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BackgroundOral contraceptives (OCs) are a unique chronic medication with which a memory slip may result in a threat that could change a person’s life course. Subjective concerns of missed OC doses among women have been addressed infrequently. Anonymized queries to internet search engines provide unique access to concerns and information gaps faced by a large number of internet users. ObjectiveWe aimed to quantitate the frequency of queries by women seeking information in an internet search engine, after missing one or more doses of an OC; their further queries on emergency contraception, abortion, and miscarriage; and their rate of reporting a pregnancy timed to the cycle of missing an OC. MethodsWe extracted all English-language queries submitted to Bing in the United States during 2018, which mentioned a missed OC and subsequent queries of the same users on miscarriage, abortion, emergency contraceptives, and week of pregnancy. ResultsWe identified 26,395 Bing users in the United States who queried about missing OC pills and the fraction that further queried about miscarriage, abortion, emergency contraceptive, and week of pregnancy. Users under the age of 30 years who asked about forgetting an OC dose were more likely to ask about abortion (1.5 times) and emergency contraception (1.7 times) (P

BackgroundSurveys suggest that a large proportion of people use the internet to search for information on medical symptoms they experience and that around one-third of the people in the United States self-diagnose using online information. However, surveys are known to be biased, and the true rates at which people search for information on their medical symptoms before receiving a formal medical diagnosis are unknown. ObjectiveThis study aimed to estimate the rate at which people search for information on their medical symptoms before receiving a formal medical diagnosis by a health professional. MethodsWe collected queries made on a general-purpose internet search engine by people in the United States who self-identified their diagnosis from 1 of 20 medical conditions. We focused on conditions that have evident symptoms and are neither screened systematically nor a part of usual medical care. Thus, they are generally diagnosed after the investigation of specific symptoms. We evaluated how many of these people queried for symptoms associated with their medical condition before their formal diagnosis. In addition, we used a survey questionnaire to assess the familiarity of laypeople with the symptoms associated with these conditions. ResultsOn average, 15.49% (1792/12,367, SD 8.4%) of people queried about symptoms associated with their medical condition before receiving a medical diagnosis. A longer duration between the first query for a symptom and the corresponding diagnosis was correlated with an increased likelihood of people querying about those symptoms (rho=0.6; P=.005); similarly, unfamiliarity with the association between a condition and its symptom was correlated with an increased likelihood of people querying about those symptoms (rho=−0.47; P=.08). In addition, worrying symptoms were 14% more likely to be queried about. ConclusionsOur results indicate that there is large variability in the percentage of people who query the internet for their symptoms before a formal medical diagnosis is made. This finding has important implications for systems that attempt to screen for medical conditions.

BackgroundPrivacy restrictions limit access to protected patient-derived health information for research purposes. Consequently, data anonymization is required to allow researchers data access for initial analysis before granting institutional review board approval. A system installed and activated at our institution enables synthetic data generation that mimics data from real electronic medical records, wherein only fictitious patients are listed. ObjectiveThis paper aimed to validate the results obtained when analyzing synthetic structured data for medical research. A comprehensive validation process concerning meaningful clinical questions and various types of data was conducted to assess the accuracy and precision of statistical estimates derived from synthetic patient data. MethodsA cross-hospital project was conducted to validate results obtained from synthetic data produced for five contemporary studies on various topics. For each study, results derived from synthetic data were compared with those based on real data. In addition, repeatedly generated synthetic datasets were used to estimate the bias and stability of results obtained from synthetic data. ResultsThis study demonstrated that results derived from synthetic data were predictive of results from real data. When the number of patients was large relative to the number of variables used, highly accurate and strongly consistent results were observed between synthetic and real data. For studies based on smaller populations that accounted for confounders and modifiers by multivariate models, predictions were of moderate accuracy, yet clear trends were correctly observed. ConclusionsThe use of synthetic structured data provides a close estimate to real data results and is thus a powerful tool in shaping research hypotheses and accessing estimated analyses, without risking patient privacy. Synthetic data enable broad access to data (eg, for out-of-organization researchers), and rapid, safe, and repeatable analysis of data in hospitals or other health organizations where patient privacy is a primary value.

