In neuropsychological disorders, the significant abnormalities in the brain connections in some regions are observed. This paper presents a novel model to demonstrate the connections between different regions in children with autism. The proposed model first conducts the wavelet decomposition of electroencephalography signals by wavelet transform then the features are extracted, such as relative energy and entropy. These features are fed to the 3D-cellular neural network model as inputs to indicate the brain connections. The results showed that there are significant differences and abnormalities in the left hemisphere, (p<0.05) at the electrodes AF3, F3, P7, T7 and O1 in alpha band, AF3, F7, T7 and O1 in beta band, T7 and P7 in gamma band for children with autism compared with the control children. Also, the evaluation of the obtained connections values between brain regions indicated that there are more abnormalities in the connectivity of frontal and parietal lobes and the relations of the neighboring regions in all three bands especially in gamma band for autistic children. Evaluation of the analysis demonstrated that alpha frequency band had the best distinction level of 96.6% based on the obtained values of the cellular neural network using support vector machine method.

Introduction The comprehensive geriatric assessment (CGA) in older patients with cancer is the gold standard to identify robust, frail or poor prognosis patients according Balducci classification. In Spain, a new proposal of a specific Geriatric Assessment in Hematology (GAH) scale has been designed and validated in patients with hematologic malignancies such as MDS/AML, multiple myeloma and CLL. The GAH scale has not been explored in patients with lymphoma. In this study, we have analyzed the utility of using the GAH scales in patients with hematologic malignancies, mostly lymphoma patients. Patients and methods. From March 2016 and September 2017, patients with hematologic malignancies were prospectively referred to the Geriatric Oncology clinic after a frailty screening test using G8 scale and with score <14 points. All patients were assessed with CIRS-G and GAH scales performed by the oncology nurses and a comprehensive geriatric assessment performed by the geriatrician. Results Of the 96 patients referred aged 70 years or over, 41 were males (42.7%) and 55 females (57.3%), the median age was 79 years (range, 70-89), and with the diagnosis of lymphoma in 53 patients (55.2%), multiple myeloma in 23 patients (24.0%), CLL in 13 patients (13.6%), MDS/AML in 5 patients (5.2%) and CML in 2 patients (2.0%). Seventy-five patients (78.1%) had good performance status with ECOG score 0-1. Regarding frailty, 20 patients (20.8%) had a score of 15 points or over at G8 scale and 76 patients (79.2%) were identified as frail because of a score of 14 points or below. Regarding comorbidities, the median CIRS-G score was 9 (range, 4-20). After the GAH scale assessment, the median number of domains affected in robust patients was 2 (1-4) and in frail patients was 4 (3-5) (p=0.0001). In the ROC curve, with an AUC of 0.7595 and a likelyhood ratio of 9, the cut-off in this series was 2 domains with impairment, with a sentivity of 13.79% and a specificity of 92.5% (p= 0.0003). Using a correlation factor for each domain, the mean score at GAH scale in robust patients was 26 points and in frail patients was 42.5 points (p=0.0038). In the ROC curve, with an area under the curve of 0.7026 and a likelihood ratio of 2.04, the cut-off value to identify robust vs frail patients was 33 points in the GAH scale, with a sensitivity of 77.5% and a specificity of 62.07% (p=0.0043). Analyzing the eight domains explored in the GAH scale, robust patients according CGA had less risk of polypharmacy of 31.25% vs 81.48% in frail patients (OR 0.1033, 95% CI 0.0472-0.2541) (p<0.0001), less gate speed/FAC impairment of 16.66% vs 81.48% (OR 0.04545, 95% CI 0.0183-0.1313) (p<0.0001), less ADL impairment 37.5% vs 85.19% (OR 0.1043, 95% CI 0.0398-0.2684) (p<0.0001), less mood impairment in 4.17% vs 40.74% in frail patients (OR 0.06324, 95% CI 0.01421-0.2498) (p<0.0001), less mental health impairments in 2.08% vs 22.22% in frail patients (OR 0.0744, 95% CI 0.0068-0.4531) (p=0.0023), less comorbidities in 2.08% vs 42.59% (OR 0.0286, 95% CI 0.0027-0.1817) (p<0.0001), less malnutrition in 10.42% vs 37.04% (OR 