Self-reported Medical Data Research Articles

User experience of self-reported computerized medical history taking for acute chest pain: The Clinical Expert Operating System Chest Pain Danderyd Study.

Chest pain is one of the most common complaints in emergency departments (EDs). Self-reported computerized history taking (CHT) programmes can be used for interpretation of the clinical significance of medical information coming directly from patients. The adoption of CHT in clinical practice depends on reactions and attitudes to the technology from patients and their belief that the technology will have benefits for their medical care. The study objective was to explore the user experience of the self-reported CHT programme Clinical Expert Operating System (CLEOS) in the setting of patients visiting an ED for acute chest pain. This qualitative interview study is part of the ongoing CLEOS-Chest Pain Danderyd Study. A subset (n = 84) of the larger sample who had taken part in self-reported history taking during waiting times at the ED were contacted by telephone and n = 54 (64%) accepted participation. An interview guide with open-ended questions was used and the text was analysed using directed content analysis. The patients' experiences of the CLEOS programme were overall positive although some perceived it as extensive. The programme was well accepted and despite the busy environment, patients were highly motivated and deemed it helpful to make a diagnosis. Six categories of user experience emerged: The clinical context, The individual context, Time aspect, Acceptability of the programme, Usability of the programmeand Perceptions of usefulness in a clinical setting. The programme was well accepted by most patients in the stressful environment at ED although some found it difficult to answer all the questions. Adjustments to the extent of an interview to better suit the context of the clinical use should be a future development of the programme. The findings suggest that CHT programmes can be integrated as a standard process for collecting self-reported medical history data in the ED setting.

The relationship between the high-risk disordered eating and social network navigation among Saudi college females during the COVID pandemic.

BackgroundDisordered eating behaviors (DEBs) are complex health issues that may lead to negative physical and mental health outcomes among college students. More studies should be directed toward the screening of DEBs. This study aimed to determine the prevalence of DEBs among Saudi female university students and their association with social networking site (SNSs) usage and composite lifestyle behaviors during the unprecedented period of COVID-19.MethodsThis cross-sectional study included 445 females recruited using stratified random sampling. The participants self-reported demographic, social, medical, and lifestyle data and completed the validated Arabic version of the Eating Attitudes Test-26, Social Networking Sites (SNSs) Usage Questionnaire, Bergen Social Media Addiction Scale, and Body Shape Questionnaire.ResultsThe prevalence of DEBs was 27.2% among the female students at Taif University. From the pre-pandemic period until the current time, the DEBs-risk group had a significantly higher SNS navigation rate (36.4%) than the normal group (20.4%) (X2 = 30.015, p = 0.001). The regression analysis revealed that females with a significant body image concern, higher number of SNSs friends, and frequent visits to SNSs, and those seeking social-dependent information in relation to weight loss/dieting were more likely to develop DEBs (Overall Model: Chi-Square X2 = 158.071, p < 0.000**).ConclusionsSNSs usage and DEBs were associated during the COVID-pandemic. However, the composite lifestyle score did not demonstrate a significant association with DEBs among the female students at Taif University. Investigating the magnitude of DEBs and understanding the role of SNS are essential for preventing disordered eating among young females.

92-OR: Persistence of Impaired Awareness of Hypoglycemia, Severe Hypoglycemic Events, and Suboptimal Glycemic Control Despite Advanced Diabetes Technologies

