Predictors of success after in vitro fertilization.

The last few decades have witnessed a rise in the global uptake of in vitro fertilization (IVF) treatment. To ensure optimal use of this technology, it is important for patients and clinicians to have access to tools that can provide accurate estimates of treatment success and understand the contribution of key clinical and laboratory parameters that influence the chance of conception after IVF treatment. The focus of this review was to identify key predictors of IVF treatment success and assess their impact in terms of live birth rates. We have identified 11 predictors that consistently feature in currently available prediction models, including age, duration of infertility, ethnicity, body mass index, antral follicle count, previous pregnancy history, cause of infertility, sperm parameters, number of oocytes collected, morphology of transferred embryos, and day of embryo transfer.

Incidence and risk factors of institutionalisation in Parkinson's disease and atypical parkinsonism.

INTRODUCTION: The basic epidemiology of institutionalisation (the need for long-term care in an institution) in parkinsonism is unclear. We aimed to identify the incidence of, and risk factors for, institutionalisation in Parkinson's disease (PD) and atypical parkinsonism (AP). METHODS: We analysed data from a prospective population-based incidence cohort of parkinsonism in North-East Scotland (the PINE study). 556 newly-diagnosed participants (PD, N = 200; AP, N = 98; controls, N = 258), recruited between 2002 and 2009, were prospectively followed life-long with data collection on place of residence. We determined the incidence and baseline predictors of institutionalisation using Cox regression. RESULTS: The median follow-up time was 9.3, 4.4, and 10.8 years in PD, AP, and controls respectively. 70 (35 %) PD, 53 (54 %) AP, and 43 (16 %) controls became institutionalised. The incidence rates of institutionalisation in PD, AP, and controls were 5.1, 20.8, and 1.8 per 100 person-years respectively. The median time to institutionalisation was 11.8 years in PD and 3.5 years in AP. Multivariable Cox regression showed that AP (HR versus PD = 3.05 [95 % CI 1.90,4.91]), increasing age (HR for 10-year increase = 1.82 [95 % CI 1.40,2.36]), poorer cognition (HR for MMSE<24 versus MMSE>27 = 2.62 [95 % CI 1.45, 4.73]), more-severe parkinsonian impairment (UPDRS part 3) (HR for 10-point increase = 1.25 [95 % CI 1.05, 1.48]) were independently associated with higher hazards of institutionalisation. Sex, co-morbidity, smoking history, and living alone were not associated with institutionalisation. CONCLUSION: Institutionalisation is much more frequent in parkinsonism, particularly in AP, than in controls. AP, older age, severe parkinsonian impairment, and poorer cognition were independent baseline predictors of institutionalisation.

External validation of models for predicting cumulative live birth over multiple complete cycles of IVF treatment.

STUDY QUESTION: Can two prediction models developed using data from 1999 to 2009 accurately predict the cumulative probability of live birth per woman over multiple complete cycles of IVF in an updated UK cohort? SUMMARY ANSWER: After being updated, the models were able to estimate individualized chances of cumulative live birth over multiple complete cycles of IVF with greater accuracy. WHAT IS KNOWN ALREADY: The McLernon models were the first to predict cumulative live birth over multiple complete cycles of IVF. They were converted into an online calculator called OPIS (Outcome Prediction In Subfertility) which has 3000 users per month on average. A previous study externally validated the McLernon models using a Dutch prospective cohort containing data from 2011 to 2014. With changes in IVF practice over time, it is important that the McLernon models are externally validated on a more recent cohort of patients to ensure that predictions remain accurate. STUDY DESIGN, SIZE, DURATION: A population-based cohort of 91 035 women undergoing IVF in the UK between January 2010 and December 2016 was used for external validation. Data on frozen embryo transfers associated with these complete IVF cycles conducted from 1 January 2017 to 31 December 2017 were also collected. PARTICIPANTS/MATERIALS, SETTING, METHODS: Data on IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA). The predictive performances of the McLernon models were evaluated in terms of discrimination and calibration. Discrimination was assessed using the c-statistic and calibration was assessed using calibration-in-the-large, calibration slope, and calibration plots. Where any model demonstrated poor calibration in the validation cohort, the models were updated using intercept recalibration, logistic recalibration, or model revision to improve model performance. MAIN RESULTS AND THE ROLE OF CHANCE: Following exclusions, 91 035 women who underwent 144 734 complete cycles were included. The validation cohort had a similar distribution age profile to women in the development cohort. Live birth rates over all complete cycles of IVF per woman were higher in the validation cohort. After calibration assessment, both models required updating. The coefficients of the pre-treatment model were revised, and the updated model showed reasonable discrimination (c-statistic: 0.67, 95% CI: 0.66 to 0.68). After logistic recalibration, the post-treatment model showed good discrimination (c-statistic: 0.75, 95% CI: 0.74 to 0.76). As an example, in the updated pre-treatment model, a 32-year-old woman with 2 years of primary infertility has a 42% chance of having a live birth in the first complete ICSI cycle and a 77% chance over three complete cycles. In a couple with 2 years of primary male factor infertility where a 30-year-old woman has 15 oocytes collected in the first cycle, a single fresh blastocyst embryo transferred in the first cycle and spare embryos cryopreserved, the estimated chance of live birth provided by the post-treatment model is 46% in the first complete ICSI cycle and 81% over three complete cycles. LIMITATIONS, REASONS FOR CAUTION: Two predictors from the original models, duration of infertility and previous pregnancy, which were not available in the recent HFEA dataset, were imputed using data from the older cohort used to develop the models. The HFEA dataset does not contain some other potentially important predictors, e.g. BMI, ethnicity, race, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. WIDER IMPLICATIONS OF THE FINDINGS: Both updated models show improved predictive ability and provide estimates which are more reflective of current practice and patient case mix. The updated OPIS tool can be used by clinicians to help shape couples' expectations by informing them of their individualized chances of live birth over a sequence of multiple complete cycles of IVF. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. S.B. has a commitment of research funding from Merck. D.J.M. and M.B.R. declare support for the present manuscript from Elphinstone scholarship scheme at the University of Aberdeen and Assisted Reproduction Unit at Aberdeen Fertility Centre, University of Aberdeen. D.J.M. declares grants received by University of Aberdeen from NHS Grampian, The Meikle Foundation, and Chief Scientist Office in the past 3 years. D.J.M. declares receiving an honorarium for lectures from Merck. D.J.M. is Associate Editor of Human Reproduction Open and Statistical Advisor for Reproductive BioMed Online. S.B. declares royalties from Cambridge University Press for a book. S.B. declares receiving an honorarium for lectures from Merck, Organon, Ferring, Obstetric and Gynaecological Society of Singapore, and Taiwanese Society for Reproductive Medicine. S.B. has received support from Merck, ESHRE, and Ferring for attending meetings as speaker and is on the METAFOR and CAPRE Trials Data Monitoring Committee. TRIAL REGISTRATION NUMBER: N/A.

