Variables associated with antibiotic administration for performing paracentesis among patients with ascites in a community hospital.

Aim of the study: Early paracentesis before antibiotic administration reduces morbidity and mortality in patients with decompensated cirrhosis. We studied the association of variables with antibiotic administration before or after performing paracentesis. Material and methods: This was a retrospective study of 137 patients with ascites secondary to cirrhosis admitted to a community hospital in New York City. Predictor variables were demographic, disease-related, admission timing, and serum measurement. Results: We found a significantly increased relative risk for performing paracentesis after antibiotic administration for those admitted at night (relative risk ratio [RRR] = 3.01, 95% CI: 1.02-8.85, p = 0.046). Demographic, disease-related, and serum measurement variables were not significantly associated with performing paracentesis or order of antibiotic administration. Also, increased body mass index was significantly associated with decreased relative risk for paracentesis not done (RRR = 0.84, 95% CI: 0.74-0.96, p = 0.01). Conclusions: In conclusion, there was increased relative risk for performing paracentesis after antibiotic administration for patients admitted at night. We recommend ongoing resident and hospitalist training to maintain competency in bedside procedures such as paracentesis for patients with cirrhosis. Also, increased staffing or the presence of a resident/hospitalist led interventional team during night shifts may also help optimize the rates of timely paracentesis.

Modelling and robust controller design for an underactuated self-balancing robot with uncertain parameter estimation.

A comprehensive literature review of self-balancing robot (SBR) provides an insight to the strengths and limitations of the available control techniques for different applications. Most of the researchers have not included the payload and its variations in their investigations. To address this problem comprehensively, it was realized that a rigorous mathematical model of the SBR will help to design an effective control for the targeted system. A robust control for a two-wheeled SBR with unknown payload parameters is considered in these investigations. Although, its mechanical design has the advantage of additional maneuverability, however, the robot's stability is affected by changes in the rider's mass and height, which affect the robot's center of gravity (COG). Conventionally, variations in these parameters impact the performance of the controller that are designed with the assumption to operate under nominal values of the rider's mass and height. The proposed solution includes an extended Kalman filter (EKF) based sliding mode controller (SMC) with an extensive mathematical model describing the dynamics of the robot itself and the payload. The rider's mass and height are estimated using EKF and this information is used to improve the control of SBR. Significance of the proposed method is demonstrated by comparing simulation results with the conventional SMC under different scenarios as well as with other techniques in literature. The proposed method shows zero steady state error and no overshoot. Performance of the conventional SMC is improved with controller parameter estimation. Moreover, the stability issue in the reaching phase of the controller is also solved with the availability of parameter estimates. The proposed method is suitable for a wide range of indoor applications with no disturbance. This investigation provides a comprehensive comparison of available techniques to contextualize the proposed method within the scope of self-balancing robots for indoor applications.

Unscented Kalman filter for airship model uncertainties and wind disturbance estimation.

An airship is lighter than an air vehicle with enormous potential in applications such as communication, aerial inspection, border surveillance, and precision agriculture. An airship model is made up of dynamic, aerodynamic, aerostatic, and propulsive forces. However, the computation of aerodynamic forces remained a challenge. In addition to aerodynamic model deficiencies, airship mass matrix suffers from parameter variations. Moreover, due to the lighter-than-air nature, it is also susceptible to wind disturbances. These modeling issues are the key challenges in developing an efficient autonomous flight controller for an airship. This article proposes a unified estimation method for airship states, model uncertainties, and wind disturbance estimation using Unscented Kalman Filter (UKF). The proposed method is based on a lumped model uncertainty vector that unifies model uncertainties and wind disturbances in a single vector. The airship model is extended by incorporating six auxiliary state variables into the lumped model uncertainty vector. The performance of the proposed methodology is evaluated using a nonlinear simulation model of a custom-developed UETT airship and is validated by conducting a kind of error analysis. For comparative studies, EKF estimator is also developed. The results show the performance superiority of the proposed estimator over EKF; however, the proposed estimator is a bit expensive on computational grounds. However, as per the requirements of the current application, the proposed estimator can be a preferred choice.

An Automated System for Classification of Chronic Obstructive Pulmonary Disease and Pneumonia Patients Using Lung Sound Analysis.

Chronic obstructive pulmonary disease (COPD) and pneumonia are two of the few fatal lung diseases which share common adventitious lung sounds. Diagnosing the disease from lung sound analysis to design a noninvasive technique for telemedicine is a challenging task. A novel framework is presented to perform a diagnosis of COPD and Pneumonia via application of the signal processing and machine learning approach. This model will help the pulmonologist to accurately detect disease A and B. COPD, normal and pneumonia lung sound (LS) data from the ICBHI respiratory database is used in this research. The performance analysis is evidence of the improved performance of the quadratic discriminate classifier with an accuracy of 99.70% on selected fused features after experimentation. The fusion of time domain, cepstral, and spectral features are employed. Feature selection for fusion is performed through the back-elimination method whereas empirical mode decomposition (EMD) and discrete wavelet transform (DWT)-based techniques are used to denoise and segment the pulmonic signal. Class imbalance is catered with the implementation of the adaptive synthetic (ADASYN) sampling technique.

Hepatic Cyst: An Unusual Suspect of Syncope.

The patient is a 75-year-old man with history of diabetes and hypertension who presented with syncope after experiencing sharp, 10/10 right flank and abdominal pain worsening over three weeks associated with decreased appetite. Physical examination revealed hepatomegaly and right lower quadrant (RUQ) tenderness, negative for peritoneal signs. Bloodwork showed leukocytosis (13 K/mcl), alkaline phosphatase (141 U/L), total bilirubin (2.0 mg/dL), and gamma-glutamyl transferase (172 U/L). Computed Tomography (CT) revealed multiple hepatic cysts with the largest measuring 17 × 14 × 18 cm (Figure 1). Parenteral opiates provided minimal relief. Cardiac and neurologic etiologies of syncope were ruled out. The patient's course was complicated by opioid-induced delirium as his abdominal pain progressively worsened despite escalating doses of parenteral and oral analgesics. Gastroenterology and interventional radiology consulted to evaluate for Glisson's capsular stretch. Therapeutic aspiration yielded 2.5 L of serous fluid, which alleviated the patient's pain. Cytology was negative for malignancy. Opiates were titrated down. Repeat CT (Figure 2) showed cysts that were significantly reduced in size. The patient showed complete resolution of symptoms and was subsequently discharged. We present a rare case of a large hepatic cyst causing syncope. In the appropriate clinical setting, syncope with RUQ tenderness and hepatomegaly should raise the index of suspicion for hepatic cysts.