0.1977, 95% CI 0.0759-0.5495) (p=0.0024), and less poor self-reported well-being in 6.25% vs 66.67% (OR 0.0333, 95% CI 0.0101-0.1187) (p<0.0001). The median overall survival for patients with 3 or less domains impaired was not reached vs 90.77 months in those patients with 4-8 domains impaired (Log-rank test, p=0.0003), with HR (Log-rank) of 0.11 (95% CI, 0.04474-0.2846). Mean G8 score were similar between robust (11.68) and frail (11.04) patients (p=n.s.) among all patients with score below 14 points. Robust patients had less comorbidities according to CIRS-G scale, with a median of 9 vs 11 points (p=0.0001). There was correlation between CIRS-G and ECOG with G8 score, not found in previous studies. There is a correlation between the brief comorbidity assessment in the GAH scale with CIRS-G score. Among patients identified as not having comorbidities, the median CIRS-G score was 9 vs 13.5 among patients with comorbidities according the GAH scale (p<0.0001). Conclusions. The GAH scale is a valid tool for patients with hematologic malignancies, including patients with lymphoma, in order to classify patients according frailty phenotype. All domains explored in GAH scale were impaired with higher frequency in frail patients. Robust patients had less comorbidities and better performance status. The brief comorbidities assessment in the GAH scale correlates well with the CIRS-G. Figure. Figure. Disclosures: No relevant conflicts of interest to declare.

Background: On March 14, 2020, a state of alarm was declared in Spain due to the spread of SARS-CoV-2. Beyond this date, COVID-19 in the country changed the practice of oncologic care. Objective: Since recurrent hospital visits were a potential risk factor for contagion, the aim of this prospective observational study was to analyze the consequences of the COVID-19 pandemic in the health care of patients with lymphoma. Methods: All data were obtained from the electronic medical record. Variables such as age, sex, reason of the visit, use of the patient portal, changes in management, enrollment in clinical trials, and COVID-19 infection were recorded. Results: In all, 290 patients visited the lymphoma clinic, totaling 437 appointments. The median age was 66 (range 18-94) years, and 157 (54.1%) patients were male. Of them, 214 (73.8%) patients had only 1 visit to the clinic. Only 23 (7.9%) patients did not have access to the patient portal. Amid the COVID-19 pandemic, 78 (26.9%) patients remained in active treatment, 35 (12.1%) experienced delays in their treatments, and 6 (2.1%) experienced treatment discontinuation. During the follow-up, only 7 (2.4%) patients had a COVID-19 infection (6 cases with confirmed polymerase chain reaction test and 1 case with clinical suspicion). Despite the implementation of telemedicine strategies to avoid visits to the hospital, 66 (22.8%) patients had in-person visits at the lymphoma clinic. Patients who attended in-person consultations were younger than those who preferred telemedicine consultations (62 vs 66 years; P=.10) and had less use of the patient portal (17/224, 7.6% vs 6/66, 9%; P=.10), although these differences did not reach statistical significance. Patients who attended in-person visits were more likely to have had only 1 visit to the hospital (29/66, 43.9% vs 185/224, 82.6%; P<.001). Regarding the reason of in-person consultations, more patients were on active treatment in comparison to those using telemedicine resources (37/66, 56.1% vs 42/224, 18.3%; P<.001). Patients with a preference for telemedicine strategies had more surveillance visits (147/224, 65.6% vs 24/66, 36.4%; P<.001). Regarding treatment modifications, more treatment delays (29/224, 12.9% vs 6/66, 9.1%; P=.10) and more definite treatment discontinuations (6/224, 2.7% vs 0/66, 0%; P=.10) were seen in patients using telemedicine resources when compared to patients attending in-person visits, although these differences did not reach statistical significance. Regarding the type of therapy, patients attending in-person visits were more likely to receive an intravenous treatment rather than those using telemedicine (23/66, 62.2% vs 17/224, 40.5%; P<.001). Conclusions: Telemedicine such as patient portals are feasible strategies in the management of patients with lymphoma during the COVID-19 pandemic, with a reduction of in-person visits to the hospital and a very low contagion rate.

