Risk of 16 cancers across the full glycemic spectrum: a population-based cohort study using the UK Biobank

INTRODUCTION: Diabetes is observed to increase cancer risk, leading to hypothesized direct effects of either hyperglycemia or medication. We investigated associations between glycosylated hemoglobin (HbA1c) across the whole glycemic spectrum and incidence of 16 cancers in a population sample with comprehensive adjustment for risk factors and medication. RESEARCH DESIGN AND METHODS: Linked data from the UK Biobank and UK cancer registry for all individuals with baseline HbA1c and no history of cancer at enrollment were used. Incident cancer was based on International Classification of Diseases - 10th Edition diagnostic codes. Age-standardized incidence rates were estimated by HbA1c category. Associations between HbA1c, modeled as a restricted cubic spline, and cancer risk were estimated using Cox proportional hazards models. RESULTS: Among 378 253 individuals with average follow-up of 7.1 years, 21 172 incident cancers occurred. While incidence for many of the 16 cancers was associated with hyperglycemia in crude analyses, these associations disappeared after multivariable adjustment, except for pancreatic cancer (HR 1.55, 95% CI 1.22 to 1.98 for 55 vs 35 mmol/mol), and a novel finding of an inverse association between HbA1c and premenopausal breast cancer (HR 1.27, 95% CI 1.00 to 1.60 for 25 vs 35 mmol/mol; HR 0.71, 95% CI 0.54 to 0.94 for 45 vs 35 mmol/mol), not observed for postmenopausal breast cancer. Adjustment for diabetes medications had no appreciable impact on HRs for cancer. CONCLUSIONS: Apart from pancreatic cancer, we did not demonstrate any independent positive association between HbA1c and cancer risk. These findings suggest that the potential for a cancer-inducing, direct effect of hyperglycemia may be misplaced

Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode

The conduction velocity and propagation patterns of Electrohysterogram (EHG) provide fundamental information about uterine electrophysiological condition. The accuracy of these measurements can be impaired by both the poor spatial selectivity and sensitivity to the relative direction of the contraction propagation associated with conventional disc electrodes. Concentric ring electrodes could overcome these limitations the aim of this study was to examine the feasibility of picking up surface EHG signals using a new flexible tripolar concentric ring electrode (TCRE), and to compare it with conventional bipolar recordings. Simultaneous recording of conventional bipolar signals and bipolar concentric EHG (BC-EHG) were carried out on 22 pregnant women. Signal bursts were characterized and compared. No significant differences among channels in either duration or dominant frequency in the Fast Wave High frequency range were found. Nonetheless, the high pass filtering effect of the BC-EHG records resulted in lower frequency content within the range 0.1 to 0.2 Hz than the bipolar ones. Although the BC-EHG signal amplitude was about 5-7 times smaller than that of bipolar recordings, similar signal-to-noise ratio was obtained. These results suggest that the flexible TCRE is able to pick up uterine electrical activity and could provide additional information for deducing uterine electrophysiological condition.The authors are grateful to the Obstetrics Unit of the Hospital Universitario La Fe de Valencia (Valencia, Spain), where the recording sessions were carried out. The work was supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC2010-16945), by the Universitat Politecnica de Valencia (PAID SP20120490) and Generalitat Valenciana (GV/2014/029) and by General Electric Healthcare.Ye Lin, Y.; Alberola Rubio, J.; Prats Boluda, G.; Perales Marin, AJ.; Desantes, D.; Garcia Casado, FJ. (2015). Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode. Annals of Biomedical Engineering. 43(4):968-976. https://doi.org/10.1007/s10439-014-1130-5S968976434Alberola-Rubio, J., G. Prats-Boluda, Y. Ye-Lin, J. Valero, A. Perales, and J. Garcia-Casado. Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. Med. Eng. Phys. 35(12):1736–1743, 2013.Besio, W. G., K. Koka, R. Aakula, and W. Dai. Tri-polar concentric ring electrode development for laplacian electroencephalography. IEEE Trans. Biomed. Eng. 53(5):926–933, 2006.Devasahayam, S. R. Signals and Systems in Biomedical Engineering. Berlin: Springer, 2013.Devedeux, D., C. Marque, S. Mansour, G. Germain, and J. Duchene. Uterine electromyography: a critical review. Am. J. Obstet. Gynecol. 169(6):1636–1653, 1993.Estrada, L., A. Torres, J. Garcia-Casado, G. Prats-Boluda, and R. Jane. Characterization of laplacian surface electromyographic signals during isometric contraction in biceps brachii. Conf. Proc. IEEE Eng Med. Biol. Soc. 2013:535–538, 2013.Euliano, T. Y., D. Marossero, M. T. Nguyen, N. R. Euliano, J. Principe, and R. K. Edwards. Spatiotemporal electrohysterography patterns in normal and arrested labor. Am. J. Obstet. Gynecol. 200(1):54–57, 2009.Farina, D., and C. Cescon. Concentric-ring electrode systems for noninvasive detection of single motor unit activity. IEEE Trans. Biomed. Eng. 48(11):1326–1334, 2001.Fele-Zorz, G., G. Kavsek, Z. Novak-Antolic, and F. Jager. A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Med. Biol. Eng Comput. 46(9):911–922, 2008.Garfield, R. E., and W. L. Maner. Physiology and electrical activity of uterine contractions. Semin. Cell Dev. Biol. 18(3):289–295, 2007.Garfield, R. E., W. L. Maner, L. B. Mackay, D. Schlembach, and G. R. Saade. Comparing uterine electromyography activity of antepartum patients vs. term labor patients. Am. J. Obstet. Gynecol. 193(1):23–29, 2005.Garfield, R. E., H. Maul, L. Shi, W. Maner, C. Fittkow, G. Olsen, and G. R. Saade. Methods and devices for the management of term and preterm labor. Ann. N. Y. Acad. Sci. 943(1):203–224, 2001.Hassan, M., J. Terrien, C. Muszynski, A. Alexandersson, C. Marque, and B. Karlsson. Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans. Biomed. Eng. 60(4):1160–1166, 2013.Kaufer, M., L. Rasquinha, and P. Tarjan. Optimization of multi-ring sensing electrode set, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 1990, pp. 612–613.Koka, K., and W. G. Besio. Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. J. Neurosci. Methods 165(2):216–222, 2007.Lu, C.-C., and P. P. Tarjan. Pasteless, active, concentric ring sensors for directly obtained laplacian cardiac electrograms. J. Med. Biol. Eng. 22(4):199–203, 2002.Lucovnik, M., W. L. Maner, L. R. Chambliss, R. Blumrick, J. Balducci, Z. Novak-Antolic, and R. E. Garfield. Noninvasive uterine electromyography for prediction of preterm delivery. Am. J. Obstet. Gynecol. 204(3):228.e1–228.e10, 2011.Maner, W. L., and R. E. Garfield. Identification of human term and preterm labor using artificial neural networks on uterine electromyography data. Ann. Biomed. Eng. 35(3):465–473, 2007.Maner, W. L., R. E. Garfield, H. Maul, G. Olson, and G. Saade. Predicting term and preterm delivery with transabdominal uterine electromyography. Obstet. Gynecol. 101(6):1254–1260, 2003.Marque, C., J. M. Duchene, S. Leclercq, G. S. Panczer, and J. Chaumont. Uterine EHG processing for obstetrical monitoring. IEEE Trans. Biomed. Eng. 33(12):1182–1187, 1986.Marque, C. K., J. Terrien, S. Rihana, and G. Germain. Preterm labour detection by use of a biophysical marker: the uterine electrical activity. BMC. Pregnancy Childbirth. 7(Suppl1):S5, 2007.Maul, H., W. L. Maner, G. Olson, G. R. Saade, and R. E. Garfield. Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. J. Matern. Fetal Neonatal Med. 15(5):297–301, 2004.Miles, A. M., M. Monga, and K. S. Richeson. Correlation of external and internal monitoring of uterine activity in a cohort of term patients. Am. J. Perinatol. 18(3):137–140, 2001.Prats-Boluda, G., J. Garcia-Casado, J. L. Martinez-de-Juan, and Y. Ye-Lin. Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Med. Eng. Phys. 33(4):446–455, 2010.Prats-Boluda, G., Y. Ye-Lin, E. Garcia-Breijo, J. Ibañez, and J. Garcia-Casado. Active flexible concentric ring electrode for non-invasive surface bioelectrical recordings. Meas. Sci. Technol. 23(12):1–10, 2012.Rabotti, C., M. Mischi, S. G. Oei, and J. W. Bergmans. Noninvasive estimation of the electrohysterographic action-potential conduction velocity. IEEE Trans. Biomed. Eng. 57(9):2178–2187, 2010.Rabotti, C., S. G. Oei, H. J. van ‘t, and M. Mischi. Electrohysterographic propagation velocity for preterm delivery prediction. Am. J. Obstet. Gynecol. 205(6):e9–e10, 2011.Rooijakkers, M. J., S. Song, C. Rabotti, S. G. Oei, J. W. Bergmans, E. Cantatore, and M. Mischi. Influence of electrode placement on signal quality for ambulatory pregnancy monitoring. Comput. Math. Methods Med. 2014(1):960980, 2014.Schlembach, D., W. L. Maner, R. E. Garfield, and H. Maul. Monitoring the progress of pregnancy and labor using electromyography. Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl1):S33–S39, 2009.Sikora, J., A. Matonia, R. Czabanski, K. Horoba, J. Jezewski, and T. Kupka. Recognition of premature threatening labour symptoms from bioelectrical uterine activity signals. Arch. Perinatal Med. 17(2):97–103, 2011.Terrien, J., C. Marque, and B. Karlsson. Spectral characterization of human EHG frequency components based on the extraction and reconstruction of the ridges in the scalogram, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 2007, pp. 1872–1875.Terrien, J., C. Marque, T. Steingrimsdottir, and B. Karlsson. Evaluation of adaptive filtering methods on a 16 electrode electrohysterogram recorded externally in labor, 11th Mediterranean Conference on Medical and Biomedical Engineering and Computing, 2007, Vol. 16, pp. 135–138.U.S. Preventive Services Task Force. Guide to clinical preventive services: an assessment of the effectiveness of 169 interventions. Baltimore: Willams & Wilkins, 1989