To study the effect of chronic excess growth hormone on adipose tissue, we performed RNA sequencing in adipose tissue biopsies from patients with acromegaly (n = 7) or non-functioning pituitary adenomas (n = 11). The patients underwent clinical and metabolic profiling including assessment of HOMA-IR. Explants of adipose tissue were assayed ex vivo for lipolysis and ceramide levels. Patients with acromegaly had higher glucose, higher insulin levels and higher HOMA-IR score. We observed several previously reported transcriptional changes (IGF1, IGFBP3, CISH, SOCS2) that are known to be induced by GH/IGF-1 in liver but are also induced in adipose tissue. We also identified several novel transcriptional changes, some of which may be important for GH/IGF responses (PTPN3 and PTPN4) and the effects of acromegaly on growth and proliferation. Several differentially expressed transcripts may be important in GH/IGF-1-induced metabolic changes. Specifically, induction of LPL, ABHD5, and NRIP1 can contribute to enhanced lipolysis and may explain the elevated adipose tissue lipolysis in acromegalic patients. Higher expression of TCF7L2 and the fatty acid desaturases FADS1, FADS2 and SCD could contribute to insulin resistance. Ceramides were not different between the two groups. In summary, we have identified the acromegaly gene expression signature in human adipose tissue. The significance of altered expression of specific transcripts will enhance our understanding of the metabolic and proliferative changes associated with acromegaly.

We introduce a new approach for automated guideline-based-care quality assessment, the bidirectional knowledge-based assessment of compliance (BiKBAC) method, and the DiscovErr system, which implements it. Our methodology compares the guideline's Asbru-based formal representation, including its intentions, with the longitudinal medical record, using a top-down and bottom-up approach. Partial matches are resolved using fuzzy temporal logic. The system was evaluated in the type 2 Diabetes management domain, comparing it to three expert clinicians, including two diabetes experts. The system and the experts commented on the management of 10 patients, randomly selected from 2,000 diabetes patients. On average, each record spanned 5.23 years; the data included 1,584 medical transactions. The system provided 279 comments. The experts made 181 different unique comments. The completeness (recall) of the system was 91% when the gold standard was comments made by at least two of the three experts, and 98%, compared to comments made by all three experts. The experts also assessed all of the 114 medication-therapy-related comments, and a random 35% of the 165 tests-and-monitoring-related comments. The system's correctness (precision) was 81%, compared to comments judged as correct by both diabetes experts, and 91%, compared to comments judged as correct by one diabetes expert and at least as partially correct by the other. 89% of the comments were judged as important by both diabetes experts, 8% were judged as important by one expert, and 3% were judged as less important by both experts. Adding the validated system comments to the experts' comments, the completeness scores of the experts were 75%, 60%, and 55%; the expert correctness scores were respectively 99%, 91%, and 88%. Thus, the system could be ranked first in completeness and second in correctness. We conclude that systems such as DiscovErr can effectively assess the quality of continuous guideline-based care. [ABSTRACT FROM AUTHOR]

Introduction: Diet forums in social media websites provide an opportunity to glimpse the experience of different weight loss diet strategies reported by tens of thousands of individuals. Methods: We analyzed all postings with weight information from the six major Reddit weight loss diet forums ("subreddits") as reported by forum participants. Results: Data were collected from January 2011 to April 2020 from all 55,900 users posting weight information. Average start BMI was in the overweight or obese range (26–34 kg/m2), and average goal BMI was in the normal range (21.5–24.5 kg/m2) for all subreddits. There is correlation between start BMI and goal BMI (R2 = 0.63, p < 10−10) and between planned weight loss and reported weight loss (R2 = 0.56, p < 10−10). Approximately 80% of forum participants reported a weight loss that was greater than 5% of their initial body weight. Actual reported weight loss was less than half of goal weight loss. Average reported weight loss and adherence were highest in the keto and loseit subreddits. More upvotes and fewer downvotes were associated with higher reported weight loss in five of the six subreddits. Conclusions: Despite the need for cautious interpretation of these data due to self-selection of users who updated weight loss and the possibility of unreliable weight reports, the study has several findings. Average goal BMI was in the normal weight range, demonstrating a highly unrealistic perception, in a very large lay-public cohort, of the plausibility of losing all excess weight. The success in weight loss and maintenance in self-selected individuals who continued reporting weight for many months may demonstrate the subjective value some individuals can obtain from forum participation. [ABSTRACT FROM AUTHOR]

