Earliest signs and management of leakage after bariatric surgeries: Single institute experience

Background: The aim of this study was to describe the clinical presentation and outcomes of treatment in patients who develop gastrointestinal leaks after different bariatric surgeries.Methods: Retrospective review of 632 consecutive bariatric surgical procedures performed from 1999–2009 in Alexandria University Hospital, Egypt.Results: Leakage occurred in 10 patients. Symptoms and signs included tachycardia, fever, tachypnea, left shoulder pain, abdominal pain, chest pain, and/or change in the nature of the drain effluent. The earliest signs of presentation were tachycardia and unilateral decrease in air entry in all patients. The average time to diagnosis was 3.9± 2.6 days. In four patients contrast study was negative (40%). Six leaks occurred after laparoscopic sleeve gastrectomy (6.3%), 2 after laparoscopic gastric bypass (3.6%), one after open gastric bypass (2.3%), and 1 after laparoscopic vertical banded gastroplasty (2.4%). The most common leak location was at the esophagogastric junction (70%). Four patients (40%) required reoperations. A percutaneous abdominal drainage was placed in five patients (50%). In 2 patients (20%), the prophylactic drain was maintained in situ till cessation of leakage. Two patients (20%) died. Mean hospital length of stay was 13.9 ± 7.8 days.Conclusions: Tachycardia and unequal breath sound in the early postoperative course are worrisome signs that warrant laparoscopic exploration even if contrast studies were negative. Patients with signs of sepsis or hemodynamic instability require emergent exploration. Leaks that are more insidious may be treated successfully with percutaneous drainage or maintenance of prophylactic drains.Keywords: Morbid obesity; Bariatric surgery; Complication; Lea

Resilience intervention for families of autistic children : reviewing the literature

: Given the rising diagnostic rates of autism, it is imperative to investigate the well-being of families with autistic children. Families of autistic children report more mental health difficulties than families of typically developing children. Resilience is identified as a key protective factor for mental health difficulties in many populations, and research suggests that this construct is effective for coping with mental health difficulties in families of autistic children. However, reviews on resilience interventions for families of autistic children are lacking. Accordingly, this paper aims to report (a) common mental health difficulties that families of autistic children experience, (b) how resilience may reduce mental health difficulties, (c) interventions to enhance resilience in families of autistic children, and (d) discuss implications for practice and future research. Our review identified that mental distress resulting from feelings of uncertainty and helplessness following a diagnosis, in addition to caregiving stressors, is especially common among families of autistic children. Enhancing resilience is suggested to reduce those difficulties by tapping into strengths related to various positive psychological resources such as internal locus of control, positive cognitive appraisal, acceptance and self-efficacy. Interventions such as Dance Movement Psychotherapy and spirituality-based approaches, are deemed especially helpful to families of autistic children. However, research in this area is still underdeveloped, and there is a pressing need to build a more rigorous evidence base. Findings reviewed in the current work can aid families of autistic children, healthcare practitioners, and researchers to support the mental wellbeing of families of autistic children, which in turn would support the wellbeing of autistic children

Leukocyte classification for acute lymphoblastic leukemia timely diagnosis by interpretable artificial neural network

Leukemia is a blood cancer characterized by leukocyte overproduction. Clinically, the reference for acute lymphoblastic leukemia diagnosis is a blood biopsy that allows obtain microscopic images of leukocytes, whose early-stage classification into leukemic (LEU) and healthy (HEA) may be disease predictor. Thus, the aim of this study is to propose an interpretable artificial neural network (ANN) for leukocyte classification to timely diagnose acute lymphoblastic leukemia. The “ALL_IDB2” dataset was used. It contains 260 microscopic images showing leukocytes acquired from 130 LEU and 130 HEA subjects. Each microscopic image shows a single leukocyte that was characterized by 8 morphological and 4 statistical features. An ANN was developed to distinguish microscopic images acquired from LEU and HEA subjects, considering 12 features as inputs and the local-interpretable model-agnostic explanatory (LIME) algorithm as an interpretable post-processing algorithm. The ANN was evaluated by the leave-one-out cross-validation procedure. The performance of our ANN is promising, presenting a testing area under the curve of the receiver operating characteristic equal to 87%. Being implemented using standard features and having LIME as a post-processing algorithm, it is clinically interpretable. Therefore, our ANN seems to be a reliable instrument for leukocyte classification to timely diagnose acute lymphoblastic leukemia, guaranteeing a high clinical interpretability level

MRI in cystic pancreatic lesions, is it of value?

Introduction: Cystic pancreatic lesions are currently discovered at higher rate, hence adequate characterization of these lesions by the radiologist is important in guiding management. Aim of the work: Was to identify the role of MRI in characterization of cystic pancreatic lesions. Patients and methods: Thirty patients with suspected cystic lesions of the pancreas were examined by MRI using 1.5 T machines including conventional MRI sequences, dynamic contrast enhanced imaging, DWI and IP/OP sequence. Results: The study included 30 patients (12 males and 18 females) with their age ranging from 16 to 88 years (mean age 55 years), MRI analysis of the cyst contents and communication with ductal system were used to characterize different cyst types, among these patients we found serous cystadenoma in five patients, mucinous cystadenoma in seven patients, mucinous cystadenocarcinoma in one patient, branch type Intraductal papillary mucinous neoplasms (IPMN) in seven patients, Mixed IPMN in two patients. Cystic neuroendocrine tumors (CNET) in three patients. Solid cystic pancreatic neoplasm (SPN) in two patients. Pseudocyst in one patient and walled off necrosis (WON) in two patients. Pathological assessment of the lesions was done whenever indicated. Conclusions: MRI with its superior soft tissue resolution is of value in characterization of different cystic pancreatic lesions helping to reach the correct diagnosis