Trials of continuous glucose monitors (CGMs) and hybrid closed-loop systems (HCLS) demonstrate improvements in glycemia with reductions in hypoglycemia in T1D, but there is limited real-world data on how these technologies impact the prevalence of impaired awareness of hypoglycemia (IAH) , severe hypoglycemic events (SHEs) , and glycemic control. We conducted a one-time online survey of adults with T1D in the T1D Exchange Registry and online communities. Self-reported medical histories (insulin delivery method, HbA1c, IAH, SHEs) and CGM data were collected. 2044 patients (mean age 43 y, mean T1D duration 26 y, 72% female, 95% White) completed the survey. Most reported using CGMs (92%) ; 953 also used HCLS. Mean HbA1c was 6.89%; 41.5% had an HbA1C of ≥7%; 30.7% reported IAH; 19.8% had ≥1 SHE in the prior year; 12.0% had ≥2 SHEs in the prior year; 9.6% had IAH + ≥1 SHE; and 6.6% had IAH + ≥2 SHEs (Table) . Rates of SHEs and IAH + SHEs were lower in CGM users and CGM + HCLS users than in non-CGM users; however, among CGM + HCLS users, 16.6% reported ≥1 SHE, 8.7% ≥2 SHEs, 7.8% IAH + ≥1 SHE, and 4.7% IAH + ≥2 SHEs. Also, 35.6% of CGM + HCLS users had an HbA1C of ≥7%. In a patient cohort with high rates of technology adoption, rates of SHEs and IAH remained high, with a significant proportion of patients not achieving targeted glycemic control, indicating the need for novel T1D treatments. Disclosure J. Pettus: Advisory Panel; Lilly, MannKind Corporation, Novo Nordisk, Sanofi. Consultant; Carmot Therapeutics, Inc., Diasome. L. Titievsky: Employee; Intercept Pharmaceuticals, Inc., Pfizer Inc., Vertex Pharmaceuticals Incorporated. Stock/Shareholder; Intercept Pharmaceuticals, Inc., Pfizer Inc., Vertex Pharmaceuticals Incorporated. K. Hagan: Employee; Vertex Pharmaceuticals Incorporated. T. Liu: Employee; Takeda Pharmaceutical Company Limited, Vertex Pharmaceuticals Incorporated. Stock/Shareholder; Seattle Genetics, Inc. K. Chandarana: Employee; Vertex Pharmaceuticals Incorporated. J.L. Gaglia: Advisory Panel; Dompé, Regeneron Pharmaceuticals Inc. Consultant; Vertex Pharmaceuticals Incorporated. Research Support; Avotres Inc., Dompé, Janssen Research &amp; Development, LLC, Provention Bio, Inc. Stock/Shareholder; Vertex Pharmaceuticals Incorporated. W. Wolf: None. J. Bispham: Employee; PPD Inc., T1D Exchange. K.S.M. Chapman: None. D. Finan: None. J. Sherr: Advisory Panel; Bigfoot Biomedical, Inc., Cecelia Health, Insulet Corporation, Medtronic, Vertex Pharmaceuticals Incorporated. Consultant; Insulet Corporation, Lexicon Pharmaceuticals, Inc. Research Support; Dexcom, Inc., Insulet Corporation, Jaeb Center for Health Research, JDRF, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Lilly Diabetes.

Detection of signs of disease in external photographs of the eyes via deep learning.

Retinal fundus photographs can be used to detect a range of retinal conditions. Here we show that deep-learning models trained instead on external photographs of the eyes can be used to detect diabetic retinopathy (DR), diabetic macular oedema and poor blood glucose control. We developed the models using eye photographs from 145,832 patients with diabetes from 301 DR screening sites and evaluated the models on four tasks and four validation datasets with a total of 48,644 patients from 198 additional screening sites. For all four tasks, the predictive performance of the deep-learning models was significantly higher than the performance of logistic regression models using self-reported demographic and medical history data, and the predictions generalized to patients with dilated pupils, to patients from a different DR screening programme and to a general eye care programme that included diabetics and non-diabetics. We also explored the use of the deep-learning models for the detection of elevated lipid levels. The utility of external eye photographs for the diagnosis and management of diseases should be further validated with images from different cameras and patient populations.

Abstract P098: Effects Of Occupational Radiation Exposure On The Prevalence Of Hypertension And Its Complications

Background: Advancement of fluoroscopy-assisted procedures in the field of medicine has led to an increase in the frequency of their use among cardiologists, radiologists and surgeons. The personal health risk involved with radiation exposure is of concern and has come under the limelight in recent times. In addition to other consequences, radiation has been linked to cardiovascular disease, but its significance is not well established. Methods: Self-reported demographic, social, occupational, and medical data was collected from board-certified cardiologists via an electronic survey. Bivariate and multivariable logistic regression analyses were performed. Results: 1478 responses were collected from board-certified cardiologists; 85.4% were males, 79% were Caucasian and 66.1% were ≤65 yrs of age. 35.6% of respondents were interventional cardiologists and 16.4% were electrophysiologists. Of those who performed procedures, 92.2% wore lead apparel during all times of radiation exposure. Exposure hours, stratified by less or more than 20,000, correlated positively with the presence of hypertension, and remained significant when adjusted for common risk factors such as age, sex, race, DM, OSA, and alcohol/tobacco use (OR 1.63 CI 1.16 to 2.29, p = 0.005). Conclusion: This study captures self-reported data of just over 4% of cardiologists in the US, and demonstrates a positive correlation between hypertension and procedural radiation exposure hours even post-adjustment for traditional risk factors. As the use of fluoroscopy-assisted procedures continues to grow, further research is necessary to inform operators of the personal health risks of radiation exposure and drive progress in protective attire and risk mitigation strategies.

