The authors reply: In response to Stanford et al.: after the exclusion of patients receiving insulin, the median gestational weight gain among the women in our study was lower in the metformin group than in the placebo group (4.6 kg [interquartile range, 1.3 to 7.2] vs. 6.3 kg [interquartile range, 2.9 to 9.2], P<0.001). In an evaluation of changes in postpartum weight from the initial antenatal visit, the median gestational weight loss was higher in the metformin group than in the placebo group (1.9 kg [interquartile range, −5.1 to 0.2] vs. 0 kg [interquartile range, −3.9 to 1.5], P = 0.02). We agree that metformin might reduce the risk of long-term obesity in these women.In response to Sahin and Corapcioglu: the American Diabetes Association classifies metformin as a category B drug (i.e., no evidence of risk in humans) during pregnancy. In the United Kingdom, metformin is recommended by the National Institute for Health and Care Excellence.1 There is no evidence of an increase in congenital malformations (including testicular abnormalities or defects in growth or motor development) in babies born to mothers treated with metformin.2,3 Blood-pressure results in a large cohort of 2-year-old children showed no differences between those whose mothers had received insulin and those whose mothers had received metformin. 4 Active B 12 (holotranscobalamin) and methylmalonic acid are better measures of vitamin B 12 status than are serum levels and do not appear to be pathologically altered in patients with type 2 diabetes after metformin treatment. DOI: 10.1056/NEJMc1603067Transient Smartphone "Blindness" To the Editor: Transient monocular vision loss is a common clinical presentation, and the cause is not always thromboembolic.1 We present two cases in which careful history taking established a benign cause (for the case histories, see the Supplementary Appendix, available with the full text of this letter at NEJM.org).A 22-year-old woman presented with a several months' history of recurrent impaired vision in the right eye that occurred at night. The results of ophthalmic and cardiovascular examinations were normal. Vitamin A levels and the results of magnetic resonance angiography, echocardiography, and a thrombophilia screening were also normal.The second case involved a 40-year-old woman who presented with a 6-month history of recurrent monocular visual impairment on waking, lasting up to 15 minutes. The results of investigations for a vascular cause were again normal. Aspirin therapy had been commenced. When the patients were seen in our neuroophthalmic clinic, detailed history taking revealed that symptoms occurred only after several minutes of viewing a smartphone screen, in the dark, while lying in bed (before going to sleep in the first case and after waking in the second). Both patients were asked to experiment and record their symptoms. They reported that the symptoms were always in the eye contralateral to the side on which the patient was lying.We hypothesized that the symptoms were dueThe New England ...

ObjectiveAccurate preoperative predictions of seizure freedom following surgery for focal drug resistant epilepsy remain elusive. Our objective was to systematically evaluate all meta-analyses of epilepsy surgery with seizure freedom as the primary outcome, to identify clinical features that are consistently prognostic and should be included in the future models.MethodsWe searched PubMed and Cochrane using free-text and Medical Subject Heading (MeSH) terms according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses. This study was registered on PROSPERO. We classified features as prognostic, non-prognostic and uncertain and into seven subcategories: ‘clinical’, ‘imaging’, ‘neurophysiology’, ‘multimodal concordance’, ‘genetic’, ‘surgical technique’ and ‘pathology’. We propose a structural causal model based on these features.ResultsWe found 46 features from 38 meta-analyses over 22 years. The following were consistently prognostic across meta-analyses: febrile convulsions, hippocampal sclerosis, focal abnormal MRI, Single-Photon Emission Computed Tomography (SPECT) coregistered to MRI, focal ictal/interictal EEG, EEG-MRI concordance, temporal lobe resections, complete excision, histopathological lesions, tumours and focal cortical dysplasia type IIb. Severe learning disability was predictive of poor prognosis. Others, including sex and side of resection, were non-prognostic. There were limited meta-analyses investigating genetic contributions, structural connectivity or multimodal concordance and few adjusted for known confounders or performed corrections for multiple comparisons.SignificanceSeizure-free outcomes have not improved over decades of epilepsy surgery and despite a multitude of models, none prognosticate accurately. Our list of multimodal population-invariant prognostic features and proposed structural causal model may serve as an objective foundation for statistical adjustments of plausible confounders for use in high-dimensional models.PROSPERO registration numberCRD42021185232.

