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      Accuracy of in-utero MRI to detect fetal brain abnormalities and prognosticate developmental outcome: postnatal follow-up of the MERIDIAN cohort

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          Summary

          Background

          In utero MRI (iuMRI) detects fetal brain abnormalities more accurately than ultrasonography and provides additional clinical information in around half of pregnancies. We aimed to study whether postnatal neuroimaging after age 6 months changes the diagnostic accuracy of iuMRI and its ability to predict developmental outcome.

          Methods

          Families enrolled in the MERIDIAN study whose child survived to age 3 years were invited to have a case note review and assessment of developmental outcome with the Bayley Scales of Infant and Toddler Development, the Ages and Stages Questionnaire, or both. A paediatric neuroradiologist, masked to the iuMRI results, reviewed the postnatal neuroimaging if the clinical report differed from iuMRI findings. Diagnostic accuracy was recalculated. A paediatric neurologist and neonatologist categorised participants' development as normal, at risk, or abnormal, and the ability of iuMRI and ultrasonography to predict developmental outcome were assessed.

          Findings

          210 participants had case note review, of whom 81 (39%) had additional investigations after age 6 months. The diagnostic accuracy of iuMRI remained higher than ultrasonography (proportion of correct cases was 529 [92%] of 574 vs 387 [67%] of 574; absolute difference 25%, 95% CI 21 to 29; p<0·0001). Developmental outcome data were analysed in 156 participants, and 111 (71%) were categorised as normal or at risk. Of these 111 participants, prognosis was normal or favourable for 56 (51%) using ultrasonography and for 76 (69%) using iuMRI (difference in specificity 18%, 95% CI 7 to 29; p=0·0008). No statistically significant difference was seen in infants with abnormal outcome (difference in sensitivity 4%, 95% CI −10 to 19; p=0·73).

          Interpretation

          iuMRI remains the optimal tool to identify fetal brain abnormalities. It is less accurate when used to predict developmental outcome, although better than ultrasonography for identifying children with normal outcome. Further work is needed to determine how the prognostic abilities of iuMRI can be improved.

          Funding

          National Institute for Health Research Health Technology Assessment programme.

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          Most cited references31

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          Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers

          Background Making evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric estimates improves patients’ risk perception and leads to better informed decision making. This paper summarises current “best practices” in communication of evidence-based numeric outcomes for developers of patient decision aids (PtDAs) and other health communication tools. Method An expert consensus group of fourteen researchers from North America, Europe, and Australasia identified eleven main issues in risk communication. Two experts for each issue wrote a “state of the art” summary of best evidence, drawing on the PtDA, health, psychological, and broader scientific literature. In addition, commonly used terms were defined and a set of guiding principles and key messages derived from the results. Results The eleven key components of risk communication were: 1) Presenting the chance an event will occur; 2) Presenting changes in numeric outcomes; 3) Outcome estimates for test and screening decisions; 4) Numeric estimates in context and with evaluative labels; 5) Conveying uncertainty; 6) Visual formats; 7) Tailoring estimates; 8) Formats for understanding outcomes over time; 9) Narrative methods for conveying the chance of an event; 10) Important skills for understanding numerical estimates; and 11) Interactive web-based formats. Guiding principles from the evidence summaries advise that risk communication formats should reflect the task required of the user, should always define a relevant reference class (i.e., denominator) over time, should aim to use a consistent format throughout documents, should avoid “1 in x” formats and variable denominators, consider the magnitude of numbers used and the possibility of format bias, and should take into account the numeracy and graph literacy of the audience. Conclusion A substantial and rapidly expanding evidence base exists for risk communication. Developers of tools to facilitate evidence-based decision making should apply these principles to improve the quality of risk communication in practice.
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            Neurologic and developmental disability after extremely preterm birth. EPICure Study Group.

