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Dataset supporting the University of Southampton Doctoral Thesis 'Digital health technologies in improving efficiency in reproductive medicine'
No full textDataset supporting the University of Southampton Doctoral Thesis 'Digital health technologies in improving efficiency in reproductive medicine'.
The data includes:
-Merged app reviews.xlsx
-App reviews for apps included in Chapter 2 study, reviews downloaded from Apple Appstore and Google Playstore.
-Mediemodata.xlsx
-MediEmoData_emotional.xlsx
-scan_streamlining_paper_cohort_anon.csv - available on request only to bone fide researchers with ethical clearance
-CFC_prediction_model_V2.ipynb- Requires PYTHON, python is a free, open-source programming language.</span
Digital health technologies in improving efficiency in reproductive medicine
No full textIn this thesis, the potential for digital health technologies to improve efficiency in reproductive medicine is explored. An efficient clinical system is one achieving high levels of performance (outcomes) relative to the inputs (resources, time, money) consumed. The primary goals of reproductive medical care are, where possible, to achieve a healthy live birth and, if this is not possible, to sustain the psychological wellbeing of those with an unfulfilled child wish. More efficient care would achieve these goals with reduced practical and psychological burden on patients, lower costs, and optimal use of resources. To provide an understanding of the landscape of digital tools in reproductive medicine, this thesis starts with a systematic review and meta-analysis of existing digital support tools. Although digital tools for use alongside fertility treatment have been developed, few are supported by research evidence. The work identified that the small number of digital support tools that have been evaluated in randomised trials overall have a small positive impact on pregnancy rates, but no significant impact on psychological outcomes. The thesis proceeds to address two aspects of the way in which the burden of treatment can potentially be reduced for patients, firstly through emotional and psychological support by means of an emotional support app (MediEmo) and secondly, through streamlining clinical processes using machine learning and algorithms to develop digital health interventions. Digital tools could help empower patients through reduction of IVF treatment burden, thereby reducing treatment dropout, the latter being a significant problem in the fertility treatment journey. One way of reducing treatment burden is by reducing the emotional strain of treatment and this thesis explores the use of a novel app MediEmo in doing just that. MediEmo is a smartphone app designed to provide practical and psychological support to patients during IVF treatment. A 3-year descriptive evaluation study demonstrated high engagement and usage of the app, with 80% of eligible patients entering app data. MediEmo was found to be a sensitive tool to examine the emotional experiences of patients during IVF treatment, indicating the emotional intensity of treatment cycles, particularly the two-week wait prior to pregnancy test. In addition, MediEmo data revealed that elevated levels of negative emotions are also experienced during both intrauterine insemination and frozen embryo transfer cycles and that more support may be required for patients undertaking these treatments. Furthermore, the observational study of rates of return for more IVF treatment within 1 year of a failed IVF cycle found that active app usage was associated with a higher rate of return for further treatment within one year of cycle failure compared to non-users of the app. A higher rate of return could, in theory, improve the chances of pregnancy via cumulative success. Further work planned to test this hypothesis is described. Development of new algorithms has led to considerable research and clinical interest in using machine learning to develop smart digital health interventions. The latter part of this thesis explores applications of these techniques aiming to develop digital tools for use in clinical reproductive medicine. A retrospective study using machine learning aimed to optimise timing of the trigger injection during an IVF stimulation cycle. After this work proved unsuccessful, similar techniques were used to address the need for frequent transvaginal ultrasound monitoring of ovarian follicular growth. This monitoring is an onerous and invasive aspect of fertility treatments, that is traditionally performed, but the frequency of this intervention lacks evidence to support efficiency. Models were developed to predict key variables in an IVF cycle using data from scans on single days. The results identified that ultrasound scans are most