Objectives: One-third of individuals with focal epilepsy do not achieve seizure freedom despite best medical therapy. Mesial temporal lobe epilepsy (MTLE) is the most common form of drug resistant focal epilepsy. Surgery may lead to long-term seizure remission if the epileptogenic zone can be defined and safely removed or disconnected. We compare published outcomes following open surgical techniques, radiosurgery (SRS), laser interstitial thermal therapy (LITT) and radiofrequency ablation (RF-TC).Methods: PRISMA systematic review was performed through structured searches of PubMed, Embase and Cochrane databases. Inclusion criteria encompassed studies of MTLE reporting seizure-free outcomes in ≥10 patients with ≥12 months follow-up. Due to variability in open surgical approaches, only comparative studies were included to minimize the risk of bias. Random effects meta-analysis was performed to calculate effects sizes and a pooled estimate of the probability of seizure freedom per person-year. A mixed effects linear regression model was performed to compare effect sizes between interventions.Results: From 1,801 screened articles, 41 articles were included in the quantitative analysis. Open surgery included anterior temporal lobe resection as well as transcortical and trans-sylvian selective amygdalohippocampectomy. The pooled seizure-free rate per person-year was 0.72 (95% CI 0.66–0.79) with trans-sylvian selective amygdalohippocampectomy, 0.59 (95% CI 0.53–0.65) with LITT, 0.70 (95% CI 0.64–0.77) with anterior temporal lobe resection, 0.60 (95% CI 0.49–0.73) with transcortical selective amygdalohippocampectomy, 0.38 (95% CI 0.14–1.00) with RF-TC and 0.50 (95% CI 0.34–0.73) with SRS. Follow up duration and study sizes were limited with LITT and RF-TC. A mixed-effects linear regression model suggests significant differences between interventions, with LITT, ATLR and SAH demonstrating the largest effects estimates and RF-TC the lowest.Conclusions: Overall, novel “minimally invasive” approaches are still comparatively less efficacious than open surgery. LITT shows promising seizure effectiveness, however follow-up durations are shorter for minimally invasive approaches so the durability of the outcomes cannot yet be assessed. Secondary outcome measures such as Neurological complications, neuropsychological outcome and interventional morbidity are poorly reported but are important considerations when deciding on first-line treatments.

Background: Epilepsy affects 50 million people worldwide and a third are refractory to medication. If a discrete cerebral focus or network can be identified, neurosurgical resection can be curative. Most excisions are in the temporal-lobe, and are more likely to result in seizure-freedom than extra-temporal resections. However, less than half of patients undergoing surgery become entirely seizure-free. Localizing the epileptogenic-zone and individualized outcome predictions are difficult, requiring detailed evaluations at specialist centers.Methods: We used bespoke natural language processing to text-mine 3,800 electronic health records, from 309 epilepsy surgery patients, evaluated over a decade, of whom 126 remained entirely seizure-free. We investigated the diagnostic performances of machine learning models using set-of-semiology (SoS) with and without hippocampal sclerosis (HS) on MRI as features, using STARD criteria.Findings: Support Vector Classifiers (SVC) and Gradient Boosted (GB) decision trees were the best performing algorithms for temporal-lobe epileptogenic zone localization (cross-validated Matthews correlation coefficient (MCC) SVC 0.73 ± 0.25, balanced accuracy 0.81 ± 0.14, AUC 0.95 ± 0.05). Models that only used seizure semiology were not always better than internal benchmarks. The combination of multimodal features, however, enhanced performance metrics including MCC and normalized mutual information (NMI) compared to either alone (p &lt; 0.0001). This combination of semiology and HS on MRI increased both cross-validated MCC and NMI by over 25% (NMI, SVC SoS: 0.35 ± 0.28 vs. SVC SoS+HS: 0.61 ± 0.27).Interpretation: Machine learning models using only the set of seizure semiology (SoS) cannot unequivocally perform better than benchmarks in temporal epileptogenic-zone localization. However, the combination of SoS with an imaging feature (HS) enhance epileptogenic lobe localization. We quantified this added NMI value to be 25% in absolute terms. Despite good performance in localization, no model was able to predict seizure-freedom better than benchmarks. The methods used are widely applicable, and the performance enhancements by combining other clinical, imaging and neurophysiological features could be similarly quantified. Multicenter studies are required to confirm generalizability.Funding: Wellcome/EPSRC Center for Interventional and Surgical Sciences (WEISS) (203145Z/16/Z).