            Small studies show that many children born as extremely preterm infants have neurologic and developmental disabilities. We evaluated all children who were born at 25 or fewer completed weeks of gestation in the United Kingdom and Ireland from March through December 1995 at the time when they reached a median age of 30 months. Each child underwent a formal assessment by an independent examiner. Development was evaluated with use of the Bayley Scales of Infant Development, and neurologic function was assessed by a standardized examination. Disability and severe disability were defined by predetermined criteria. At a median age of 30 months, corrected for gestational age, 283 (92 percent) of the 308 surviving children were formally assessed. The mean (+/-SD) scores on the Bayley Mental and Psychomotor Developmental Indexes, referenced to a population mean of 100, were 84+/-12 and 87+/-13, respectively. Fifty-three children (19 percent) had severely delayed development (with scores more than 3 SD below the mean), and a further 32 children (11 percent) had scores from 2 SD to 3 SD below the mean. Twenty-eight children (10 percent) had severe neuromotor disability, 7 (2 percent) were blind or perceived light only, and 8 (3 percent) had hearing loss that was uncorrectable or required aids. Overall, 138 children had disability (49 percent; 95 percent confidence interval, 43 to 55 percent), including 64 who met the criteria for severe disability (23 percent; 95 percent confidence interval, 18 to 28 percent). When data from 17 assessments by local pediatricians were included, 155 of the 314 infants discharged (49 percent) had no disability. Severe disability is common among children born as extremely preterm infants.
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              Using the Bayley-III to assess neurodevelopmental delay: which cut-off should be used?

              As the latest edition of the Bayley Scales (Bayley-III) produces higher scores than its predecessor (BSID-II), there is uncertainty about how to classify moderate-severe neurodevelopmental delay. We have investigated agreement between classifications of delay made using the BSID-II and Bayley-III. BSID-II Mental Development Index (MDI) and Bayley-III cognitive and language scales were administered in 185 extremely preterm (<27 wk) children. A combined Bayley-III score (CB-III) was computed. Agreement between delay classified using MDI scores <70 and various Bayley-III cut-offs was assessed. Bayley-III cognitive and language scores were close to the normative mean and were higher than BSID-II MDI scores. Nineteen (10.2%) children had MDI <70. Bayley-III scores <70 significantly underestimated the proportion with MDI <70. Bayley-III cognitive and language scores <85 had 99% agreement with MDI <70 and underestimated delay by 1.1%. CB-III scores <80 had 98% agreement and produced the same proportion with delay. Bayley-III cognitive and language scores <85 or CB-III scores <80 provide the best definition of moderate-severe neurodevelopmental delay for equivalence with MDI <70. CB-III scores have the advantage of producing a single continuous outcome measure but require further validation. The relative accuracy of both tests for predicting long-term outcomes requires investigation.
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                Author and article information

                Contributors
                Journal
                Lancet Child Adolesc Health
                Lancet Child Adolesc Health
                The Lancet. Child & Adolescent Health
                Elsevier Ltd
                2352-4642
                2352-4650
                1 February 2020
                February 2020
                : 4
                : 2
                : 131-140
                Affiliations
                [a ]Department of Paediatric and Perinatal Neurology, Sheffield Children's Hospital NHS Foundation Trust, Ryegate Children's Centre, Sheffield, UK
                [b ]Newcastle Neonatal Service, Ward 35 Neonatal Unit, Royal Victoria Infirmary, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
                [c ]Clinical Trials Research Unit, School Health and Related Research, University of Sheffield, Sheffield, UK
                [d ]Department of Paediatric Neuroradiology, Sheffield Children's Hospital NHS Foundation Trust, Western Bank, Sheffield, UK
                [e ]Academic Unit of Radiology, University of Sheffield, Royal Hallamshire Hospital, Sheffield, UK
                Author notes
                [* ]Correspondence to: Miss Cara Mooney, Clinical Trials Research Unit, School Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK c.d.mooney@ 123456sheffield.ac.uk
                Article
                S2352-4642(19)30349-9
                10.1016/S2352-4642(19)30349-9
                6988445
                31786091
                37c1a99c-ba68-4f5a-95e3-f65bb0720d5c
                © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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