Background: Heart failure (HF) with preserved ejection fraction (HFpEF) and monoclonal gammopathy of uncertain significance (MGUS) are two entities that share pathophysiological mechanisms. The aim herein, was to assess the prevalence of MGUS in patients with HFpEF and no left ventricular (LV) hypertrophy, as well as its association with a pre-specified clinical endpoint at 12 months. Methods: The present study prospectively enrolled 69 patients admitted with HF, with ejection fraction ≥ 50%, and LV wall thickness < 12 mm. All patients were screened for MGUS. Clinical events were determined over a 12 month follow-up. The pre-specified composite clinical endpoint was readmission for heart failure or death. Results: The prevalence of MGUS in this population was 13%. There were no differences in the incidence of the composite clinical endpoint between patients with and without MGUS. Multivariate analysis showed that treatment with angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) was associated with fewer clinical events (HR: 0.153, 95% CI: 0.037–0.622, p = 0.009) and indicated a trend to lower risk of readmission for HF and death. Beta-blockers were associated with lower rates of the composite clinical endpoint (HR: 0.192, 95% CI: 0.05–0.736, p = 0.016), readmission for HF (HR: 0.272, 95% CI: 0.087–0.851, p = 0.025) and indicated a trend to lower mortality. Moreover, potassium serum levels > 5 mEq/L were associated with higher rates of the composite endpoint (HR: 6.074, 95% CI: 1.6–22.65,p = 0.007). Conclusions: The prevalence of MGUS in patients with HFpEF without hypertrophy was 3-fold that of the general population. There was no significant correlation between clinical outcomes and the presence of MGUS. Beta-blockers and ACEIs/ARBs reduced the composite of mortality and readmissions for HF in HFpEF patients. Hyperpotassemia was related to worse prognosis. Background: Heart failure (HF) with preserved ejection fraction (HFpEF) and monoclonal gammopathy of uncertain significance (MGUS) are two entities that share pathophysiological mechanisms. The aim herein, was to assess the prevalence of MGUS in patients with HFpEF and no left ventricular (LV) hypertrophy, as well as its association with a pre-specified clinical endpoint at 12 months. Methods: The present study prospectively enrolled 69 patients admitted with HF, with ejection fraction ≥ 50%, and LV wall thickness < 12 mm. All patients were screened for MGUS. Clinical events were determined over a 12 month follow-up. The pre-specified composite clinical endpoint was readmission for heart failure or death. Results: The prevalence of MGUS in this population was 13%. There were no differences in the incidence of the composite clinical endpoint between patients with and without MGUS. Multivariate analysis showed that treatment with angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) was associated with fewer clinical events (HR: 0.153, 95% CI: 0.037–0.622, p = 0.009) and indicated a trend to lower risk of readmission for HF and death. Beta-blockers were associated with lower rates of the composite clinical endpoint (HR: 0.192, 95% CI: 0.05–0.736, p = 0.016), readmission for HF (HR: 0.272, 95% CI: 0.087–0.851, p = 0.025) and indicated a trend to lower mortality. Moreover, potassium serum levels > 5 mEq/L were associated with higher rates of the composite endpoint (HR: 6.074, 95% CI: 1.6–22.65,p = 0.007). Conclusions: The prevalence of MGUS in patients with HFpEF without hypertrophy was 3-fold that of the general population. There was no significant correlation between clinical outcomes and the presence of MGUS. Beta-blockers and ACEIs/ARBs reduced the composite of mortality and readmissions for HF in HFpEF patients. Hyperpotassemia was related to worse prognosis.