A comparison of perinatal outcomes following fresh blastocyst or cleavage stage embryo transfer in singletons and twins and between singleton siblings.

STUDY QUESTION: Are perinatal outcomes following fresh blastocyst versus fresh cleavage stage embryo transfer (ET) different in singletons, twins, and between singleton siblings? SUMMARY ANSWER: Singleton babies conceived following fresh blastocyst, versus cleavage stage, ET are less likely to be small for gestational age (SGA) or to have a congenital anomaly (a result confirmed by comparing singleton siblings), while singletons born following fresh blastocyst ET were at a higher risk of being large for gestational age (LGA) than their sibling born following fresh cleavage stage ET. WHAT IS KNOWN ALREADY: Blastocyst stage transfer is now the preferred strategy in most IVF units. Previous studies have suggested that babies conceived through blastocyst transfer are at increased risk of preterm birth and LGA. STUDY DESIGN SIZE DURATION: A national population-based retrospective cohort study was performed using linked Human Fertilisation and Embryology Authority (HFEA) data on 130 516 IVF and ICSI livebirths occurring from 103 062 women between 2000 and 2017. PARTICIPANTS/MATERIALS SETTING METHODS: We included women who had at least one singleton livebirth resulting from IVF/ICSI fresh embryo treatment, using their own eggs and partner's sperm. A linked HFEA dataset was analysed using a multilevel framework, which accommodated repeated IVF cycles resulting in livebirths in the same woman. A population-averaged robust Poisson model was used for binary outcomes and a multinomial logistic regression model was used for categorical outcomes. Unadjusted and adjusted risk ratios (aRRs) (95% CI) were calculated. MAIN RESULTS AND THE ROLE OF CHANCE: There were 130 516 livebirths in 103 062 women, including 86 630 singletons, 43 886 twin births, and 5384 pairs of singleton siblings. In comparison with fresh cleavage stage ET, fresh blastocyst stage transfer in singletons was associated with a lower risk of low birthweight (aRR = 0.92; 95% CI 0.86, 0.99), lower risk of being SGA (0.83; 0.78, 0.89), and lower risk of congenital anomaly (0.79; 0.71, 0.89). This analysis did not show an increase in risk associated with preterm birth (1.00; 0.94, 1.06), high birthweight (0.99; 0.93, 1.06), LGA (0.99; 0.93, 1.05), and the chance of healthy singleton baby (1.00; 1.00, 1.02). Twins resulting from fresh blastocyst stage ET were at slightly higher risk of preterm birth (1.05; 1.02, 1.10) compared with twins conceived following fresh cleavage stage ET. There was insufficient evidence for an association with the other perinatal outcomes. Singleton siblings born following fresh blastocyst stage ET were at a higher risk of being LGA (1.57; 1.01, 2.46) and at lower risk of having a congenital anomaly (0.52; 0.28, 0.97) compared to their singleton siblings born following cleavage stage ET. There was some evidence of excess risk of preterm birth (1.42; 0.97, 2.23) associated with blastocyst stage transfer. However, we could not confirm an association between blastocyst stage ET and low birthweight (1.35; 0.81, 2.27), high birthweight (1.19; 0.80, 1.77), and the chance of being a healthy baby (0.97; 0.86, 1.09). LIMITATIONS REASONS FOR CAUTION: This was an observational study where we were unable to adjust for some key confounders, such as maternal smoking status and BMI, which may change from one pregnancy to another and are not recorded in the HFEA dataset. WIDER IMPLICATIONS OF THE FINDINGS: In the largest study of its kind, our analysis of singleton siblings, corrected for unmeasured, non-time varying maternal factors, confirms the previously reported association between blastocyst transfer and LGA babies, and shows a reduced risk of congenital anomaly following blastocyst transfer. Our sibling analysis did not confirm a decreased risk of low birthweight following blastocyst transfer. Overall, absolute risks are low and there is insufficient evidence to challenge the practice of extended culture of embryos. STUDY FUNDING/COMPETING INTERESTS: This project is financed by an NHS Grampian Endowment Research Grant, project number 17/052. One of the authors, S.B., was the Editor in Chief of HROpen until 31 December 2022 and would have been in that role when the paper was first submitted. As an invited speaker, S.B. has received travel expenses, accommodation and honoraria from Merck, Organon, and Ferring. A.M. has received travel expenses, accommodation, and honoraria from Merck Serono, Cook Medical, Pharmasure, Gedeon Richter, and Ferring. D.J.M. is currently a HROpen Associate Editor. TRIAL REGISTRATION NUMBER: N/A.

