Fundus topographical distribution patterns of ocular toxoplasmosis

BACKGROUND: To establish topographic maps and determine fundus distribution patterns of ocular toxoplasmosis (OT) lesions. METHODS: In this retrospective study, patients who presented with OT to ophthalmology clinics from four countries (Argentina, Turkey, UK, USA) were included. Size, shape and location of primary (1°)/recurrent (2°) and active/inactive lesions were converted into a two-dimensional retinal chart by a retinal drawing software. A final contour map of the merged image charts was then created using a custom Matlab programme. Descriptive analyses were performed. RESULTS: 984 lesions in 514 eyes of 464 subjects (53% women) were included. Mean area of all 1° and 2° lesions was 5.96±12.26 and 5.21±12.77 mm2, respectively. For the subset group lesions (eyes with both 1° and 2° lesions), 1° lesions were significantly larger than 2° lesions (5.52±6.04 mm2 vs 4.09±8.90 mm2, p=0.038). Mean distances from foveola to 1° and 2° lesion centres were 6336±4267 and 5763±3491 µm, respectively. The majority of lesions were found in temporal quadrant (p<0.001). Maximum overlap of all lesions was at 278 µm inferotemporal to foveola. CONCLUSION: The 1° lesions were larger than 2° lesions. The 2° lesions were not significantly closer to fovea than 1° lesions. Temporal quadrant and macular region were found to be densely affected underlining the vision threatening nature of the disease

New and conventional strategies for lung recruitment in acute respiratory distress syndrome

Mechanical ventilation is a supportive and life saving therapy in patients with acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). Despite advances in critical care, mortality remains high. During the last decade, the fact that mechanical ventilation can produce morphologic and physiologic alterations in the lungs has been recognized. In this context, the use of low tidal volumes (VT) and limited inspiratory plateau pressure (Pplat) has been proposed when mechanically ventilating the lungs of patients with ALI/ARDS, to prevent lung as well as distal organ injury. However, the reduction in VT may result in alveolar derecruitment, cyclic opening and closing of atelectatic alveoli and distal small airways leading to ventilator-induced lung injury (VILI) if inadequate low positive end-expiratory pressure (PEEP) is applied. On the other hand, high PEEP levels may be associated with excessive lung parenchyma stress and strain and negative hemodynamic effects, resulting in systemic organ injury. Therefore, lung recruitment maneuvers have been proposed and used to open up collapsed lung, while PEEP counteracts alveolar derecruitment due to low VT ventilatio

Timing and Modality of Kidney Replacement Therapy in Children and Adolescents

Introduction: The choice and timing of kidney replacement therapy (KRT) is influenced by clinical factors, laboratory features, feasibility issues, family preferences, and clinicians' attitudes. We analyzed the factors associated with KRT modality and timing in a multicenter, multinational prospective pediatric cohort study. Methods: A total of 695 pediatric patients with chronic kidney disease (CKD) enrolled into the Cardiovascular Comorbidity in Children with CKD (4C) study at age 6 to 17 years with estimated glomerular filtration rate (eGFR) of 10 to 60 ml/min per 1.73 m(2) were investigated. Competing risk regression was performed to identify factors associated with initiation of dialysis or preemptive transplantation (Tx), including primary renal diagnosis, demographics, anthropometrics, and laboratory parameters. Results: During the 8-year observation period, 342 patients (49%) started KRT. Of these, 200 patients started dialysis, whereas 142 patients underwent preemptive Tx. A lower eGFR at enrolment (Hazard ratio [HR]: 0.76 [95% confidence interval: 0.74-0.78]), a steeper eGFR slope (HR: 0.90 [0.85-0.95], and a higher systolic blood pressure SD score (SDS) (HR: 2.07 [1.49-2.87]) increased the likelihood of KRT initiation. Patients with glomerulopathies were more likely to start dialysis than children with congenital anomalies of the kidneys and urinary tracts (CAKUT) (HR: 3.81 [2.52-5.76]). Lower body mass index (BMI) SDS (HR: 0.73 [0.6-0.89]) and lower hemoglobin (HR: 0.8 [0.72-0.9]) were associated with higher likelihood of dialysis. A significant center effect was observed, accounting for 6.8% (dialysis) to 8.7% (preemptive Tx) of explained variation. Conclusion: The timing and choice of KRT in pediatric patients is influenced by the rate of kidney function loss, the underlying kidney disease, nutritional status, blood pressure, anemia and center-specific factors

Renal amyloidosis in children

Renal amyloidosis is a detrimental disease caused by the deposition of amyloid fibrils. A child with renal amyloidosis may present with proteinuria or nephrotic syndrome. Chronic renal failure may follow. Amyloid fibrils may deposit in other organs as well. The diagnosis is through the typical appearance on histopathology. Although chronic infections and chronic inflammatory diseases used to be the causes of secondary amyloidosis in children, the most frequent cause is now autoinflammatory diseases. Among this group of diseases, the most frequent one throughout the world is familial Mediterranean fever (FMF). FMF is typically characterized by attacks of clinical inflammation in the form of fever and serositis and high acute-phase reactants. Persisting inflammation in inadequately treated disease is associated with the development of secondary amyloidosis. The main treatment is colchicine. A number of other monogenic autoinflammatory diseases have also been identified. Among them cryopyrin-associated periodic syndrome (CAPS) is outstanding with its clinical features and the predilection to develop secondary amyloidosis in untreated cases. The treatment of secondary amyloidosis mainly depends on the treatment of the disease. However, a number of new treatments for amyloid per se are in the pipeline

Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validation

Background Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid–base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters. Methods We performed our analysis on VENTILA dataset, an observational, prospective, international, multi-centre study, performed to investigate the effect of baseline characteristics and management changes over time on the all-cause mortality rate in mechanically ventilated patients in ICU. Our cohort includes 12,596 adult patients older than 18, associated with 12,755 distinct admissions in ICUs across 37 countries and receiving invasive and non-invasive mechanical ventilation. We carry out four different analysis. Initially we select typical mechanical ventilation parameters and evaluate the machine learning model on both, the overall cohort and a subgroup of patients admitted with respiratory disorders. Furthermore, we carry out sensitivity analysis to evaluate whether inclusion of variables related to the function of other organs, improve the predictive performance of the model for both the overall cohort as well as the subgroup of patients with respiratory disorders. Results Predictive performance of RNN-based model was higher with Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.72 (± 0.01) and Average Precision (AP) of 0.57 (± 0.01) in comparison to RF and LR for the overall patient dataset. Higher predictive performance was recorded in the subgroup of patients admitted with respiratory disorders with AUC of 0.75 (± 0.02) and AP of 0.65 (± 0.03). Inclusion of function of other organs further improved the performance to AUC of 0.79 (± 0.01) and AP 0.68 (± 0.02) for the overall patient dataset and AUC of 0.79 (± 0.01) and AP 0.72 (± 0.02) for the subgroup with respiratory disorders. Conclusion The RNN-based model demonstrated better performance than RF and LR in patients in mechanical ventilation and its subgroup admitted with respiratory disorders. Clinical studies are needed to evaluate whether it impacts decision-making and patient outcomes