Self-reported and general practitioner recorded indicators of lifetime health up to age 48 according to offender type in the Cambridge Study in Delinquent Development.

Previous research has suggested that people with a history of offending have worse health compared to non-offenders, but it is less clear whether all types of offenders are at similar health risks. In a New Zealand birthcohort study, Moffitt evidenced three main offending trajectories-life-course-persistent (LCP), adolescence-limited (AL) and late-onset (LO) offending, subsequently confirmed in other substantial longitudinal studies. Our aim was to explore the relationship between these offending trajectories and both self-reported (SR) and general practitioner (GP) (primary care) recorded health indicators. Self-reported medical data at age 48 were obtained for 394 men followed since age 8years in the Cambridge Study in Delinquent Development. In addition, medical records were obtained from GPs for 264 of them. Health indicators from both sources were compared between each of the three established trajectories of offenders across the life course-LCP, AL, LO and the non-offenders. LCP offenders were found to have over twice the likelihood of disabling medical conditions according to both self-report and GP records. They were also more likely to have GP records indicating mental health problems and treatment for them. According to GP records alone, the LO offenders were also more likely to have mental health problems. The health of AL offenders appeared to be no different from that of the crime-free controls. Our findings add weight to the growing evidence that LCP offending and offending that only occurs relatively late in life are likely to be the indicators of generally unhealthy and disrupted lives. This suggests that if lifestyle is to change for the better, interventions are likely to be needed for health as well as antisocial behaviour.

Sleep apnoea and incident malignancy in type 2 diabetes.

BackgroundSleep apnoea and type 2 diabetes (T2D) have been linked to malignancy. The aim of the present study was to evaluate the association between sleep apnoea and incidence of malignancy in patients with T2D.MethodsThe DIACORE (DIAbetes COhoRtE) study is a prospective, population-based cohort study in T2D patients. In the sleep disordered breathing substudy, the apnoea–hypopnoea index (AHI), oxygen desaturation index (ODI) and percentage of night-time spent with a peripheral oxygen saturation of <90% (tsat90%) were assessed using a two-channel ambulatory monitoring device. Malignancy diagnoses were gathered using self-reported medical history data validated by medical records. Hazard ratios (HRs) for incident malignancy were derived by Cox regression adjusting for sex, age, body mass index, smoking status, alcohol intake, socioeconomic status and HbA1c.ResultsOf 1239 patients with T2D (mean age 67 years, 41% female, mean body mass index 30.9 kg·m−2), 79 (6.4%) were first-time diagnosed with a malignancy within a median follow-up period of 2.7 years (interquartile range 2.2–4.5 years). AHI, ODI and tsat90% were not associated with incident malignancy. In subgroup analysis, females showed increased cancer risk per AHI unit (adjusted HR 1.03 per AHI unit, 95% CI 1.00–1.06; p=0.028) and severe sleep apnoea (defined as AHI ≥30 events·h−1; adjusted HR 4.19, 95% CI 1.39–12.77; p=0.012). This was not seen in males, and a significant interaction was observed (interaction terms p=0.048 and p=0.033, respectively).ConclusionSleep apnoea was not associated with incident malignancy in T2D patients. However, stratified analysis revealed a significant association between sleep apnoea and incident malignancy in females, but not in males.

A Web-Based Mobile App (INTERACCT App) for Adolescents Undergoing Cancer and Hematopoietic Stem Cell Transplantation Aftercare to Improve the Quality of Medical Information for Clinicians: Observational Study.

BackgroundA growing number of cancer and hematopoietic stem cell transplant (HSCT) survivors require long-term follow-up with optimal communication schemes, and patients' compliance is crucial. Adolescents have various unmet needs. Regarding self-report of symptoms and health status, users of mobile apps showed enhanced compliance. Currently, HSCT aftercare at the HSCT outpatient clinic of the St. Anna Children’s Hospital in Vienna, Austria, is based on handwritten diaries, carrying various disadvantages. Recently, we developed the prototype of a web-based, self-monitoring gamified mobile app tailored for adolescents: the INTERACCT (Integrating Entertainment and Reaction Assessment into Child Cancer Therapy) app.ObjectiveThis observational, prospective study evaluated the usability of the INTERACCT app for tracking real-time self-reported symptoms and health status data in adolescent HSCT patients and a healthy matched control group. The primary outcome of the study was the quality of the self-reported medical information. We hypothesized that the mobile app would provide superior medical information for the clinicians than would the handwritten diaries.MethodsHealth data were reported via paper diary and mobile app for 5 consecutive days each. The quality of medical information was rated on a 5-point scale independently and blinded by two HSCT clinicians, and the duration of use was evaluated. A total of 52 participant questionnaires were assessed for gaming patterns and device preferences, self-efficacy, users’ satisfaction, acceptability, and suggestions for improvement of the mobile app. Interrater reliability was calculated with the intraclass correlation coefficient, based on a two-way mixed model; one-way repeated-measures analysis of variance and t tests were conducted post hoc. Descriptive methods were used for correlation with participants’ demographics. For users’ satisfaction and acceptability of the mobile app, the median and the IQR were calculated.ResultsData from 42 participants—15 patients and 27 healthy students—with comparable demographics were evaluated. The results of our study indicated a superiority of the quality of self-reported medical data in the INTERACCT app over traditional paper-and-pencil assessment (mobile app: 4.14 points, vs paper-based diary: 3.77 points, P=.02). The mobile app outperformed paper-and-pencil assessments mainly among the patients, in particular among patients with treatment-associated complications (mobile app: 4.43 points, vs paper-based diary: 3.73 points, P=.01). The mobile app was used significantly longer by adolescents (≥14 years: 4.57 days, vs ≤13 years: 3.14 days, P=.03) and females (4.76 days for females vs 2.95 days for males, P=.004). This corresponds with a longer duration of use among impaired patients with comorbidities. User satisfaction and acceptability ratings for the mobile app were high across all groups, but adherence to entering a large amount of data decreased over time. Based on our results, we developed a case vignette of the target group.ConclusionsOur study was the first to show that the quality of patient-reported medical information submitted via the INTERACCT app embedded in a serious game is superior to that submitted via a handwritten diary. In light of these results, a refinement of the mobile app supported by a machine learning approach is planned within an international research project.

Improving accuracy of self-reported diagnoses of rheumatoid arthritis in the French prospective E3N-EPIC cohort: a validation study

ObjectivesThe French E3N-EPIC (Etude Epidémiologique auprès des femmes de la Mutuelle générale de l’Education Nationale-European Prospective Investigation into Cancer and Nutrition) cohort enrolled 98 995 women aged 40 to 65...

Comparison of self-reported and register-based hospital medical data on comorbidities in women

Breast cancer patients commonly present with comorbidities which are known to influence treatment decisions and survival. We aim to examine agreement between self-reported and register-based medical records (National Patient Register [NPR]). Ascertainment of nine conditions, using individually-linked data from 64,961 women enrolled in the Swedish KARolinska MAmmography Project for Risk Prediction of Breast Cancer (KARMA) study. Agreement was assessed using observed proportion of agreement (overall agreement), expected proportion of agreement, and Cohen’s Kappa statistic. Two-stage logistic regression models taking into account chance agreement were used to identify potential predictors of overall agreement. High levels of overall agreement (i.e. ≥86.6%) were observed for all conditions. Substantial agreement (Cohen’s Kappa) was observed for myocardial infarction (0.74), diabetes (0.71) and stroke (0.64) between self-reported and NPR data. Moderate agreement was observed for preeclampsia (0.51) and hypertension (0.46). Fair agreement was observed for heart failure (0.40) and polycystic ovaries or ovarian cysts (0.27). For hyperlipidemia (0.14) and angina (0.10), slight agreement was observed. In most subgroups we observed negative specific agreement of >90%. There is no clear reference data source for ascertainment of conditions. Negative specific agreement between NPR and self-reported data is consistently high across all conditions.

Constructing a Local Potential Participant Registry to Improve Alzheimer's Disease Clinical Research Recruitment.