Synchronization analysis of the uterine magnetic activity during contractions

BACKGROUND: Our objective was to quantify and compare the extent of synchronization of the spatial-temporal myometrial activity over the human uterus before and during a contraction using transabdominal magnetomyographic (MMG) recordings. Synchronization can be an important indicator for the quantification of uterine contractions. METHODS: The spatialtermporal myometrial activity recordings were performed using a 151-channel noninvasive magnetic sensor system called SARA. This device covers the entire pregnant abdomen and records the magnetic field corresponding to the electrical activity generated in the uterine myometrium. The data was collected at 250 samples/sec and was resampled with 25 samples/sec and then filtered in the band of 0.1–0.2 Hz to study the primary magnetic activity of the uterus related to contractions. The synchronization between a channel pair was computed. It was inferred from a statistical tendency to maintain a nearly constant phase difference over a given period of time even though the analytic phase of each channel may change markedly during that time frame. The analytic phase was computed after taking Hilbert transform of the magnetic field data. The process was applied on the pairs of magnetic field traces (240 sec length) with a stepping window of 20 sec duration which is long enough to cover two cycle of the lowest frequency of interest (0.1 Hz). The analysis was repeated by stepping the window at 10 sec intervals. The spatial patterns of the synchronization indices covering the anterior transabdominal area were computed. For this, regional coil-pairs were used. For a given coil, the coil pairs were constructed with the surrounding six coils. The synchronization indices were computed for each coil pair, averaged over the 21 coil-pairs and then assigned as the synchronization index to that particular coil. This procedure was tested on six pregnant subjects at the gestational age between 29 and 40 weeks admitted to the hospital for contractions. The RMS magnetic field for each coil was also computed. RESULTS: The results show that the spatial patterns of the synchronization indices change and follow the periodic pattern of the uterine contraction cycle. Spatial patterns of synchronization indices and the RMS magnetic fields show similarities in few window frames and also show large differences in few other windows. For six subjects, the average synchronization indices were: 0.346 ± 0.068 for the quiescent baseline period and 0.545 ± 0.022 at the peak of the contraction. DISCUSSION: These results show that synchronization indices and their spatial distributions depict uterine contractions and relaxations

Type 2 diabetes risks and determinants in second-generation migrants and mixed ethnicity people of South Asian and African Caribbean descent in the UK

