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CN-122006039-A - High-frequency ventilation method and system for preventing lung injury

CN122006039ACN 122006039 ACN122006039 ACN 122006039ACN-122006039-A

Abstract

The invention relates to the technical field of high-frequency ventilation methods, in particular to a high-frequency ventilation method and a system for preventing lung injury, comprising the steps of obtaining historical control parameters of a high-frequency breathing machine during anesthesia in a preset time period; the method comprises the steps of obtaining real-time ventilation information, carrying out correlation evaluation on standardized historical control parameters and the real-time ventilation information, accumulating real-time ventilation data in a time dimension, comparing the real-time ventilation data with the ventilation total quantity requirement in a preset anesthesia period, determining standard-reaching grades based on comparison difference, generating a first control strategy, a second control strategy and a third control strategy according to the standard-reaching grades, optimizing control parameters of a high-frequency breathing machine, and carrying out real-time driving control on the high-frequency breathing machine based on optimized control parameter groups. The invention solves the problems of volume injury, air pressure injury and other risks in the prior art, dynamically optimizes amplitude, frequency, average airway pressure and inhaled oxygen concentration in the whole anesthesia process, and ensures that the total lung stretching amount is always kept within a safe range.

Inventors

  • YUAN XIAOHONG

Assignees

  • 浙江省肿瘤医院

Dates

Publication Date
20260512
Application Date
20260323

Claims (9)

  1. 1. A method of high frequency ventilation for preventing lung injury comprising the steps of: S1, acquiring historical control parameters of a high-frequency breathing machine during anesthesia in a preset time period, and preprocessing the historical control parameters to obtain standardized historical control parameters; S2, acquiring real-time ventilation information, and performing correlation evaluation on the standardized historical control parameters and the real-time ventilation information to obtain a correlation evaluation result; s3, accumulating the real-time ventilation data in a time dimension to obtain accumulated ventilation, comparing the accumulated ventilation with the ventilation total quantity requirement in a preset anesthesia period to obtain comparison difference, and determining a standard grade based on the comparison difference; S4, generating a first control strategy, a second control strategy and a third control strategy according to the standard grade, and optimizing control parameters of the high-frequency breathing machine based on the first control strategy, the second control strategy, the third control strategy and a correlation evaluation result; and S5, performing real-time driving control on the high-frequency breathing machine based on the optimized control parameter set.
  2. 2. The method for high-frequency ventilation for preventing lung injury according to claim 1, wherein in S1, obtaining a history control parameter of the high-frequency ventilator during anesthesia within a preset time period, and preprocessing the history control parameter to obtain a standardized history control parameter comprises: the history control parameters comprise respiratory rate, tidal volume set value, oscillation pressure amplitude, respiratory rate and oxygen concentration set value; Acquiring the breathing frequency, the tidal volume set value, the oscillation pressure amplitude, the breathing ratio and the oxygen concentration set value of the high-frequency breathing machine during anesthesia; And sequentially carrying out data cleaning on the respiratory frequency, the tidal volume set value, the oscillation pressure amplitude, the respiratory ratio and the oxygen concentration set value, removing abnormal values and null values, carrying out data conversion to obtain characteristic vectors of each control parameter, and carrying out data integration on the characteristic vectors of each control parameter to obtain the standardized historical control parameter.
  3. 3. The method for high-frequency ventilation for preventing lung injury according to claim 2, wherein in S2, acquiring real-time ventilation information, performing a correlation evaluation on the normalized historical control parameter and the real-time ventilation information, and obtaining a correlation evaluation result includes: S21, continuously collecting the real-time ventilation of the high-frequency breathing machine according to a fixed sampling period, and performing linear interpolation and low-pass filtering on missing or abnormal values to generate a real-time ventilation smooth sequence; S22, extracting the same sampling period sequence corresponding to the current anesthesia stage from the standardized historical control parameter matrix, and constructing a historical control parameter time alignment matrix; S23, performing hysteresis correlation analysis on the time alignment matrix of the historical control parameters and the real-time ventilation smooth sequence, and comparing and analyzing a hysteresis correlation analysis result with a preset correlation threshold value to obtain a correlation evaluation result.
  4. 4. A method of high frequency ventilation for the prevention of lung injury according to claim 3, wherein in S2, the expression for performing a hysteresis correlation analysis comprises: ; Wherein, the For a real-time ventilation smoothing sequence, 、 、 、 、 、 Respectively a regression intercept, a breathing frequency coefficient, a tidal volume set value coefficient, an oscillation pressure amplitude coefficient, a breathing ratio coefficient and an oxygen concentration set value coefficient, As a characteristic of the hysteresis of the breathing frequency, For the tidal volume set point hysteresis feature, To be a characteristic of the amplitude hysteresis of the oscillating pressure, As a characteristic of the hysteresis of the breathing ratio, To be a hysteresis feature of the oxygen concentration set point, T is the time corresponding to the sampling point at the fixed time for the optimal lag time; smoothing sequence of real-time ventilation And model predictive value And (3) performing difference calculation, wherein the expression is as follows: ; Wherein, the In order to normalize the instantaneous error, Smoothing sequences for real-time ventilation Is a sample standard deviation of (2); Calculating a hysteresis correlation analysis result The expression is: ; Wherein, the Is a permissible deviation threshold.
  5. 5. The method of claim 4, wherein in S3, accumulating the real-time ventilation data in a time dimension to obtain an accumulated ventilation comprises: ; Wherein, the For the instantaneous ventilation of the ith sample point, In order to accumulate the ventilation quantity, For the sampling period, k is the total number of sampling points.
  6. 6. The method of claim 5, wherein in S3, comparing the total ventilation requirement with a preset total ventilation requirement during anesthesia to obtain a comparison difference, and determining the standard grade based on the comparison difference comprises: calculating and comparing the accumulated ventilation with the preset ventilation total amount during anesthesia, wherein the expression is as follows: ; Wherein, the For the comparison of the difference amounts, A ventilation total amount requirement for a preset anesthesia period; The method comprises the steps of generating a threshold curve graph comprising two threshold curves based on a clinical allowable error ratio, determining the comparison difference below a first threshold curve of the threshold curve graph as a first standard-reaching level, determining the comparison difference above the first threshold curve of the threshold curve and below a second threshold curve as a second standard-reaching level, and determining the comparison difference above the second threshold curve of the threshold curve as a third standard-reaching level.
  7. 7. The method of claim 6, wherein generating the first control strategy, the second control strategy, and the third control strategy according to the compliance level in S4 comprises: and respectively generating a first control strategy, a second control strategy and a third control strategy according to the first standard grade, the second standard grade and the third standard grade.
  8. 8. The method according to claim 7, wherein in S4, the first control strategy includes not adjusting parameters, and keeping the respiratory rate, the tidal volume set value, the oscillation pressure amplitude, the respiratory rate, the oxygen concentration set value at the previous period value, so as to accelerate the acquisition rate of the real-time ventilation information; the second control strategy comprises the steps of adjusting respiratory frequency, a tidal volume set value and an oscillation pressure amplitude according to a configured importance index, and accelerating the acquisition rate of real-time ventilation volume information; the third control strategy comprises the steps of adjusting the breathing frequency, the tidal volume set value, the oscillation pressure amplitude, the breathing ratio and the oxygen concentration set value according to the configured importance index, and accelerating the acquisition rate of the real-time ventilation information.
  9. 9. A high frequency ventilation system for preventing lung injury, comprising: The acquisition module is used for acquiring the history control parameters of the high-frequency breathing machine during anesthesia within a preset time period, and preprocessing the history control parameters to obtain standardized history control parameters; The evaluation module is used for acquiring the real-time ventilation information, and performing correlation evaluation on the standardized historical control parameters and the real-time ventilation information to obtain a correlation evaluation result; The comparison module is used for accumulating the real-time ventilation data in the time dimension to obtain accumulated ventilation, comparing the accumulated ventilation with the ventilation total quantity requirement in the preset anesthesia period to obtain comparison difference, and determining the standard grade based on the comparison difference; The optimizing module is used for generating a first control strategy, a second control strategy and a third control strategy according to the standard grade, and optimizing control parameters of the high-frequency breathing machine based on the first control strategy, the second control strategy, the third control strategy and the correlation evaluation result; and the control module is used for carrying out real-time driving control on the high-frequency breathing machine based on the optimized control parameter set.

Description

High-frequency ventilation method and system for preventing lung injury Technical Field The invention relates to the technical field of high-frequency ventilation methods, in particular to a high-frequency ventilation method and a high-frequency ventilation system for preventing lung injury. Background High Frequency Ventilation (HFV), which is an important device for maintaining oxygenation and carbon dioxide scavenging during anesthesia, has been used in difficult airways, single lung ventilation, etc. settings by virtue of its high frequency, small tidal volume, which can accomplish oxygenation and carbon dioxide scavenging during anesthesia at lower airway pressures. The device realizes gas exchange under lower airway pressure, can reduce volume injury and air pressure injury theoretically, and is widely used in anesthesia scenes such as difficult airway, single lung ventilation, thoracic surgery and the like. However, the existing open loop preset, experience compensation or single point instant feedback mode can only passively correct the instantaneous physiological index, so that the optimal parameter-ventilation mapping rule cannot be extracted by utilizing the historical big data, and a dynamic comparison mechanism of accumulated ventilation and preoperative total ventilation targets is lacking, so that the total lung stretching amount is difficult to be limited by a system in the continuous long-time anesthesia process, and the risks of volume injury, air pressure injury and the like still exist. Disclosure of Invention The invention aims to provide a high-frequency ventilation method and a high-frequency ventilation system for preventing lung injury, which solve the problems of volume injury, air pressure injury and other risks in the prior art, dynamically optimize amplitude, frequency, average airway pressure and inhaled oxygen concentration in the whole anesthesia process, and ensure that the total lung stretching amount is always kept within a safe range. To achieve the above object, the present invention provides a high-frequency ventilation method for preventing lung injury, comprising the steps of: S1, acquiring historical control parameters of a high-frequency breathing machine during anesthesia in a preset time period, and preprocessing the historical control parameters to obtain standardized historical control parameters; S2, acquiring real-time ventilation information, and performing correlation evaluation on the standardized historical control parameters and the real-time ventilation information to obtain a correlation evaluation result; s3, accumulating the real-time ventilation data in a time dimension to obtain accumulated ventilation, comparing the accumulated ventilation with the ventilation total quantity requirement in a preset anesthesia period to obtain comparison difference, and determining a standard grade based on the comparison difference; S4, generating a first control strategy, a second control strategy and a third control strategy according to the standard grade, and optimizing control parameters of the high-frequency breathing machine based on the first control strategy, the second control strategy, the third control strategy and the correlation evaluation result; and S5, performing real-time driving control on the high-frequency breathing machine based on the optimized control parameter set. In some embodiments of the present application, in S1, obtaining a history control parameter of the high-frequency ventilator during anesthesia within a preset time period, and preprocessing the history control parameter to obtain a standardized history control parameter includes: The historical control parameters comprise respiratory rate, tidal volume set value, oscillation pressure amplitude, respiratory rate and oxygen concentration set value; Acquiring the breathing frequency, the tidal volume set value, the oscillation pressure amplitude, the breathing ratio and the oxygen concentration set value of the high-frequency breathing machine during anesthesia; And sequentially carrying out data cleaning on the respiratory frequency, the tidal volume set value, the oscillation pressure amplitude, the respiratory ratio and the oxygen concentration set value, removing abnormal values and null values, carrying out data conversion to obtain characteristic vectors of each control parameter, and carrying out data integration on the characteristic vectors of each control parameter to obtain the standardized historical control parameter. In some embodiments of the present application, in S2, acquiring the real-time ventilation information, performing a correlation evaluation on the standardized historical control parameter and the real-time ventilation information, and obtaining a correlation evaluation result includes: S21, continuously collecting the real-time ventilation of the high-frequency breathing machine according to a fixed sampling period, and performing linear interpolation an