Potential participant registries are tools to address the challenge of slow recruitment to clinical research. In particular, registries may aid recruitment to secondary prevention clinical trials for Alzheimer's disease (AD), which enroll cognitively normal older individuals meeting specific genetic or biomarker criteria. Evidence of registry effectiveness is sparse, as is guidance on optimal designs or methods of conduct. We report our experiences of developing a novel local potential participant registry that implemented online enrollment and data collection. In the first year of operation, 957 individuals submitted email addresses to the registry, of whom 592 self-reported demographic, family history, and medical data. In addition, registrants provided information related to their interest and willingness to be contacted about studies. Local earned media and community education were the most effective methods of recruitment into the registry. Seventy-six (26%) of 298 registrants contacted about studies in the first year enrolled in those studies. One hundred twenty-nine registrants were invited to enroll in a preclinical AD trial, of whom 25 (18%) screened and 6 were randomized. These results indicate that registries can aid recruitment and provide needed guidance for investigators initiating new local registries.

Governing PatientsLikeMe: Information Production and Research Through an Open, Distributed, and Data-Based Social Media Network

Many organizations develop social media networks with the aim of engaging a wide range of social groups in the production of information that fuels their processes. This effort appears to crucially depend on complex data structures that allow the organization to connect and collect data from a myriad of local contexts and actors. One such organization, PatientsLikeMe, is developing a platform with the aim of connecting patients with one another while collecting self-reported medical data, which it uses for scientific and commercial medical research. Here the question of how technology and the underlying data structures shape the kind of information and medical evidence that can be produced through social media-based arrangements comes powerfully to the fore. In this observational case study, I introduce the concepts of information cultivation and social denomination to explicate how the development of such a data collection architecture requires a continuous exercise of balancing between the conflicting demands of patient engagement, necessary for collecting data in scale, and data semantic context, necessary for effective capture of health phenomena in informative and specific data. The study extends the understanding of the context-embeddedness of information phenomena and discusses some of the social consequences of social media models for knowledge making.

Psychological distress mediates the effects of socio-demographic and clinical characteristics on the physical health component of health-related quality of life in patients with coronary heart disease

This study aimed to examine the mediating role of psychological distress in the relationship between the physical health component of health-related quality of life (HRQoL) of coronary heart disease patients and their socio-demographic and clinical characteristics. This was a cross-sectional study conducted from March 2009 to July 2010 with a total of 420 participants recruited from two hospital-based phase II cardiac rehabilitation centres. Participants' socio-demographic variables, self-reported medical history data, level of psychological distress, perceived social support, and HRQoL were collected by means of a structured questionnaire. Body weight and height, blood pressure and clinical data including fasting blood glucose, triglycerides, and low- and high-density lipoprotein cholesterol were also collected. Exploratory univariate analyses and multivariable regressions were conducted to identify socio-demographic and clinical determinants of the physical health component of HRQoL. Path analyses were then performed to examine the mediating role of psychological distress in the relationship between the physical health component of HRQoL and the determinants. Path analysis revealed that age, sex, perceived social support, history of angina, and dyslipidaemia had both direct effect and indirect effect through psychological distress on the physical health component of HRQoL. Obesity and impaired left ventricular function only affected the physical health component of HRQoL directly, whereas household income only affected it indirectly, through psychological distress. Psychological distress mediates the effects of some socio-demographic and clinical variables of CHD patients on the physical health component of HRQoL. Our findings have important implications for rehabilitation care for people with CHD in order to enhance their HRQoL.

Efficient Replication of over 180 Genetic Associations with Self-Reported Medical Data

While the cost and speed of generating genomic data have come down dramatically in recent years, the slow pace of collecting medical data for large cohorts continues to hamper genetic research. Here we evaluate a novel online framework for obtaining large amounts of medical information from a recontactable cohort by assessing our ability to replicate genetic associations using these data. Using web-based questionnaires, we gathered self-reported data on 50 medical phenotypes from a generally unselected cohort of over 20,000 genotyped individuals. Of a list of genetic associations curated by NHGRI, we successfully replicated about 75% of the associations that we expected to (based on the number of cases in our cohort and reported odds ratios, and excluding a set of associations with contradictory published evidence). Altogether we replicated over 180 previously reported associations, including many for type 2 diabetes, prostate cancer, cholesterol levels, and multiple sclerosis. We found significant variation across categories of conditions in the percentage of expected associations that we were able to replicate, which may reflect systematic inflation of the effects in some initial reports, or differences across diseases in the likelihood of misdiagnosis or misreport. We also demonstrated that we could improve replication success by taking advantage of our recontactable cohort, offering more in-depth questions to refine self-reported diagnoses. Our data suggest that online collection of self-reported data from a recontactable cohort may be a viable method for both broad and deep phenotyping in large populations.