useful between day 8 and 10 of an IVF cycle, when accurate predictions of oocyte maturation trigger day, and ovarian hyperstimulation syndrome (OHSS) risk, can be made. With further work, it may be possible to omit the less useful earlier scans, particularly in circumstances such as the Covid pandemic and the resulting need for social distancing. The development of algorithms to improve mid-cycle communication with patients is also summarised.Digital health technologies will play an increasing role in reproductive medicine. This thesis demonstrates this emerging contribution via two specific aspects aiming to reduce patient and clinical treatment burden: 1) emotional support by way of a digital app and 2) utilising advanced analytics in streamlining clinical processes. However, any new digital tools in fertility care must be robustly evaluated to show they truly improve efficiency. The tools should then be tested in the ‘real-world’ and the thesis concludes by considering how this field of work could develop in the future. <br/
Streamlining follicular monitoring during controlled ovarian stimulation. A data-driven approach to efficient IVF care in the new era of social distancing
No full textSTUDY QUESTIONWhat is the optimal follicular tracking strategy for controlled ovarian stimulation (COS) in order to minimise face-to-face interactions?SUMMARY ANSWERAs data from follicular tracking scans on Days 5, 6 or 7 of stimulation are the most useful to accurately predict trigger timing and risk of over-response, scans on these days should be prioritised if streamlined monitoring is necessary.WHAT IS KNOWN ALREADYBritish Fertility Society guidance for centres restarting ART following coronavirus disease 2019 (COVID-19) pandemic-related shutdowns recommends reducing the number of patient visits for monitoring during COS. Current evidence on optimal monitoring during ovarian stimulation is sparse, and protocols vary significantly. Small studies of simplifying IVF therapy by minimising monitoring have reported no adverse effects on outcomes, including live birth rate. There are opportunities to learn from the adaptations necessary during these extraordinary times to improve the efficiency of IVF care in the longer term.STUDY DESIGN, SIZE, DURATIONA retrospective database analysis of 9294 ultrasound scans performed during monitoring of 2322 IVF cycles undertaken by 1875 women in a single centre was performed. The primary objective was to identify when in the IVF cycle the data obtained from ultrasound are most predictive of both oocyte maturation trigger timing and an over-response to stimulation. If a reduced frequency of clinic visits is needed due to COVID-19 precautions, prioritising attendance for monitoring scans on the most predictive cycle days may be prudent.PARTICIPANTS/MATERIALS, SETTING, METHODSThe study comprised anonymised retrospective database analysis of IVF/ICSI cycles at a tertiary referral IVF centre. Machine learning models are used in combining demographic and follicular tracking data to predict cycle oocyte maturation trigger timing and over-response. The primary outcome was the day or days in cycle from which scan data yield optimal model prediction performance statistics. The model for predicting trigger day uses patient age, number of follicles at baseline scan and follicle count by size for the current scan. The model to predict over-response uses age and number of follicles of a given size.MAIN RESULTS AND THE ROLE OF CHANCEThe earliest cycle day for which our model has high accuracy to predict both trigger day and risk of over-response is stimulation Day 5. The Day 5 model to predict trigger date has a mean squared error 2.16 ± 0.12 and to predict over-response an area under the receiver operating characteristic curve 0.91 ± 0.01.LIMITATIONS, REASONS FOR CAUTIONThis is a retrospective single-centre study and the results may not be generalisable to centres using different treatment protocols. The results are derived from modelling, and further clinical validation studies will verify the accuracy of the model.WIDER IMPLICATIONS OF THE FINDINGSFollicular tracking starting at Day 5 of stimulation may help to streamline the amount of monitoring required in COS. Previous small studies have shown that minimal monitoring protocols did not adversely impact outcomes. If IVF can safely be made less onerous on the clinic’s resources and patient’s time, without compromising success, this could help to reduce burden-related treatment drop-out.STUDY FUNDING/COMPETING INTEREST(S)F.P.C. acknowledges funding from the NIHR Applied Research Collaboration Wessex. The authors declare they have no competing interests in relation to this work.TRIAL REGISTRATION NUMBERN/A
After egg collection, can we predict the chance of embryos for day 5 transfer or freezing?