AIMS/HYPOTHESIS: Excess risks of type 2 diabetes in UK South Asians (SA) and African Caribbeans (AC) compared with Europeans remain unexplained. We studied risks and determinants of type 2 diabetes in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity. METHODS: Data from the UK Biobank, a population-based cohort of ~500,000 participants aged 40-69 at recruitment, were used. Type 2 diabetes was assigned using self-report and HbA1c. Ethnicity was both self-reported and genetically assigned using admixture level scores. European, mixed European/South Asian (MixESA), mixed European/African Caribbean (MixEAC), SA and AC groups were analysed, matched for age and sex to enable comparison. In the frames of this cross-sectional study, we compared type 2 diabetes in second- vs first-generation migrants, and mixed ethnicity vs non-mixed groups. Risks and explanations were analysed using logistic regression and mediation analysis, respectively. RESULTS: Type 2 diabetes prevalence was markedly elevated in SA (599/3317 = 18%) and AC (534/4180 = 13%) compared with Europeans (140/3324 = 4%). Prevalence was lower in second- vs first-generation SA (124/1115 = 11% vs 155/1115 = 14%) and AC (163/2200 = 7% vs 227/2200 = 10%). Favourable adiposity (i.e. lower waist/hip ratio or BMI) contributed to lower risk in second-generation migrants. Type 2 diabetes in mixed populations (MixESA: 52/831 = 6%, MixEAC: 70/1045 = 7%) was lower than in comparator ethnic groups (SA: 18%, AC: 13%) and higher than in Europeans (4%). Greater socioeconomic deprivation accounted for 17% and 42% of the excess type 2 diabetes risk in MixESA and MixEAC compared with Europeans, respectively. Replacing self-reported with genetically assigned ethnicity corroborated the mixed ethnicity analysis. CONCLUSIONS/INTERPRETATION: Type 2 diabetes risks in second-generation SA and AC migrants are a fifth lower than in first-generation migrants. Mixed ethnicity risks were markedly lower than SA and AC groups, though remaining higher than in Europeans. Distribution of environmental risk factors, largely obesity and socioeconomic status, appears to play a key role in accounting for ethnic differences in type 2 diabetes risk

Patient and public involvement in patient safety research: a workshop to review patient information, minimise psychological risk and inform research

Background Patient safety has attracted increasing attention in recent years. This paper explores patients’ contributions to informing patient safety research at an early stage, within a project on intravenous infusion errors. Currently, there is little or no guidance on how best to involve patients and the wider public in shaping patient safety research, and indeed, whether such efforts are worthwhile. Method We ran a 3-hour workshop involving nine patients with experience of intravenous therapy in the hospital setting. The first part explored patients’ experiences of intravenous therapy. We derived research questions from the resulting discussion through qualitative analysis. In the second part, patients were asked for feedback on patient information sheets considering both content and clarity, and on two potential approaches to framing our patient information: one that focused on research on safety and error, the other on quality improvement. Results The workshop led to a thorough review of how we should engage with patients. Importantly, there was a clear steer away from terms such as ‘error’ and ‘safety’ that could worry patients. The experiences that patients revealed were also richer than we had anticipated, revealing different conceptions of how patients related to their treatment and care, their role in safety and use of medical devices, the different levels of information they preferred, and broader factors impacting perceptions of their care. Conclusion Involving patients at an early stage in patient safety research can be of great value. Our workshop highlighted sensitivities around potentially worrying patients about risks that they might not have considered previously, and how to address these. Patient representatives also emphasised a need to expand the focus of patient safety research beyond clinicians and error, to include factors affecting perceptions of quality and safety for patients more broadly

Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment

[EN] As one of the main aims of obstetrics is to be able to detect imminent delivery in patients with threatened preterm labor, the techniques currently used in clinical practice have serious limitations in this respect. The electrohysterogram (EHG) has now emerged as an alternative technique, providing relevant information about labor onset when recorded in controlled checkups without administration of tocolytic drugs. The studies published to date mainly focus on EHG-burst analysis and, to a lesser extent, on whole EHG window analysis. The study described here assessed the ability of EHG signals to discriminate imminent labor (The ability of EHG recordings to predict imminent labor (<7days) was analyzed in preterm threatened patients undergoing tocolytic therapies by means of EHG-burst and whole EHG window analysis. The non-linear features were found to have better performance than the temporal and spectral parameters in separating women who delivered in less than 7days from those who did not.Mas-Cabo, J.; Prats-Boluda, G.; Perales Marín, AJ.; Garcia-Casado, J.; Alberola Rubio, J.; Ye Lin, Y. (2019). Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment. Medical & Biological Engineering & Computing. 57:401-411. https://doi.org/10.1007/s11517-018-1888-yS40141157Aboy M, Cuesta-Frau D, Austin D, Micó-Tormos P (2007) Characterization of sample entropy in the context of biomedical signal analysis. Conf Proc IEEE Eng Med Biol Soc:5942–5945. https://doi.org/10.1109/IEMBS.2007.4353701Aboy M, Hornero R, Abásolo D, Álvarez D (2006) Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis. 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Med Eng Phys 33:980–986. https://doi.org/10.1016/j.medengphy.2011.03.010Hassan M, Terrien J, Muszynski C et al (2013) Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans Biomed Eng 60:1160–1166. https://doi.org/10.1109/TBME.2012.2229279Horoba K, Jezewski J, Matonia A, Wrobel J, Czabanski R, Jezewski M (2016) Early predicting a risk of preterm labour by analysis of antepartum electrohysterograhic signals. Biocybern Biomed Eng 36:574–583. https://doi.org/10.1016/j.bbe.2016.06.004Lawn JE, Wilczynska-Ketende K, Cousens SN (2006) Estimating the causes of 4 million neonatal deaths in the year 2000. Int J Epidemiol 35:706–718. https://doi.org/10.1093/ije/dyl043Lemancewicz A, Borowska M, Kuć P, Jasińska E, Laudański P, Laudański T, Oczeretko E (2016) Early diagnosis of threatened premature labor by electrohysterographic recordings—the use of digital signal processing. Biocybern Biomed Eng 36:302–307. https://doi.org/10.1016/j.bbe.2015.11.005M L WLM, LR C (2012) Noninvasive uterine electromyography for prediction of preterm delivery. Am J Obstet Gynecol 204:1–20. https://doi.org/10.1016/j.ajog.2010.09.024.NoninvasiveManer WL, Garfield RE (2007) Identification of human term and preterm labor using artificial neural networks on uterine electromyography data. Ann Biomed Eng 35:465–473. https://doi.org/10.1007/s10439-006-9248-8Maner WL, Garfield RE, Maul H, Olson G, Saade G (2003) Predicting term and preterm delivery with transabdominal uterine electromyography. Obstet Gynecol 101:1254–1260. https://doi.org/10.1016/S0029-7844(03)00341-7Marque C, Gondry J (1999) Use of the electrohysterogram signal for characterization of contractions during pregnancy. 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Social Network Analytics for Advanced Bibliometrics: Referring to Actor Roles of Management Journals instead of Journal Rankings

Impact factors are commonly used to assess journals relevance. This implies a simplified view on science as a single-stage linear process. Therefore, few top-tier journals are one-sidedly favored as outlets, such that submissions to top-tier journals explode whereas others are short of submissions. Consequently, the often claimed gap between research and practical application in application-oriented disciplines as business administration is not narrowing but becoming entrenched. A more complete view of the scientific system is needed to fully capture journals ´ contributions in the development of a discipline. Simple citation measures, as e.g. citation counts, are commonly used to evaluate scientific work. There are many known dangers of miss- or over-interpretation of such simple data and this paper adds to this discussion by developing an alternative way of interpreting a discipline based on the positions and roles of journals in their wider network. Specifically, we employ ideas from the network analytic approach. Relative positions allow the direct comparison between different fields. Similarly, the approach provides a better understanding of the diffusion process of knowledge as it differentiates positions in the knowledge creation process. We demonstrate how different modes of social capital create different patterns of action that require a multidimensional evaluation of scientific research. We explore different types of social capital and intertwined relational structures of actors to compare journals with different bibliometric profiles. Ultimately, we develop a multi-dimensional evaluation of actor roles based upon multiple indicators and we test this approach by classifying management journals based on their bibliometric environment

The use of bibliometrics for assessing research : possibilities, limitations and adverse effects

Researchers are used to being evaluated: publications, hiring, tenure and funding decisions are all based on the evaluation of research. Traditionally, this evaluation relied on judgement of peers but, in the light of limited resources and increased bureaucratization of science, peer review is getting more and more replaced or complemented with bibliometric methods. Central to the introduction of bibliometrics in research evaluation was the creation of the Science Citation Index (SCI)in the 1960s, a citation database initially developed for the retrieval of scientific information. Embedded in this database was the Impact Factor, first used as a tool for the selection of journals to cover in the SCI, which then became a synonym for journal quality and academic prestige. Over the last 10 years, this indicator became powerful enough to influence researchers’ publication patterns in so far as it became one of the most important criteria to select a publication venue. Regardless of its many flaws as a journal metric and its inadequacy as a predictor of citations on the paper level, it became the go-to indicator of research quality and was used and misused by authors, editors, publishers and research policy makers alike. The h-index, introduced as an indicator of both output and impact combined in one simple number, has experienced a similar fate, mainly due to simplicity and availability. Despite their massive use, these measures are too simple to capture the complexity and multiple dimensions of research output and impact. This chapter provides an overview of bibliometric methods, from the development of citation indexing as a tool for information retrieval to its application in research evaluation, and discusses their misuse and effects on researchers’ scholarly communication behavior

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier