Clinical machine withdrawal prediction system and method

A prediction system, dynamic monitoring technology, applied in computer-aided medical procedures, ventilators, patient-specific data, etc., can solve problems such as lack of unified guidance and lack of weaning prediction analysis

Pending Publication Date: 2022-02-11
THE SECOND AFFILIATED HOSPITAL OF ANHUI MEDICAL UNIV
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Problems solved by technology

However, the selection of weaning parameters and the timing of weaning are relatively random in clinical practice. There is no...

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  • Clinical machine withdrawal prediction system and method
  • Clinical machine withdrawal prediction system and method
  • Clinical machine withdrawal prediction system and method

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Embodiment Construction

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0055] Mechanical ventilation is a ventilation method that uses mechanical devices to replace, control or change spontaneous breathing movements. Mechanical ventilation is a very important means of treatment in clinical treatment. For example, with the help of a ventilator, it can maintain the patient's airway, improve ventilation and oxygenation, and prevent the body from hypoxia and carbon dioxide accumulation. Overcome the respiratory failure caused by basic dis...

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Abstract

The invention discloses a clinical machine withdrawal prediction system. The system at least comprises a clinical dynamic monitoring module, a symptom index acquisition module, an index data calculation module and a display module, wherein the clinical dynamic monitoring module is used for obtaining the dynamic index data of a clinical patient; the symptom index acquisition module is connected to the clinical dynamic monitoring module, and the symptom index acquisition module acquires symptom expression index data according to clinical symptoms and patient data in a global medical database; the index data calculation module is connected to the symptom index acquisition module, and the index data calculation module constructs an optimal analysis model according to the symptom expression index data; and the display module is connected to the index data calculation module and the clinical dynamic monitoring module, and the display module establishes a treatment dependence graph according to the optimal analysis model to guide machine withdrawal. According to the invention, a clinician can be helped to carry out precise machine withdrawal prediction on a sepsis patient.

Description

technical field [0001] The invention belongs to the field of medical equipment control, in particular to a clinical weaning prediction system and a method thereof. Background technique [0002] Sepsis is an organ dysfunction syndrome caused by the body's dysregulated response to inflammation. It is a class of patients with rapid disease changes and high mortality. Existing studies have proved that the lungs of patients are very susceptible, and too long or too short mechanical ventilation is not good for the prognosis of sepsis patients. Therefore, in sepsis patients undergoing invasive ventilation, choosing the right time to wean is extremely important for the prognosis of sepsis patients. However, the selection of weaning parameters and the timing of weaning are relatively arbitrary in clinical practice, and there is no unified guidance similar to guidelines, and there is also a lack of corresponding weaning prediction analysis as a guiding opinion. Contents of the inv...

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Application Information

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IPC IPC(8): G16H50/30G16H50/20G16H10/60G06F30/27A61M16/00G06F111/10
CPCG16H50/30G16H50/20A61M16/026G16H10/60G06F30/27G06F2111/10
Inventor 杨旻刘万军刘瑜张金肖文艳许耀华华天凤李惠
Owner THE SECOND AFFILIATED HOSPITAL OF ANHUI MEDICAL UNIV
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