A method for heart failure management may include volume overload intervention in response to sensor-based parameters indicating volume overload. The method may include administering non-volume overload intervention in response to the sensor-based parameters not indicating volume overload. Volume overload may be determined based on monitoring sensor-based parameters. Sensor-based parameters may be monitored in response to receiving an alert indicative of a worsening heart failure score or status for a patient.

Described is an apparatus for inline urine analysis comprising a control unit and at least one image capture unit comprising an image sensor and an optical assembly. The apparatus is configured to be coupled with an indwelling urinary catheter or conduit leading from the catheter. Embodiments of the apparatus comprise a dispenser configured to dispense inert or reactive matter into the urine stream to aid in the analysis of properties of the urine and an illumination device configured to illuminate the urine stream. Also described is a system comprising at least one of these apparatuses and at least one image analyzer unit operatively connected to it. The image analyzer unit comprises a processor and software adapted to analyze the captured images to derive information therefrom relating to identification of properties of the urine and/or objects of interest in the urine stream. Embodiments of the system may comprise other peripheral devices.

The present disclosure provides catheter systems, electrode assemblies, and methods for electrically stimulating one or more points about the circumference of the renal artery to provide real time intraprocedural operational feedback to the operator of a renal denervation procedure to allow for more precise and thorough ablation of the renal artery and better patient outcomes. In many embodiments, an electrode assembly is provided that includes multiple splines that extend from an insulated proximal hub to an insulated distal hub and are interconnected to an electrical wire to allow the splines to independently function as electrical stimulation electrodes. The electrically active splines can then be energized at one or more desired points during a renal denervation procedure to provide operational feedback.

A medical monitoring device for monitoring electrical signals from the body of a subject is described. The medical monitoring device monitors electrical signals originating from a cardiac cycle of the subject and associates each cardiac cycle with a time index. The medical monitoring device applies a forward computational procedure to generate a risk score indicative of hyperkalemia, hypokalemia or arrhythmia of the subject. The medical monitoring device can adjust the forward computational procedure based upon clinical data obtained from the subject.

Systems, devices, and methods for delivering laser energy to a target in an endoscopic procedure are disclosed. An exemplary method comprises providing a first laser pulse train and a different second laser pulse train emitting from a distal end of an endoscope and incident on a target. The first laser pulse train has a first laser energy level, and the second laser pulse train has a second laser energy level higher than the first laser energy level. In an example, the first laser pulse train is used to form cracks on a surface of a calculi structure, and the second laser pulse train causes fragmentation of the calculi structure after the cracks are formed.

Methods, systems, devices, assemblies and apparatuses for treatment of hypertension in a patient using renal denervation. The therapeutic assembly includes an energy delivery element. The energy delivery element is configured to provide renal denervation energy to a nerve within a blood vessel of a patient. The therapeutic assembly includes a controller. The controller is coupled to the energy delivery element. The controller is configured to determine that the hypertension in the patient is orthostatic. The controller is configured to apply renal denervation energy to the patient using the energy delivery element.

An end stage renal disease (ESRD) monitoring system may include an implantable sensor and a reader device with an optical sensor. The implantable sensor may be configured to detect a group of analytes relevant to ESRD, such as glucose, creatinine, urea, and potassium. The implantable sensor may be implanted into the dermis of an animal, and may exhibit color changes in response to the presence of the target analytes or reaction product(s) thereof. The reader device may be configured to capture an image of the implanted sensor and to determine the concentration of the target analytes based at least in part on the image. The reader device may be a personal electronic device such as a cell phone, PDA, or personal computer.

Provided herein are methods, devices and compositions for assessing neuromodulation efficacy based on changes in the level of one or more biomarkers in plasma or urine collected from a human subject following a renal neuromodulation procedure.

Embodiments herein include systems and methods for detecting, predicting and/or assessing acute kidney injury. In an embodiment, a monitoring system to detect acute kidney injury is included. The monitoring system can include a sensor circuit configured to collect renal data including at least one of systemic renal data, direct renal data, urinary tract data, and renal-relevant extracorporeal data. The monitoring system can also include a memory circuit to store collected renal data, an evaluation circuit to assess renal status, and a telemetry circuit. The evaluation circuit can determine whether acute kidney injury has occurred or is likely to occur by comparing the renal data to at least one of threshold values, personal historical values, patient population values and patterns indicative of acute kidney injury. The evaluation circuit can initiate a warning notification if acute kidney injury has occurred or is likely to occur. Other embodiments are also included herein.

Example devices, systems, and techniques predict renal denervation efficacy for reducing hypertension in a patient based on pulse information. For example, a system may include processing circuitry configured to obtain pulse information representative of pulses from both wrists of a patient, obtain a plurality of values representative of respective patient metrics for the patient, and apply the pulse information and the plurality of values to a deep learning model trained to represent a relationship of the pulse information and the patient metrics to an efficacy of renal denervation in reducing hypertension. In some examples, responsive to applying the pulse information and the plurality of values to the deep learning model, the processing circuitry obtains, from the deep learning model, a score indicative of renal denervation efficacy in reducing hypertension for the patient, and generates a graphical user interface comprising a graphical representation of the score for the patient.