Automated diagnosis of flatfoot using cascaded convolutional neural network for angle measurements in weight-bearing lateral radiographs.

Objectives: Diagnosis of flatfoot using a radiograph is subject to intra- and inter-observer variabilities. Here, we developed a cascade convolutional neural network (CNN)-based deep learning model (DLM) for an automated angle measurement for flatfoot diagnosis using landmark detection.

Methods: We used 1200 weight-bearing lateral foot radiographs from young adult Korean males for the model development.

Automated landmark identification for diagnosis of the deformity using a cascade convolutional neural network (FlatNet) on weight-bearing lateral radiographs of the foot.

Landmark detection in flatfoot radiographs is crucial in analyzing foot deformity. Here, we evaluated the accuracy and efficiency of the automated identification of flatfoot landmarks using a newly developed cascade convolutional neural network (CNN) algorithm, Flatfoot Landmarks AnnoTating Network (FlatNet). A total of 1200 consecutive weight-bearing lateral radiographs of the foot were acquired.

The effects of backward, upward, rightward pressure maneuver for intubation using the OptiscopeTM: a retrospective study.

Background: The OptiscopeTM and the backward, upward, rightward pressure (BURP) maneuver are widely used in clinical practice because the BURP maneuver facilitates intubation by improving visualization of the larynx. However, the effect of the BURP maneuver is unclear when using the OptiscopeTM. Therefore, we retrospectively investigated the effect of the BURP maneuver on intubation using the OptiscopeTM.

Treatment of rocuronium-induced anaphylaxis using sugammadex - A case report.

Background: Perioperative anaphylaxis is a life-threatening clinical condition characterized by severe respiratory and cardiovascular manifestations. Neuromuscular blocking agents are the most common cause of anaphylaxis during anesthesia.

Case: We report a case of rocuronium-induced anaphylaxis treated with sugammadex.

Comparison of five glomerular filtration rate estimating equations as predictors of acute kidney injury after cardiovascular surgery.

We aimed to compare the ability of preoperative estimated glomerular filtration rate (eGFR), calculated using five different equations, to predict adverse renal outcomes after cardiovascular surgery. Cohorts of 4,125 adult patients undergoing elective cardiovascular surgery were evaluated. Preoperative eGFR was calculated using the Cockcroft-Gault, Modification of Diet in Renal Disease (MDRD) II, re-expressed MDRD II, Chronic Kidney Disease Epidemiology Collaboration, and Mayo quadratic (Mayo) equations.

The relationship of preoperative estimated glomerular filtration rate and outcomes after cardiovascular surgery in patients with normal serum creatinine: a retrospective cohort study.

Background: Although serum creatinine concentration has been traditionally used as an index of renal function in clinical practice, it is considered relatively inaccurate, especially in patients with mild renal dysfunction. This study investigated the usefulness of preoperative estimated glomerular filtration rate (eGFR) in predicting complications after cardiovascular surgery in patients with normal serum creatinine concentrations.

Methods: This study included 2208 adults undergoing elective cardiovascular surgery.