Efficient Replication of Over 180 Genetic Associations with Self-Reported Medical Data

AbstractWhile the cost and speed of generating genomic data have come down dramatically in recent years, the slow pace of collecting medical data for large cohorts continues to hamper genetic research. Here we evaluate a novel online framework for amassing large amounts of medical information in a recontactable cohort by assessing our ability to replicate genetic associations using these data. Using web-based questionnaires, we gathered self-reported data on 50 medical phenotypes from a generally unselected cohort of over 20,000 genotyped individuals. Of a list of genetic associations curated by NHGRI, we successfully replicated about 75% of the associations that we expected to (based on the number of cases in our cohort and reported odds ratios, and excluding a set of associations with contradictory published evidence). Altogether we replicated over 180 previously reported associations, including many for type 2 diabetes, prostate cancer, cholesterol levels, and multiple sclerosis. We found significant variation across categories of conditions in the percentage of expected associations that we were able to replicate, which may reflect systematic inflation of the effects in some initial reports, or differences across diseases in the likelihood of misdiagnosis or misreport. We also demonstrated that we could improve replication success by taking advantage of our recontactable cohort, offering more in-depth questions to refine self-reported diagnoses. Our data suggests that online collection of self-reported data in a recontactable cohort may be a viable method for both broad and deep phenotyping in large populations.

ENDOCRINE HEALTH: Nitrate May Feed Thyroid Disorders

Thyroid cancer incidence has been rising substantially worldwide since at least the 1970s,1 but the reasons remain murky. Trend data are scant for two other thyroid diseases, hyperthyroidism and hypothyroidism, but incidence estimates suggest each is at least 5 times more common than thyroid cancer.2,3 Limited evidence has suggested substances such as polychlorinated biphenyls, polybrominated diphenyl ethers, bisphenol A, and triclosan may be playing a role in these disorders. Nitrate also may belong on that list of suspects, U.S. researchers now report.4 The new study is apparently the first to link nitrate ingestion and thyroid cancer. The authors found that the quartile of women who consumed drinking water containing an average concentration of nitrate–nitrogen5 (NO3–N) greater than 2.46 mg/L—about one-fourth the EPA maximum contaminant level of 10 mg/L—were 2.18 times more likely to have thyroid cancer than the bottom quartile, whose water contained less than 0.36 mg/L NO3–N. Consuming water containing more than 5 mg/L NO3–N for more than five years increased the risk slightly more. The women in the highest quartile of daily nitrate ingestion from food were 2.9 times more likely to have thyroid cancer than the quartile who consumed the least, and were 24% more likely to report having hypothyroidism. Nitrate in food dominated total nitrate intake. The study was based on records from women who were followed from 1986 to 2004 as part of the larger Iowa Women’s Health study. The women were 55–69 years old at recruitment. The researchers had extensive self-reported demographic, behavioral, and medical data, but fewer data on overall diet and none on nitrate levels in individuals. Instead, they had to develop intake estimates based on local public water supply monitoring data and national food nitrate data. The small number of thyroid cancers—40 in the approximately 21,000 women analyzed—also is a limitation, although the findings were statistically significant.6 The numerous limitations make Lewis Braverman, a professor of medicine at the Boston University School of Medicine, somewhat skeptical of the conclusions. “The evidence is fairly soft,” he says. He notes, though, there has been some evidence globally of a nitrate-related association with hypothyroidism, goiter, and other thyroid disorders in subjects such as pregnant women and children exposed to far higher nitrate concentrations than those reported in the present study.7 Ongoing and planned studies, including one looking at men, may provide additional clues, says Mary Ward, lead author of the current study and a senior investigator at the National Cancer Institute. Thyroid cancer is estimated to be the seventh leading site of new cancers in U.S. women, according to the American Cancer Society.8 Incidence is about three times higher in women than in men, similar to the pattern worldwide.1 Some experts are concluding that increased detection alone is not likely to be responsible for global increases.9 Synthetic fertilizer can be an important source of nitrate in water and food.10 The foods that often have the highest concentrations of nitrate, such as spinach, kale, and beets, often are touted for their nutritional benefits. The women in this study who were hardest hit by thyroid disorders tended to be better educated, physically active nonsmokers—a group Ward says is more likely to eat vegetables.