Quality of clinical prediction models in in vitro fertilisation: Which covariates are really important to predict cumulative live birth and which models are best?

The improvement in IVF cryopreservation techniques over the last 20 years has led to an increase in elective single embryo transfer, thus reducing multiple pregnancy rates. This strategy of successive transfers of fresh followed by frozen embryos has resulted in the acceptance of using cumulative live birth over complete cycles of IVF as a critical measure of success. Clinical prediction models are a useful way of estimating the cumulative chances of success for couples tailored to their individual clinical factors, which help them prepare for and plan future treatment. In this review, we describe several models that predict cumulative live birth and recommend which should be used by couples and/or their clinicians and when they should be used. We also discuss the most relevant predictors to consider when either developing new IVF prediction models or updating existing models.

Assessing Performance and Clinical Usefulness in Prediction Models With Survival Outcomes: Practical Guidance for Cox Proportional Hazards Models.

Risk prediction models need thorough validation to assess their performance. Validation of models for survival outcomes poses challenges due to the censoring of observations and the varying time horizon at which predictions can be made. This article describes measures to evaluate predictions and the potential improvement in decision making from survival models based on Cox proportional hazards regression.As a motivating case study, the authors consider the prediction of the composite outcome of recurrence or death (the "event") in patients with breast cancer after surgery. They developed a simple Cox regression model with 3 predictors, as in the Nottingham Prognostic Index, in 2982 women (1275 events over 5 years of follow-up) and externally validated this model in 686 women (285 events over 5 years). Improvement in performance was assessed after the addition of progesterone receptor as a prognostic biomarker.The model predictions can be evaluated across the full range of observed follow-up times or for the event occurring by the end of a fixed time horizon of interest. The authors first discuss recommended statistical measures that evaluate model performance in terms of discrimination, calibration, or overall performance. Further, they evaluate the potential clinical utility of the model to support clinical decision making according to a net benefit measure. They provide SAS and R code to illustrate internal and external validation.The authors recommend the proposed set of performance measures for transparent reporting of the validity of predictions from survival models.

Should we adopt a prognosis-based approach to unexplained infertility?

The treatment of unexplained infertility is a contentious topic that continues to attract a great deal of interest amongst clinicians, patients and policy makers. The inability to identify an underlying pathology makes it difficult to devise effective treatments for this condition. Couples with unexplained infertility can conceive on their own and any proposed intervention needs to offer a better chance of having a baby. Over the years, several prognostic and prediction models based on routinely collected clinical data have been developed, but these are not widely used by clinicians and patients. In this opinion paper, we propose a prognosis-based approach such that a decision to access treatment is based on the estimated chances of natural and treatment-related conception, which, in the same couple, can change over time. This approach avoids treating all couples as a homogeneous group and minimizes unnecessary treatment whilst ensuring access to those who need it early.

Perinatal outcomes of 221,709 singleton and twin pregnancies after the use of donor versus partner sperm.