No full textLay summaryEven partway through an IVF cycle, at the point when a woman’s eggs have been collected, it is hard to provide reliableanswers to the common question of ‘Am I likely to have a good embryo to transfer?’ Sometimes, it only takes one good eggto be successful. However, doctors and patients are acutely aware that low egg numbers, older age and having conditionssuch as endometriosis can stack the odds against success. We have developed a model to try and answer this question forthose patients who wish for more information to help guide their expectations after egg collection. A new tool is presentedto predict whether a woman having IVF treatment will have a good enough embryo either to transfer on day 5 or freeze. Itwas built using information from all 2015 to 2016 UK cycles and predicts using age, number of eggs collected and cause ofsubfertility
Digital support tools for fertility patients - a narrative systematic review
No full textDigital support tools, including smartphone apps, are increasingly being used alongside fertility treatments. These tools aim to harness the power of information and technology to improve care, facilitate communication and support patients through stressful treatment cycles. To warrant patient engagement, digital support tools must be perceived as useful. This review identifies and narratively analyses tools developed for fertility patients to date, discusses salient included features and evaluates user reviews. A systematic search of the app markets and electronic literature databases identified 46 digital support tools for fertility patients. The identified web-based tools focussed on psychosocial support, whereas the smartphone apps primarily have practical features, with some incorporating coping support. User feedback was collated from the Google and Apple app marketplaces and analysed using thematic analysis. Patients have high expectations of support apps, in particular the user experience. Nine published studies of web-based digital support tools were identified, but there was a complete absence of peer-reviewed studies of smartphone support apps for fertility patients. This review identifies the increasing range of available digital tools to support patients having fertility treatments and highlights the very limited evidence on which clinicians and patients can currently evaluate these tools.</p
Dealing with equipment failure during oocyte retrieval
No full textThis chapter includes clinical cases, background, evidence-based practical management options, preventive measures, key-point summaries of equipment failure during oocyte retrieval and answers to questions patients ask. It is important any equipment failure is clearly documented, reported on the institution's reporting system and reviewed for learning and actions to mitigate future risk. If the issues cannot be adequately resolved, no oocytes may be retrieved in the window of time available after ovulation trigger. In such cases, the patient will require a full explanation and discussion as per the duty of candor. The question about any equipment failure is not if but rather when it will happen. A good preventive strategy will reduce the chance of failure, allow its prompt recognition and have a plan B for what to do when it occurs.</p
Observational cohort study exploring MediEmo smartphone application use, live birth, and in vitro fertilization treatment return rates
Full text linkObjectiveTo explore the associations between the use of the MediEmo smartphone application and IVF live birth and treatment return rates.DesignA three-year observational cohort studySubjectsPatients undergoing IVF were classified as users if they used the medication or emotion features of the MediEmo. Patients who did not use the two key features or declined to use the app were classified as non-users.ExposureThe use of the MediEmo smartphone application.Main outcome measuresOutcomes of interest were rate of live birth per fresh index cycle, live birth per complete cycle and treatment return for a stimulated cycle of treatment within 12 months of the unsuccessful stimulated index cycle.ResultsA total 1081 patients were eligible to use MediEmo app, 863 were categorised as users and 218 as non-users. MediEmo use was associated with a higher live birth rate per index cycle compared to non-users (27.81% [n=240/863] vs 19.26% [n=42/218], respectively, OR=1.248 95% CI: 1.041, 1.509) and treatment return rate compared to non-users (46.00% [n=169/363] vs 31.37% [n=32/102] respectively, OR=1.339 95% CI: 1.092, 1.656). It was not associated with live birth rate per complete cycle.ConclusionThe observed positive association between MediEmo use and live birth and treatment return rates suggests benefits to patients and clinics. Further research and replication using a randomised controlled trial design is warranted as is investment in development of digital tools for use during IVF treatment
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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