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Semiology describes the evolution of symptoms and signs during epileptic seizures and contributes to the evaluation of individuals with focal drug-resistant epilepsy for curative resection. Semiology varies in complexity from elementary sensorimotor seizures arising from primary cortex to complex behaviours and automatisms emerging from distributed cerebral networks. Detailed semiology interpreted by expert epileptologists may point towards the likely site of seizure onset, but this process is subjective. No study has captured the variances in semiological localising values in a data-driven manner to allow objective and probabilistic determinations of implicated networks and nodes. We curated an open dataset from the epilepsy literature, in accordance with PRISMA guidelines, linking semiology to hierarchical brain localisations. A total of 11230 datapoints were collected from 4643 patients across 309 articles, labelled using ground-truths (postoperative seizure-freedom, concordance of imaging and neurophysiology, and/or invasive EEG) and a designation method that distinguished between semiologies arising from a predefined cortical region and descriptions of neuroanatomical localisations responsible for generating a particular semiology. This allowed us to mitigate temporal lobe publication bias by filtering studies that preselected patients based on prior knowledge of their seizure-foci. Using this dataset, we describe the probabilistic landscape of semiological localising values as forest plots at the resolution of seven major brain regions: temporal, frontal, cingulate, parietal, occipital, insula, and hypothalamus, and five temporal subregions. We evaluated the intrinsic value of any one semiology over all other ictal manifestations. For example, epigastric auras implicated the temporal lobe with 83% probability when not accounting for the publication bias that favoured temporal lobe epilepsies. Unbiased results for a prior distribution of cortical localisations revised the prevalence of temporal lobe epilepsies from 66% to 44%. Therefore, knowledge about the presence of epigastric auras updates localisation to the temporal lobe with an odds ratio (OR) of 2.4 (CI95% [1.9, 2.9]; and specifically, mesial temporal structures OR 2.8[2.3, 2.9]), attesting the value of epigastric auras. As a further example, although head version is thought to implicate the frontal lobes, it did not add localising value compared to the prior distribution of cortical localisations (OR 0.9[0.7, 1.2]). Objectification of the localising values of the twelve most common semiologies provides a complementary view of brain dysfunction to that of lesion-deficit mappings, as instead of linking brain regions to phenotypic-deficits, semiological phenotypes are linked back to brain sources. This work enables coupling of seizure-propagation with ictal-manifestations, and clinical support algorithms for localising seizure phenotypes.

Background Mindstep is an app that aims to improve dementia screening by assessing cognition and risk factors. It considers important clinical risk factors, including prodromal symptoms, mental health disorders, and differential diagnoses of dementia. The 9-item Patient Health Questionnaire for depression (PHQ-9) and the 7-item Generalized Anxiety Disorder Scale (GAD-7) are widely validated and commonly used scales used in screening for depression and anxiety disorders, respectively. Shortened versions of both (PHQ-2/GAD-2) have been produced. Objective We sought to develop a method that maintained the brevity of these shorter questionnaires while maintaining the better precision of the original questionnaires. Methods Single questions were designed to encompass symptoms covered in the original questionnaires. Answers to these questions were combined with PHQ-2/GAD-2, and anonymized risk factors were collected by Mindset4Dementia from 2235 users. Machine learning models were trained to use these single questions in combination with data already collected by the app: age, response to a joke, and reporting of functional impairment to predict binary and continuous outcomes as measured using PHQ-9/GAD-7. Our model was developed with a training data set by using 10-fold cross-validation and a holdout testing data set and compared to results from using the shorter questionnaires (PHQ-2/GAD-2) alone to benchmark performance. Results We were able to achieve superior performance in predicting PHQ-9/GAD-7 screening cutoffs compared to PHQ-2 (difference in area under the curve 0.04, 95% CI 0.00-0.08, P=.02) but not GAD-2 (difference in area under the curve 0.00, 95% CI –0.02 to 0.03, P=.42). Regression models were able to accurately predict total questionnaire scores in PHQ-9 (R2=0.655, mean absolute error=2.267) and GAD-7 (R2=0.837, mean absolute error=1.780). Conclusions We app-adapted PHQ-4 by adding brief summary questions about factors normally covered in the longer questionnaires. We additionally trained machine learning models that used the wide range of additional information already collected in Mindstep to make a short app-based screening tool for affective disorders, which appears to have superior or equivalent performance to well-established methods.

A 40-year-old woman presented with a side-locked headache with autonomic features, which then switched sides before reverting to the original side. The atypical features of side swapping, partial response to indometacin and abnormal optic disc appearances ultimately led to a diagnosis of recurrent posterior scleritis. We discuss the differential diagnosis of trigeminal autonomic cephalgias and its secondary causes, and provide practical pointers for its investigation and management.