OBJECTIVE: To study the association of donor sperm on perinatal outcomes of livebirths conceived via in vitro fertilization (IVF) when compared with partner sperm. DESIGN: Retrospective cohort study SETTING: National Human Fertilisation and Embryology Authority assisted reproductive technology registry PATIENTS: All live born singletons and twins conceived through IVF with or without intracytoplasmic sperm injection in the United Kingdom between 1991 and 2016 INTERVENTION(S): Donor sperm compared to partner sperm MAIN OUTCOME MEASURE(S): Perinatal outcomes were assessed. The primary outcomes were preterm and very preterm birth; low, very low, high, and very high birthweight; Secondary outcomes were congenital anomaly and health baby. These were assessed for singletons and twins separately. RESULTS: For singleton livebirths, compared to partner sperm, those conceived with donor sperm were at reduced odds of very preterm (odds ratio [OR], 0.76; 95% confidence interval [CI], 0.63-0.91; adjusted OR [aOR], 0.80; 95% CI, 0.66-0.96), and preterm (OR, 0.90; 95% CI, 0.83-0.98; aOR, 0.93; 95% CI, 0.85-1.01) birth. For birthweight outcomes, donor sperm showed a reduced odds of low (OR, 0.83; 95% CI, 0.76-0.91; aOR, 0.86; 95% CI, 0.78-0.94) and an increased odds of high (OR, 1.15; 95% CI, 1.07-1.23; aOR, 1.09; 95% CI, 1.01-1.17) birthweight. There was no confirmed difference in the odds ratios of very low (OR, 0.88; 95% CI, 0.74-1.06; aOR, 0.94; 95% CI, 0.78-1.13) or very high (OR, 1.21; 95% CI, 1.04-1.40; aOR, 1.15; 95% CI, 0.98-1.34) birthweight. Liveborn twins conceived with donor sperm, compared to partner sperm, were at reduced odds of very low (OR, 0.76; 95% CI, 0.66-0.88; aOR, 0.83; 95% CI, 0.72-0.96) and low (OR, 0.87; 95% CI, 0.81-0.93; aOR, 0.91; 95% CI, 0.85-0.98) birthweight. There was a suggestion of a reduced odds of very preterm (OR, 0.81; 95% CI, 0.70-0.95; aOR, 0.86; 95% CI, 0.74-1.01) and preterm (OR, 0.93; 95% CI, 0.86-1.01; aOR, 0.96; 95% CI, 0.88-1.04) birth. There was considerable uncertainty around the ORs for high (OR, 0.73; 95% CI, 0.31-1.72; aOR, 0.72; 95% CI, 0.29-1.80) and very high (OR, 1.02; 95% CI, 0.39-2.67; aOR, 1.34; 95% CI, 0.50-3.60) birthweight. CONCLUSION: Although unmeasured confounding remains a possibility, as paternal age, body mass index, and smoking status were unavailable for analysis, women, couples, service providers can be reassured that IVF livebirths conceived with donor sperm have no greater chance of adverse outcomes when compared to partner sperm.

Individual participant data meta-analysis of trials comparing frozen versus fresh embryo transfer strategy (INFORM): a protocol.

INTRODUCTION: Existing randomised controlled trials (RCTs) comparing a freeze-all embryo transfer strategy and a fresh embryo transfer strategy have shown conflicting results. A freeze-all or a fresh transfer policy may be preferable for some couples undergoing in-vitro fertilisation (IVF), but it is unclear which couples would benefit most from each policy, how and under which protocols. Therefore, we plan a systematic review and individual participant data meta-analysis of RCTs comparing a freeze-all and a fresh transfer policy. METHODS AND ANALYSIS: We will search electronic databases (Medline, Embase, PsycINFO and CENTRAL) and trial registries (ClinicalTrials.gov and the International Clinical Trials Registry Platform) from their inception to present to identify eligible RCTs. We will also check reference lists of relevant papers. The search was performed on 23 September 2020 and will be updated. We will include RCTs comparing a freeze-all embryo transfer strategy and a fresh embryo transfer strategy in couples undergoing IVF. The primary outcome will be live birth resulting from the first embryo transfer. All outcomes listed in the core outcome set for infertility research will be reported. We will invite the lead investigators of eligible trials to join the Individual participant data meta-analysis of trials comparing frozen versus fresh embryo transfer strategy (INFORM) collaboration and share the deidentified individual participant data (IPD) of their trials. We will harmonise the IPD and perform a two-stage meta-analysis and examine treatment-covariate interactions for important baseline characteristics. ETHICS AND DISSEMINATION: The study ethics have been granted by the Monash University Human Research Ethics Committee (Project ID: 30391). The findings will be disseminated via presentations at international conferences and publication in peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42021296566.

Predicting cumulative live birth for couples beginning their second complete cycle of in vitro fertilization treatment.

STUDY QUESTION: Can we develop an IVF prediction model to estimate individualized chances of a live birth over multiple complete cycles of IVF in couples embarking on their second complete cycle of treatment? SUMMARY ANSWER: Yes, our prediction model can estimate individualized chances of cumulative live birth over three additional complete cycles of IVF. WHAT IS KNOWN ALREADY: After the completion of a first complete cycle of IVF, couples who are unsuccessful may choose to undergo further treatment to have their first child, while those who have had a live birth may decide to have more children. Existing prediction models can estimate the overall chances of success in couples before commencing IVF but are unable to revise these chances on the basis of the couple's response to a first treatment cycle in terms of the number of eggs retrieved and pregnancy outcome. This makes it difficult for couples to plan and prepare emotionally and financially for the next step in their treatment. STUDY DESIGN, SIZE, DURATION: For model development, a population-based cohort was used of 49 314 women who started their second cycle of IVF including ICSI in the UK from 1999 to 2008 using their own oocytes and their partners' sperm. External validation was performed on data from 39 442 women who underwent their second cycle from 2010 to 2016. PARTICIPANTS/MATERIALS, SETTING, METHODS: Data about all UK IVF treatments were obtained from the Human Fertilisation and Embryology Authority (HFEA) database. Using a discrete time logistic regression model, we predicted the cumulative probability of live birth from the second up to and including the fourth complete cycles of IVF. Inverse probability weighting was used to account for treatment discontinuation. Discrimination was assessed using c-statistic and calibration was assessed using calibration-in-the-large and calibration slope. MAIN RESULTS AND THE ROLE OF CHANCE: Following exclusions, 49 314 women with 73 053 complete cycles were included. 12 408 (25.2%) had a live birth resulting from their second complete cycle. Cumulatively, 17 394 (35.3%) had a live birth over complete cycles two to four. The model showed moderate discriminative ability (c-statistic: 0.65, 95% CI: 0.64 to 0.65) and evidence of overprediction (calibration-in-the-large = -0.08) and overfitting (calibration slope 0.85, 95% CI: 0.81 to 0.88) in the validation cohort. However, after recalibration the fit was much improved. The recalibrated model identified the following key predictors of live birth: female age (38 versus 32 years-adjusted odds ratio: 0.59, 95% CI: 0.57 to 0.62), number of eggs retrieved in the first complete cycle (12 versus 4 eggs; 1.34, 1.30 to 1.37) and outcome of the first complete cycle (live birth versus no pregnancy; 1.78, 1.66 to 1.91; live birth versus pregnancy loss; 1.29, 1.23 to 1.36). As an example, a 32-year-old with 2 years of non-tubal infertility who had 12 eggs retrieved from her first stimulation and had a live birth during her first complete cycle has a 46% chance of having a further live birth from the second complete cycle of IVF and an 81% chance over a further three cycles. LIMITATIONS, REASONS FOR CAUTION: The developed model was updated using validation data that was 6 to 12 years old. IVF practice continues to evolve over time, which may affect the accuracy of predictions from the model. We were unable to adjust for some potentially important predictors, e.g. BMI, smoking and alcohol intake in women, as well as measures of ovarian reserve such as antral follicle count. These were not available in the linked HFEA dataset. WIDER IMPLICATIONS OF THE FINDINGS: By appropriately adjusting for couples who discontinue treatment, our novel prediction model will provide more realistic chances of live birth in couples starting a second complete cycle of IVF. Clinicians can use these predictions to inform discussion with couples who wish to plan ahead. This prediction tool will enable couples to prepare emotionally, financially and logistically for IVF treatment. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by an Elphinstone scholarship scheme at the University of Aberdeen and Aberdeen Fertility Centre, University of Aberdeen. The authors have no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Comparison of perinatal outcomes after frozen or fresh embryo transfer: separate analyses of singleton, twin, and sibling live births from a linked national in vitro fertilization registry.

OBJECTIVE: To determine whether perinatal outcomes following frozen vs. fresh embryo transfer (ET) differ within singletons, within sets of twins, and between siblings. DESIGN: Population-based retrospective cohort study. SETTING: Academic Medical School PATIENT(S): 200,075 live births in 151,561 women who underwent in vitro fertilization with frozen or fresh ET between 1992 and 2017. MAIN OUTCOME MEASURE(S): Gestational age at birth, birthweight, congenital anomaly, and healthy baby (≥37 weeks of gestation, birthweight 2,500-4,000 g, no congenital malformations). RESULT(S): There were 200,075 live births in 151,561 women including 132,679 singletons, 33,698 sets of twins, and 5,723 pairs of singleton siblings. In singletons, frozen ET was associated with a lower risk of very preterm birth (adjusted relative risk [aRR], 0.83; 95% confidence interval [CI], 0.73, 0.94), preterm birth (aRR, 0.93; 95% CI, 0.88, 0.97), low birthweight (<2,500 g) (aRR, 0.72; 95% CI, 0.68, 0.77), small for gestational age (aRR, 0.66; 95% CI, 0.62, 0.70) and congenital anomaly (aRR, 0.85; 95% CI, 0.78, 0.94), but higher risk of high birthweight (>4,000 g) (aRR, 1.64; 95% CI, 1.58, 1.72) and large for gestational age (aRR, 1.62; 95% CI, 1.55, 1.70) in comparison with fresh ET. In twins, frozen ET was associated with lower risk of very preterm birth (aRR, 0.84; 95% CI, 0.73, 0.97), and low birthweight (aRR, 0.72; 95% CI, 0.68, 0.77), but with a higher chance of a healthy baby (aRR, 1.11; 95% CI, 1.06, 1.16) compared to fresh ET. Singletons conceived following frozen ET had a lower risk of low birthweight (aRR, 0.56; 95% CI, 0.44, 0.74) and being small for gestational age (aRR, 0.54; 95% CI, 0.42, 0.68) than a singleton sibling born after a fresh ET. Frozen ET also was associated with higher risk of high birthweight (aRR, 1.85; 95% CI, 1.54, 2.24) and being large for gestational age (aRR, 1.81; 95% CI, 1.50, 2.20), and also were less likely to be preterm (aRR, 0.81; 95% CI, 0.67, 0.99). CONCLUSION(S): Our key finding is that singletons born following a frozen ET are less likely to be small for gestational age than a singleton sibling born following fresh ET but are more likely to be large for gestational age.

