METHODS: Retrospective data of 347 patients, consisting of maternal demographics and ultrasound parameters collected between the 20th and 25th gestational weeks, were studied. ML models were applied to different combinations of the parameters to predict SGA and severe SGA at birth (defined as 10th and third centile birth weight).
RESULTS: Using second-trimester measurements, ML models achieved an accuracy of 70% and 73% in predicting SGA and severe SGA whereas clinical guidelines had accuracies of 64% and 48%. Uterine PI (Ut PI) was found to be an important predictor, corroborating with existing literature, but surprisingly, so was nuchal fold thickness (NF). Logistic regression showed that Ut PI and NF were significant predictors and statistical comparisons showed that these parameters were significantly different in disease. Further, including NF was found to improve ML model performance, and vice versa.
CONCLUSION: ML could potentially improve the prediction of SGA at birth from second-trimester measurements, and demonstrated reduced NF to be an important predictor. Early prediction of SGA allows closer clinical monitoring, which provides an opportunity to discover any underlying diseases associated with SGA.
METHODS: 2010-2015 incidence data for influenza A (IAV), influenza B (IBV), respiratory syncytial (RSV) and parainfluenza (PIV) virus infections were collected from 18 sites (14 countries), consisting of local (n = 6), regional (n = 9) and national (n = 3) laboratories using molecular diagnostic methods. Each site submitted monthly virus incidence data, together with details of their patient populations tested and diagnostic assays used.
RESULTS: For the Northern Hemisphere temperate countries, the IAV, IBV and RSV incidence peaks were 2-6 months out of phase with those in the Southern Hemisphere, with IAV having a sharp out-of-phase difference at 6 months, whereas IBV and RSV showed more variable out-of-phase differences of 2-6 months. The tropical sites Singapore and Kuala Lumpur showed fluctuating incidence of these viruses throughout the year, whereas subtropical sites such as Hong Kong, Brisbane and Sydney showed distinctive biannual peaks for IAV but not for RSV and PIV.
CONCLUSIONS: There was a notable pattern of synchrony of IAV, IBV and RSV incidence peaks globally, and within countries with multiple sampling sites (Canada, UK, Australia), despite significant distances between these sites.
METHODS: A total of 29 international experts with clinical and/or research experience in GD completed three iterative rounds of a Delphi survey. Experts rated proposed criteria in progressive rounds until a pre-determined level of agreement was achieved.
RESULTS: For DSM-5 IGD criteria, there was an agreement both that a subset had high diagnostic validity, clinical utility and prognostic value and that some (e.g. tolerance, deception) had low diagnostic validity, clinical utility and prognostic value. Crucially, some DSM-5 criteria (e.g. escapism/mood regulation, tolerance) were regarded as incapable of distinguishing between problematic and non-problematic gaming. In contrast, ICD-11 diagnostic guidelines for GD (except for the criterion relating to diminished non-gaming interests) were judged as presenting high diagnostic validity, clinical utility and prognostic value.
CONCLUSIONS: This Delphi survey provides a foundation for identifying the most diagnostically valid and clinically useful criteria for GD. There was expert agreement that some DSM-5 criteria were not clinically relevant and may pathologize non-problematic patterns of gaming, whereas ICD-11 diagnostic guidelines are likely to diagnose GD adequately and avoid pathologizing.