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Find 3,347 clinical trials for rheumatoid arthritis near Philadelphia, Pennsylvania. Connect with research centers in your area.
Showing 441-460 of 3,347 trials
NCT05642455
This is a pediatric basket study to investigate the safety and efficacy of afamitresgene autoleucel in HLA-A\*02 eligible and MAGE-A4 positive subjects aged 2-17 years of age with advanced cancers.
NCT04026737
This is an observational study aiming to prospectively define the rate of occurrence, natural history and progression of cardiac dysfunction in adults, and to identify the patients at high risk of developing cardiovascular events. The study enrolls patients prior to infusion with CART cell therapy and follows them with serial echocardiography, cardiac biomarkers, clinical data, and quality of life questionnaire.
NCT07217197
This study is being conducted to evaluate the ability of the Respiratory Monitoring System (RMS) to detect and predict opioid induced respiratory depression (OIRD) in post-operative surgical patients managed with opioid medications. The ability of the RMS to detect OIRD will be compared to the detection of OIRD using a commercial capnometer, pulse oximeter, airflow monitor, and breathing volume monitor . We hypothesize the RMS will detect the onset and progression of a true OIRD event with high sensitivity, specificity, positive predictive value, and negative predictive value. A true OIRD event will be determined by the reference device trend data. RTM Vital Signs, LLC is developing a Respiratory Monitoring System (RMS) that consists of a wearable Trachea Sound Sensor (TSS) and a software application that measures the sounds of air flow within the trachea during inhalation and exhalation and cardiovascular sounds. The sounds of airflow in the trachea are used to continuously monitor a patient's respiratory rate (RR), relative tidal volume (TV), relative minute ventilation (MV), pattern of breathing, duration of apnea in a healthcare setting. The cardiovascular sounds are used to continuously monitor pulse rate and PR variability. Once commercialized, clinicians will observe the RMS trend data on a smart phone, bedside display, or electronic medical record to determine whether the patient is breathing within their normal range, breathing more than their normal range (hyperventilation), breathing less than their normal range (hypoventilation), or not breathing (apnea). Real-time alerts and alarms will be based upon trends in a patient's rate and depth of breathing, number and duration of apnea events, RTM's Risk-Index-Score, and RTM's machine learning/artificial intelligence methods.