Predicting 10-year stroke mortality: development and validation of a nomogram.

Predicting long-term stroke mortality is a clinically important and unmet need. We aimed to develop and internally validate a 10-year ischaemic stroke mortality prediction score. In this UK cohort study, 10,366 patients with first-ever ischaemic stroke between January 2003 and December 2016 were followed up for a median (interquartile range) of 5.47 (2.96-9.15) years. A Cox proportional-hazards model was used to predict 10-year post-admission mortality. The predictors associated with 10-year mortality included age, sex, Oxfordshire Community Stroke Project classification, estimated glomerular filtration rate (eGFR), pre-stroke modified Rankin Score, admission haemoglobin, sodium, white blood cell count and comorbidities (atrial fibrillation, coronary heart disease, heart failure, cancer, hypertension, chronic obstructive pulmonary disease, liver disease and peripheral vascular disease). The model was internally validated using bootstrap resampling to assess optimism in discrimination and calibration. A nomogram was created to facilitate application of the score at the point of care. Mean age (SD) was 78.5 ± 10.9 years, 52% female. Most strokes were partial anterior circulation syndromes (38%). 10-year mortality predictors were: total anterior circulation stroke (hazard ratio, 95% confidence intervals) (2.87, 2.62-3.14), eGFR < 15 (1.97, 1.55-2.52), 1-year increment in age (1.04, 1.04-1.05), liver disease (1.50, 1.20-1.87), peripheral vascular disease (1.39, 1.23-1.57), cancers (1.37, 1.27-1.47), heart failure (1.24, 1.15-1.34), 1-point increment in pre-stroke mRS (1.20, 1.17-1.22), atrial fibrillation (1.17, 1.10-1.24), coronary heart disease (1.09, 1.02-1.16), chronic obstructive pulmonary disease (1.13, 1.03-1.25) and hypertension (0.77, 0.72-0.82). Upon internal validation, the optimism-adjusted c-statistic was 0.76 and calibration slope was 0.98. Our 10-year mortality model uses routinely collected point-of-care information. It is the first 10-year mortality score in stroke. While the model was internally validated, further external validation is also warranted.

Predicting personalized cumulative live birth following in vitro fertilization.

OBJECTIVE: To develop in vitro fertilization (IVF) prediction models to estimate the individualized chance of cumulative live birth at two time points: pretreatment (i.e., before starting the first complete cycle of IVF) and posttreatment (i.e., before starting the second complete cycle of IVF in those couples whose first complete cycle was unsuccessful). DESIGN: Population-based cohort study. SETTING: National data from the Society for Assisted Reproductive Technology (SART) Clinic Outcome Reporting System. PATIENT(S): Based on 88,614 women who commenced IVF treatment using their own eggs and partner's sperm in SART member clinics. INTERVENTION(S): Not applicable. MAIN OUTCOME MEASURE(S): The pretreatment model estimated the cumulative chance of a live birth over a maximum of three complete cycles of IVF, whereas the posttreatment model did so over the second and third complete cycles. One complete cycle included all fresh and frozen embryo transfers resulting from one episode of ovarian stimulation. We considered the first live birth episode, including singletons and multiple births. RESULT(S): Pretreatment predictors included woman's age (35 years vs. 25 years, adjusted odds ratio 0.69, 95% confidence interval 0.66-0.73) and body mass index (35 kg/m2 vs. 25 kg/m2, adjusted odds ratio 0.75, 95% confidence interval 0.72-0.78). The posttreatment model additionally included the number of eggs from the first complete cycle (15 vs. 9 eggs, adjusted odds ratio 1.10, 95% confidence interval 1.03-1.18). According to the pretreatment model, a nulliparous woman aged 34 years with a body mass index of 23.3 kg/m2, male partner infertility, and an antimüllerian hormone level of 3 ng/mL has a 61.7% chance of having a live birth over her first complete cycle of IVF (and a cumulative chance over three complete cycles of 88.8%). If a live birth is not achieved, according to the posttreatment model, her chance of having a live birth over the second complete cycle 1 year later (age 35 years, number of eggs 7) is 42.9%. The C-statistic for all models was between 0.71 and 0.73. CONCLUSION(S): The focus of previous IVF prediction models based on US data has been cumulative live birth excluding cycles involving frozen embryos. These novel prediction models provide clinically relevant estimates that could help clinicians and couples plan IVF treatment at different points in time.

Erratum to: Development of a clinical risk score for pain and function following total knee arthroplasty: results from the TRIO study.

[This corrects the article DOI: 10.1093/rap/rky021.][This corrects the article DOI: 10.1093/rap/rky021.].

Prevalence of PErioperAtive CHildhood obesitY in children undergoing general anaesthesia in the UK: a prospective, multicentre, observational cohort study.

