recurrent spontaneous preterm birth based on the results of a multicenter, randomized trial in the United States. However, recent literature lacks consensus for efficacy in the American population. In addition, partial adherence and outcomes thereof are underreported. Hence, the relationship between practical adherence to 17-hydroxyprogesterone caproate and outcomes were evaluated. OBJECTIVE: The objective of this study was to evaluate the adherence to 17-hydroxyprogesterone caproate, defined as receipt of greater than 80% of intended injections, at an outpatient maternal-fetal medicine center and its effect on maternal and neonatal outcomes. STUDY DESIGN: This retrospective cohort study included women older than 18 years with a singleton gestation, history of spontaneous preterm birth who initiated 17-hydroxyprogesterone caproate weekly injections between 16 and 20 weeks' gestational age and delivered between the years 2014 and 2017. Women receiving 17-hydroxyprogesterone caproate injections outside of the clinic were excluded. The primary outcome of adherence and secondary outcomes of gestational age at delivery, birthweight, and neonatal outcomes were analyzed using descriptive data, independent t-test, Mann-Whitney U test, chi-square test, and Fisher exact test, where appropriate, with a P value <.05 being considered significant. RESULTS: Adherence to 17-hydroxyprogesterone caproate occurred in 38 of 92 (41.3%) women included in the study. At baseline, there was a difference in age between groups of adherent and nonadherent women (adherent: 30.8 years; nonadherent: 27.4 years; P=.002). The rate of spontaneous preterm birth less than 37, 35, and 32 weeks were not significantly different in those who were adherent vs nonadherent to 17-hydroxyprogesterone caproate. There were no differences in gestational age at delivery (adherent: 36.8±2.6 weeks; nonadherent: 36.5±3.8 weeks; P=.66), birthweight (adherent: 2776 g; nonadherent: 2709 g; P=.68), or composite neonatal morbidity (adherent: 18.4%; nonadherent: 20.4%; P=.86) between the adherent and nonadherent groups. Neonatal intensive care unit length of stay was 15.5 days in the adherent group compared with 15 days in the nonadherent group (P=.72). CONCLUSION: Real-world adherence to 17-hydroxyprogesterone caproate is suboptimal with less than half of women adherent to in-clinic administration. Adherence to 17-hydroxyprogesterone caproate was not associated with a difference in gestational age at delivery or birthweight compared with nonadherence. Further studies are needed to assess the outpatient administration and benefit of 17-hydroxyprogesterone caproate therapy.

Intraoperative vasopressor use during emergency surgery on injured meth users.

BACKGROUND: Methamphetamine is a growing drug of abuse in America. Patients with recent methamphetamine use pose potential complications to general anesthesia due to changes in hemodynamics and arrhythmias. Limited data exists on the incidence of intraoperative complications on methamphetamine-intoxicated patients requiring urgent or emergent trauma surgery. This study aims to describe intraoperative complications observed in methamphetamine and amphetamine-intoxicated patients requiring emergent surgery. METHODS: Using the Trauma Registry at our ACS-verified level I trauma center, we completed a single-center, descriptive, retrospective cohort review between July 1, 2012 and June 30, 2016, of adult patients requiring emergent surgery with a positive urine-drug screen for methamphetamines or amphetamines. The objective was to evaluate vasopressor utilization during surgical operation. RESULTS: A total of 92 patients were identified with a positive UDS for amphetamine and/or methamphetamine who went to the operating room within 24 hours of admission. Thirty-two (34%) patients received one or more (≥1) doses of vasopressor, while 60 patients (66%) received no vasopressor. Changes in mean arterial pressure (MAP) were noted in 64%, while only 3% experienced an EKG change. A binomial logistic regression showed age, base deficit and change in MAP to be predictive of vasopressor use (p<0.002). No intraoperative cardiac events or anesthetic complications were seen. DISCUSSION: Hemodynamic instability in the amphetamine and methamphetamine-intoxicated population may be more directly related to degree of resuscitation required, than the presence of a positive UDS. LEVEL OF EVIDENCE: IV.

Applying Ethical Principles When Discussing Alcohol Use During Pregnancy.

Over the past 2 decades, more women in the United States are engaging in excessive alcohol use, including women of reproductive age. Consuming alcohol in amounts greater than recommended limits is associated with an increased risk for adverse health effects, such as breast cancer, hypertension stroke, spontaneous abortion, and infertility. No safe time, safe amount, or safe type of alcohol to consume during pregnancy has been identified. Contradictory beliefs about alcohol use, fear of stigmatization, and potential legal consequences can provide challenges for health care providers who communicate these risks to clients. Health care providers can help to prevent alcohol-related health issues, including alcohol-exposed pregnancies, by providing their clients with factual information about alcohol and health and client-centered options for reducing their health risks. Clinicians can use alcohol screening and brief intervention as a framework for applying the ethical principles of autonomy, veracity, beneficence, and nonmaleficence when talking with women in ways that are nonstigmatizing and supportive to help reduce their health risks and prevent alcohol-exposed pregnancies.

Long-acting reversible contraception side effect management.

PURPOSE OF REVIEW: Long-acting reversible contraception (LARC) is increasingly used by adolescents and young adults (AYAs). Subsequent to LARC insertion, AYAs are presenting to their primary care providers with LARC concerns. This article seeks to equip primary care clinicians with the tools necessary to assess and manage common LARC-associated side effects. RECENT FINDINGS: Side effects are common with progestin-only LARC, and can precipitate early discontinuation of an otherwise effective, low-maintenance form of contraception. Abnormal uterine bleeding, pelvic pain, acne, and weight change are often cited as progestin-only LARC side effects, yet the causes are poorly understood despite extensive research. While most side effects improve with time, therapeutic interventions are available for patients with undesirable side effects that prefer medical management. Research emphasizes the importance of proper patient counseling and clinical follow-up. SUMMARY: Counseling remains essential in the management of LARC-associated side effects. However, options are available to temporarily mitigate such side effects and increase LARC satisfaction. While these therapeutic options are prescribed based on expert opinion, such regimens remain inadequately studied in AYA populations.