Enteral tubes, tube tip detection systems, and methods for detecting tube misplacement are provided. For example, a tube tip detection system comprises an enteral tube having a tip and a first light disposed at the tip that is illuminated as the enteral tube is inserted into a patient to indicate to a user of the system whether the tip is misplaced in the patient's airway. Similarly, enteral tubes are provided that comprise a tip, a length, and a light that is continuously illuminated as the enteral tube is inserted into a patient. Methods for detecting a tube misplacement in a patient's airway include embedding a light into an enteral tube, inserting the enteral tube into the patient through the patient's nose or mouth, and monitoring a location of the light as the enteral tube is inserted into the patient to determine if the tube is traveling into the patient's airway.

There is provided a method comprising: computing a target nutritional goal to reach at an end of a time interval based on a real time energy expenditure of a patient, wherein the target nutritional goal comprises a volume to be delivered (VTBD) by the end of the time interval corresponding to a target amount of energy expenditure of the patient over the time interval, computing a target feeding profile defining a target feeding rate for enteral feeding of the patient for reaching the VTBD by the end of the time interval, continuously monitoring the real time energy expenditure, adapting the target nutritional goal and corresponding VTBD to compute a maximum VTBD to reach at the end of the time interval according to the monitoring, and dynamically adapting the target feeding rate and the corresponding target feeding profile for a remaining portion of the time interval for reaching the maximum VTBD.

Embodiments relate to guiding medical care based on detected gastric function. For example, gastric acid stimulant or suppressant is administered, and then a change in the gastric juice H+ concentration is measured. This change is compared to a guidance H+ concentration differential indicative of relatively healthy gastric function. Medical care is guided based on a relatively healthy gastric function if the measured H+ concentration differential is equal to or exceeds the guidance H+ concentration differential, while medical care is guided based on a relatively unhealthy gastric function if the measured H+ concentration differential is less than the guidance H+ concentration differential. Disclosed embodiments implementing this procedure include, but are not limited to, methods, apparatus, processors, computer programs, and computer-readable mediums.

The use of a device to measure patient sensory response through the application of an incrementally increased electrical current to the oropharynx.

An automatic breastfeeding method of a premature infant is disclosed, which includes a preparation stage, an active lactation stage, a passive lactation stage and a rest stage. The invention also provides an automatic breastfeeding machine used for the automatic breastfeeding method of a premature infant, comprising a stomach tube, a lactation supply device, a detector and a control device. According to the invention, a self-sucking ability of the premature infant is trained, normal circulation of a mouth-pharyngeal-gastric-intestinal reflex of the premature infant is realized, and nutritional requirements of the premature infant are ensured in the case of taking differences of the premature infants into account, so that the premature infants have no difference with term infants in care, diet, neurological development and growth and development in the future.

A computer-implemented method of adjusting enteral feeding of a patient by an enteral feeding controller, comprising: computing an estimate of energy expenditure of the patient based on oxygen measurements and carbon dioxide measurements of the patient, computing a target composition and target feeding rate for the enteral feeding according to the computed estimate of energy expenditure, when the target composition and target feeding rate differ from a current enteral feeding composition and feeding rate by a requirement, generating instructions for adjustment, by an enteral feeding controller, of the rate of delivery of the enteral feeding according to the target composition, wherein the receiving the oxygen measurement, receiving the carbon dioxide measurement, and computing the estimate of energy expenditure are performing iteratively for every first time interval, and the generating instructions for adjustment are performed for a second time interval that is larger than the first time interval.

Embodiments relate to guiding medical care based on detected gastric function. For example, gastric acid stimulant or suppressant is administered, and then a change in the gastric juice H+ concentration is measured. This change is compared to a guidance H+ concentration differential indicative of relatively healthy gastric function. Medical care is guided based on a relatively healthy gastric function if the measured H+ concentration differential is equal to or exceeds the guidance H+ concentration differential, while medical care is guided based on a relatively unhealthy gastric function if the measured H+ concentration differential is less than the guidance H+ concentration differential. Disclosed embodiments implementing this procedure include, but are not limited to, methods, apparatus, processors, computer programs, and computer-readable mediums.

A computer-implemented method of treating a patient's and automated enteral feeding, comprising: monitoring a plurality of reflux-related parameters and at least one reflux event while the patient is automatically enterally fed by an enteral feeding controller according to a baseline feeding profile including a target nutritional goal, training a classifier component of a model for predicting likelihood of a future reflux event according to an input of scheduled and/or predicted plurality of reflux-related parameters, the classifier trained according to computed correlations between the plurality of reflux-related parameters and the at least one reflux event, feeding scheduled and/or predicted reflux-related parameters into the trained classifier component of the model for outputting risk of likelihood of a future reflux event, and computing, by the model, an adjustment to the baseline feeding profile for reducing likelihood of the future reflux event and for meeting the target nutritional goal.

There is provided a system for managing reflux during an enteral feeding, comprising: (i) a non-transitory memory having stored thereon a code for execution by at least one hardware processor of a computing device, the code comprising: code for receiving electrical signals outputted by at least one reflux event sensor disposed within a digestive system of a patient; code for determining a gastric reflux event based on an analysis of the electrical signals; code for outputting instructions to pause enteral feeding of the patient by a feeding controller that regulates enteral feeding of the patient using an enteral feeding tube positioned within the digestive system of the patient; and (ii) an evacuation controller that directs back-flow of digestive contents from the digestive system of the patient to an external evacuation reservoir through an evacuation tube.

A system for monitoring a patient's nutrition administration, the system including a processing device and a memory storing instructions executable by the processing device for: accessing nutrition administration information for a plurality of patients describing nutrition administered by different forms to the plurality of patients; accessing medical information about the plurality of patients from a healthcare information system; accessing nutritional requirement data describing a nutritional requirement for the plurality of patients; determining a difference between a nutritional requirement for a patient of the plurality of patients based on the nutritional requirement data, an amount of a nutrient administered to the patient, and the nutrition administration information; and integrating the nutrition administration information for the patient, the medical information for the patient, and the nutritional requirement data for the patient, for determining a nutritional adjustment for administering the amount of the nutrient to the patient based on the difference.