BACKGROUND: Childhood obesity has become a serious global healthcare challenge. No UK data currently define its anaesthetic and perioperative implications. We aimed to determine obesity prevalence amongst UK children undergoing general anaesthesia and the incidence of predefined adverse perioperative events, and to compare perioperative obesity rates with National Child Measurement Programme (NCMP) data. METHODS: During a site-selected consecutive 7-day study period, all children (2-16 yr) undergoing general anaesthesia were included. Anonymised hospital, surgical, and procedural details; demographic data; and adverse perioperative events were collected prospectively by Paediatric Anaesthesia Trainee Research Network (PATRN) collaborators. RESULTS: For this study, 102 UK hospitals participated and 4232 cases were included in the final analysis; 76% of hospitals did not routinely calculate BMI. In addition, 3030 (71.6%; 95% confidence interval [CI]: 70.2-73.0%) children of healthy weight were compared with 537 (12.7%; 11.7-13.7%) children who were overweight and 478 (11.3%; 10.3-12.2%) children with obesity. Children with obesity (n=71; 14.9%) more commonly underwent (adeno)tonsillectomy than children of healthy weight (n=282; 9.3%; P<0.001; odds ratio [OR] 2.15; 95% CI: 1.58-2.92). Fewer children with obesity (n=365; 77% vs n=2552; 85%) were anaesthetised by consultant anaesthetists (OR 0.62; 95% CI: 0.48-0.79). Mask ventilation was difficult for 3.7% of children with obesity vs 0.6% of children of healthy weight (difference 3.0%; 95% CI: 1.3-4.7%; P<0.001). Comparison with NCMP data demonstrated an over-representation of obesity amongst the paediatric surgical population. CONCLUSIONS: This large multicentre cohort study suggests a concerning prevalence of children with obesity presenting for anaesthesia. These results should be used to inform optimal provision of care for this population and support perioperative healthcare initiatives to address the burden of childhood obesity. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03994419.

Predictive models of individual risk of elective caesarean section complications: a systematic review.

INTRODUCTION: With increasing caesarean section (c-section) rates, personalized communication of risk has become paramount. A reliable tool to predict complications would support evidence-based discussions around planned mode of birth. This systematic review aimed to identify, synthesize and quality appraise prognostic models of maternal complications of elective c-section. METHODS: MEDLINE, Embase, Web of Science, CINAHL and the Cochrane Library were searched on 27 January using terms relating to 'c-section', 'prognostic models' and complications such as 'infection'. Any study developing and/or validating a prognostic model for a maternal complication of elective c-section in the English language after January 1995 was selected for analysis. Data were extracted using a predetermined checklist: source of data; participants; outcome to be predicted; candidate predictors; sample size; missing data; model development; model performance; model evaluation; results; and interpretation. Quality was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST) tool. RESULTS: In total, 7752 studies were identified; of these, 16 full papers were reviewed and three eligible studies were identified, containing three prognostic models derived from hospitals in Japan, South Africa and the UK. The models predicted risk of blood transfusion, spinal hypotension and postpartum haemorrhage. The study authors deemed their studies to be exploratory, exploratory and confirmatory, respectively. From the three studies, a total of 29 unique candidate predictors were identified, with 15 predictors in the final models. Maternal age (n = 3), previous c-section (n = 2), placenta praevia (n = 2) and pre-operative haemoglobin (n = 2) were found to be common predictors amongst the included studies. None of the studies were externally validated and all had a high risk of bias due to the analysis technique used. CONCLUSION: Few models have been developed to predict complications of elective c-section. Existing models predicting blood transfusion, spinal hypotension and postpartum haemorrhage cannot be recommended for clinical practice. Future research should focus on identifying predictors known before surgery and validating the resulting models.

Country-level determinants of the severity of the first global wave of the COVID-19 pandemic: an ecological study.

OBJECTIVE: We aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic. DESIGN: Ecological study of publicly available data. Countries reporting >25 COVID-19 related deaths until 8 June 2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, population >65 years, average body mass index and smoking prevalence); economic parameters (gross domestic product per capita); environmental parameters (pollution levels and mean temperature (January-May); comorbidities (prevalence of diabetes, hypertension and cancer); health system parameters (WHO Health Index and hospital beds per 10 000 population); international arrivals; the stringency index, as a measure of country-level response to COVID-19; BCG vaccination coverage; UV radiation exposure; and testing capacity. Multivariable linear regression was used to analyse the data. PRIMARY OUTCOME: Country-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase. PARTICIPANTS: Thirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the UK and the USA. RESULTS: Of all country-level determinants included in the multivariable model, total number of international arrivals (beta 0.033 (95% CI 0.012 to 0.054)) and BCG vaccination coverage (-0.018 (95% CI -0.034 to -0.002)), were significantly associated with the natural logarithm of the mean death rate. CONCLUSIONS: International travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID-19 outbreaks and prevent related deaths.

Women's perspectives on smartphone apps for fertility tracking and predicting conception: a mixed methods study.