Background and purpose: Advanced analysis of electroencephalography (EEG) data has become an essential tool in brain research. Based solely on resting state EEG signals, a data‐driven, predictive and explanatory approach is presented to discriminate painful from non‐painful diabetic polyneuropathy (DPN) patients. Methods: Three minutes long, 64 electrode resting‐state recordings were obtained from 180 DPN patients. The analysis consisted of a mixture of traditional, explanatory and machine learning analyses. First, the 10 functional bivariate connections best differentiating between painful and non‐painful patients in each EEG band were identified and the relevant receiver operating characteristic was calculated. Later, those connections were correlated with selected clinical parameters. Results: Predictive analysis indicated that theta and beta bands contain most of the information required for discrimination between painful and non‐painful polyneuropathy patients, with area under the receiver operating characteristic curve values of 0.93 for theta and 0.89 for beta bands. Assessing statistical differences between the average magnitude of functional connectivity values and clinical pain parameters revealed that painful DPN patients had significantly higher cortical functional connectivity than non‐painful ones (p = 0.008 for theta and p = 0.001 for alpha bands). Moreover, intra‐band analysis of individual significant functional connections revealed a positive correlation with average reported pain in the previous 3 months in all frequency bands. Conclusions: Resting state EEG functional connectivity can serve as a highly accurate biomarker for the presence or absence of pain in DPN patients. This highlights the importance of the brain, in addition to the peripheral lesions, in generating the clinical pain picture. This tool can probably be extended to other pain syndromes. [ABSTRACT FROM AUTHOR]

Although the molecular events underlying the relationship between obesity and insulin resistance remain uncertain (1-4), numerous studies have implicated an inflammatory link (5-7). Obesity produces a state of chronic, low-grade [...], Emerging evidence suggests that inflammation provides a link between obesity and insulin resistance. The noncanonical IκB kinases IKK-ζ and TANK-binding kinase 1 (TBK1) are induced in liver and fat by NF-κB activation upon high-fat diet feeding and in turn initiate a program of counterinflammation that preserves energy storage. Here we report that amlexanox, an approved small-molecule therapeutic presently used in the clinic to treat aphthous ulcers and asthma, is an inhibitor of these kinases. Treatment of obese mice with amlexanox elevates energy expenditure through increased thermogenesis, producing weight loss, improved insulin sensitivity and decreased steatosis. Because of its record of safety in patients, amlexanox may be an interesting candidate for clinical evaluation in the treatment of obesity and related disorders.

Angiotensin-converting enzyme (ACE)-2 is a newly described enzyme with antagonistic effects to those of the classical ACE (ACE-1). Both ANG II and aldosterone play an important role in the pathophysiology of congestive heart failure (CHF) and in the adverse cardiac remodeling during its development. In this study, we examined the effects of experimental CHF induced by an aortocaval fistula (ACF) and of its treatment with ANG II and aldosterone inhibitors on the relative levels of ACE-1 and ACE-2. We also compared the effects of spironolactone, an aldosterone antagonist, and eprosartan, an ANG II receptor antagonist, on heart hypertrophy and fibrosis in rats with ACF. Spironolactone (15 mg*[kg.sup.-1]*[day.sup.-1] ip, via minipump) or eprosartan (5 mg*[kg.sup.-1]*[day.sup.-1] ip, via minipump) was administered into rats with ACF for 14 and 28 days. Specific antibodies were used to determine the protein levels of myocardial ACE-1 and ACE-2. ACF increased the cardiac levels of ACE-1 and decreased those of ACE-2. Heart-to-body weight ratio significantly increased from 0.30 [+ or -] 0.004% in sham-operated controls to 0.50 [+ or -] 0.018% and 0.56 [+ or -] 0.044% (P < 0.001) in rats with ACF, 2 and 4 wk after surgery, respectively, in association with increased plasma levels of aldostetone. The area occupied by collagen increased from 2.33 [+ or -] 0.27% to 6.85 [+ or -] 0.65% and 8.03 [+ or -] 0.93% (P < 0.01), 2 and 4 wk after ACF, respectively. Both spironolactone and eprosartan decreased cardiac mass and collagen content and reversed the shift in ACE isoforms. ACF alters the ratio between ACE isoforms in a manner that increases local ANG II and aldosterone levels. Early treatment with both ANG II and aldosterone antagonists is effective in reducing this effect. Thus ACE isoform shift may represent an important component of the development of cardiac remodeling in response to hemodynamic overload, and its correction may contribute to the beneficial therapeutic effects of renin-angiotensin-aldosterone system inhibitors. aldosterone antagonist; angiotensin antagonist