Challenges of self-reported medical conditions and electronic medical records among members of a large military cohort

BackgroundSelf-reported medical history data are frequently used in epidemiological studies. Self-reported diagnoses may differ from medical record diagnoses due to poor patient-clinician communication, self-diagnosis in the absence of a satisfactory explanation for symptoms, or the "health literacy" of the patient.MethodsThe US Department of Defense military health system offers a unique opportunity to evaluate electronic medical records with near complete ascertainment while on active duty. This study compared 38 self-reported medical conditions to electronic medical record data in a large population-based US military cohort. The objective of this study was to better understand challenges and strengths in self-reporting of medical conditions.ResultsUsing positive and negative agreement statistics for less-prevalent conditions, near-perfect negative agreement and moderate positive agreement were found for the 38 diagnoses.ConclusionThis report highlights the challenges of using self-reported medical data and electronic medical records data, but illustrates that agreement between the two data sources increases with increased surveillance period of medical records. Self-reported medical data may be sufficient for ruling out history of a particular condition whereas prevalence studies may be best served by using an objective measure of medical conditions found in electronic healthcare records. Defining medical conditions from multiple sources in large, long-term prospective cohorts will reinforce the value of the study, particularly during the initial years when prevalence for many conditions may still be low.

Medical exposure to ionising radiation and the risk of brain tumours: Interphone study group, Germany

Background The role of exposure to low doses of ionising radiation in the aetiology of brain tumours has yet to be clarified. The objective of this study was to investigate the association between medically or occupationally related exposure to ionising radiation and brain tumours. Methods We used self-reported medical and occupational data collected during the German part of a multinational case–control study on mobile phone use and the risk of brain tumours (Interphone study) for the analyses. Results For any exposure to medical ionising radiation we found odds ratios (ORs) of 0.63 (95% confidence interval (CI) = 0.48–0.83), 1.08 (95% CI = 0.80–1.45) and 0.97 (95% CI = 0.54–1.75) for glioma, meningioma and acoustic neuroma, respectively. Elevated ORs were found for meningioma (OR 2.32, 95% CI: 0.90–5.96) and acoustic neuroma (OR 6.45, 95% CI: 0.62–67.16) for radiotherapy to the head and neck regions. Conclusion We did not find any significant increased risk of brain tumours for exposure to medical ionising radiation.

Lower agreement on behavioral factors than on medical conditions in self-reported data among pregnant latina women

Background Agreement between self-reported data and data obtained from medical records is far from perfect and few studies have analyzed the element of language when self-reported data are given in one language and this information is recorded in another language in the medical record. Our objective was to assess agreement between self-reported data and medical record data with regard to prenatal risk factors in pregnant Latina women. Methods We interviewed 350 Latina women at ≥20 weeks' gestation regarding alcohol use, tobacco use, use of prenatal vitamins, age, education, use of prenatal care, and medical conditions. Kappa statistic (κ) and 95% confidence intervals (95% CIs) were used to calculate agreement between self-reported responses and medical record data. Multiple logistic regression analysis was used to evaluate effect of maternal characteristics on likelihood of disagreement. Results Agreement between self-reported and medical record data was generally lower for behavioral factors (alcohol κ = 0.37 and prenatal vitamin use κ = 0.09) than for medical conditions (anemia κ = 0.63, gestational diabetes κ = 0.83, and hypertension κ = 0.68). In general, maternal characteristics did not significantly predict patterns of disagreement. Conclusions Among pregnant Latina women, self-reported data on behavioral factors had lower agreement than self-reported data on medical conditions. Further study is needed to define the effect of other factors, such as social norms, on accuracy of self-reported data during pregnancy.

Agreement between Self-Reported Information and Medical Claims Data on Diagnosed Diabetes in Oregonʼs Medicaid Population

Recent trends in Oregon indicated that diabetes is on the rise. Medicaid self-reported data estimated about 11 percent are affected by diabetes, which is twice the prevalence of the general population in Oregon. Little is known about the agreement between self-reported information and medical claims data in the Medicaid population. This study provides an opportunity to compare prevalence of diabetes when the estimates are computed from the two different data sources. A sample of 2,154 Medicaid adults in Oregon (18 to 64 years old) were identified in both the Medicaid claims and self-report survey. The result reported a strong agreement of diabetes definition between the Medicaid claim data and the self-reported survey.