Objectives The objective of this article is to characterize olfactory stimulation as a trigger of headaches attacks and differentiation between migraine and other primary headaches. Participants and methods The study was prospective and experimental, with comparison of groups. A total of 158 volunteers (73 men and 85 women) were diagnosed with primary headaches, according to the criteria of the International Classification of Headache Disorders, Third Edition (beta version) (ICHD-3β). The study was conducted by two examiners; one of them was assigned to diagnose the presence and type of primary headache, while the other was responsible for exposing the volunteers to odor and recording the effects of this exposure. Results Of the 158 volunteers with headache, there were 72 (45.6%) cases of migraine and 86 (54.4%) with other primary headaches. In both groups, there were differences in headache characteristics (χ= 4.132; p = 0.046). Headache attacks (25/72; 34.7%) and nausea (5/72; 6.9%) were triggered by odor only in patients with migraine, corresponding to 19.0% (30/158) of the sample, but in none with other primary headaches (χ= 43.78; p < 0.001). Headache occurred more often associated with nausea ( p = 0.146) and bilateral location ( p = 0.002) in migraineurs who had headache triggered by odor. Headache was triggered after 118 ± 24.6 min and nausea after 72.8 ± 84.7 min of exposure to odor. Conclusions The odor triggered headache attacks or nausea only in migraineurs. Therefore, headache triggered by odors may be considered a factor of differentiation between migraine and other primary headaches and this trigger seems very specific of migraine.

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For atypical brainstem lesions, histological diagnosis can have an impact on treatment, especially in cases where diffuse glioma is not found. Since radiotherapy is the only therapeutic modality that has shown clinical and radiographic improvement in patients with diffuse glioma, the misdiagnosis of diffuse glioma can have drastic consequences, particularly in patients with nontumorous lesions. Thus, the purpose of this study was to evaluate the impact of histological diagnosis on the treatment of atypical brainstem lesions. This was a retrospective study of 31 patients who underwent biopsy of atypical brainstem lesions. The procedures were performed between January 2008 and December 2018 at the Life Center Hospital and Santa Casa de Belo Horizonte, MG, Brazil. A diagnosis was obtained in 26 (83.9%) cases. Three patients presented complications: one presented bleeding with no clinical repercussions and two showed worsening of neurological deficit, only one of which was definitive. No mortality occurred due to the procedure. The histological diagnosis was diffuse glioma in seven cases (22.6%) and not diffuse glioma in 19 cases (61.3%). Thus, the histological diagnosis had an impact on the treatment of 19 patients (treatment impact rate: 61.3%). The histological diagnosis of intrinsic brainstem lesions is a safe, efficient procedure with a high diagnosis rate, and as such, it should be considered in the management of atypical lesions.

Objectives:To find a pretreatment predictor for achieving a live birth. Assisted reproduction technology with IVF/ICSI is the ultimate chance for some couples to conceive a child. The expectations are high and it is important to give them a realistic perspective about the chances of achieving a live birth.Methods:A retrospective cohort study of all IVF/ICSI cycles performed in our center between 2012 and 2016. We considered only those cycles with a live birth delivery after 24 weeks, or cycles with no surplus embryos left. The following data was evaluated: AMH; AFC; age; BMI; previous diagnosis; type of treatment; number of previous deliveries; ethnicity, smoking status. Univariate and multivariate analysis were used to examine the association of live birth with baseline patient characteristics. We determined the odds-ratio for all the statistically significant variables (p<0.05), in a multivariate model. The results are presented according to the predictors founded.Results:739 cycles were evaluated: 9.1% were canceled; 10.2% did not have oocytes; 15.6% did not have D2 embryos; 31.4% achieved a live birth. The univariate analysis revealed statistically significant differences regarding AMH, AFC and women’s age between couples with and without a live birth (p<0.001), and the cause of infertility. We found no association with live births in other variables. These variables were categorized and used in a multivariate analysis.Conclusion:Age, AMH, AFC and cause, when sub-classified, are independently associated with the results of an IVF/ICSI treatment. These results enable couples to face real expectations in their particular scenario.

The aim of this study was to build an Artificial Neural Network (ANN) complemented by a decision tree to predict the chance of live birth after an In Vitro Fertilization (IVF)/Intracytoplasmic Sperm Injection (ICSI) treatment, before the first embryo transfer, using demographic and clinical data. Overall, 26 demographic and clinical data from 1193 cycles who underwent an IVF/ICSI treatment at Centro de Infertilidade e Reprodução Medicamente Assistida, between 2012 and 2019, were analyzed. An ANN was constructed by selecting experimentally the input variables which most correlated to the target through Pearson correlation. The final used variables were: woman’s age, total dose of gonadotropin, number of eggs, number of embryos and Antral Follicle Count (AFC). A decision tree was developed considering as an initial set the input variables integrated in the previous model. The ANN model was validated by the holdout method and the decision tree model by the 10-fold cross method. The ANN accuracy was 75.0% and the Area Under the Receiver Operating Characteristic (AUROC) curve was 75.2% (95% Confidence Interval (CI): 72.5–77.5%), whereas the decision tree model reached 75.0% and 74.9% (95% CI: 72.3–77.5%). These results demonstrated that both ANN and decision tree methods are fair for prediction the chance of conceive after an IVF/ICSI cycle.