BACKGROUND: Women use fertility tracking apps (FTAs) for conception purposes, but user perspectives on FTA use for conception are largely unknown. In collaboration with SPD Clearblue, this study explored: how women trying to conceive use FTAs; women's knowledge of their conception chances; and women's feelings towards a potential natural conception prediction app (NCPA). METHODS: A mixed methods design was used (online survey and phone interviews). Participants were women 18-40 years old actively trying to conceive. RESULTS: The survey received 154 responses and 24 interviews were conducted. Thematic analysis of interviews found that women consider several factors before trying to conceive (ex. age, financial and job security, stability of relationship, etc.) and may adopt lifestyle and behaviour changes when trying (ex. increasing exercise, smoking cessation, diet changes, etc.). Survey results indicated that nearly all respondents were aware of FTAs (n = 146, 94.8%), however, several other fertility and conception information sources were also used (ex. health care providers, online sources, family and friends, etc.). Nearly all respondents reported they would use an NCPA (n = 153, 99.4%). During interviews women had positive feelings towards such an app due to it offering new and individualised information, but worried the app could provide upsetting information. CONCLUSION: This research elaborates on women's uses of and interest in FTAs. Stakeholders should use this research to reflect on current conception experiences and possibilities for improvement through development of an NCPA. Future research should seek opinions from a more diverse sample of women to inform the development of an inclusive NCPA.

Validation of Risk Prediction Models to Inform Clinical Decisions After Acute Kidney Injury.

RATIONALE & OBJECTIVE: There is limited evidence to guide follow-up after acute kidney injury (AKI). Knowledge gaps include which patients to prioritize, at what time point, and for mitigation of which outcomes. In this study, we sought to compare the net benefit of risk model-based clinical decisions following AKI. STUDY DESIGN: External validation of 2 risk models of AKI outcomes: the Grampian -Aberdeen (United Kingdom) AKI readmissions model and the Alberta (Canada) kidney disease risk model of chronic kidney disease (CKD) glomerular (G) filtration rate categories 4 and 5 (CKD G4 and G5). Process mining to delineate existing care pathways. SETTING & PARTICIPANTS: Validation was based on data from adult hospital survivors of AKI from Grampian, 2011-2013. PREDICTORS: KDIGO-based measures of AKI severity and comorbidities specified in the original models. OUTCOMES: Death or readmission within 90 days for all hospital survivors. Progression to new CKD G4-G5 for patients surviving at least 90 days after AKI. ANALYTICAL APPROACH: Decision curve analysis to assess the "net benefit" of use of risk models to guide clinical care compared to alternative approaches (eg, prioritizing all AKI, severe AKI, or only those without kidney recovery). RESULTS: 26,575 of 105,461 hospital survivors in Grampian (mean age, 60.9 ± 19.8 [SD] years) were included for validation of the death or readmission model, and 9,382 patients (mean age, 60.9 ± 19.8 years) for the CKD G4-G5 model. Both models discriminated well (area under the curve [AUC], 0.77 and 0.86, respectively). Decision curve analysis showed greater net benefit for follow up of all AKI than only severe AKI in most cases. Both original and refitted models provided net benefit superior to any other decision strategy. In process mining of all hospital discharges, 41% of readmissions and deaths occurred among people recovering after AKI. 1,464 of 3,776 people (39%) readmitted after AKI had received no intervening monitoring. LIMITATIONS: Both original models overstated risks, indicating a need for regular updating. CONCLUSIONS: Follow up after AKI has potential net benefit for preempting readmissions, death, and subsequent CKD progression. Decisions could be improved by using risk models and by focusing on AKI across a full spectrum of severity. The current lack of monitoring among many with poor outcomes indicates possible opportunities for implementation of decision support.

Outcomes following Notched Ruthenium-106 Plaque Brachytherapy for Juxtapapillary Choroidal Melanomas.

PURPOSE: This study aimed to evaluate the outcomes of juxtapapillary choroidal melanomas treated with notched ruthenium-106 plaques. METHODS: Juxtapapillary choroidal melanomas (tumours within 2 disc diameters from the optic disc) treated with notched ruthenium-106 plaques (Eckert & Ziegler, BEBIG, Berlin, Germany) at the Scottish Ocular Oncology Service between 2009 and 2015 were retrospectively reviewed. The data were analysed with respect to various outcome measures including recurrence, complications, vision, and eye preservation. RESULTS: We reviewed 40 patients with a median tumour diameter of 8.4 mm (range 5-17 mm) and a median thickness of 2.5 mm (range 1.1-6 mm). AJCC tumour category distribution was 62.5% T1, 32.5% T2, and 5% T3 tumours. The mean presenting vision was 0.3 logMAR, and the mean final vision was 0.7 logMAR, with 62.5% retaining >1.0 logMAR and 50% retaining >0.3 logMAR at the final follow-up. The median follow-up was 51 months (14-100 months). Over the maximum follow-up time, 13 tumours (32.5%) recurred. Six of these were treated with salvage proton beam therapy (PBT), 2 with transpupillary thermotherapy followed by PBT, and 5 with enucleation. The final eye retention rate was 87.5%. Complications included maculopathy (10%), retinal detachment (5%), neovascular glaucoma (2.5%), and diplopia (2.5%). The observed risk of recurrence over 5 years was 31% (95% CI: 14.1%, 47.8%), and the risk of enucleation over 5 years was 11.5% (95% CI: 0.9%, 21.8%). CONCLUSION: Juxtapapillary choroidal melanomas treated with notched ruthenium plaques have a high recurrence rate and frequently need salvage treatment with PBT for tumour control. This has led to a change in our practice toward offering PBT as the first-line treatment for these patients.