A method of protecting alveolar epithelial cells from oxidative damage by hyperinflation with isocarbic acid

Abstract

This invention proposes a method for isocarbonyl hyperventilation to protect alveolar epithelial cells from oxidative damage. It belongs to the field of medical respiratory therapy technology. The method includes: providing patients requiring respiratory support with a minute ventilation volume higher than physiologically required, while simultaneously supplementing the inhaled air with exogenous carbon dioxide using a gas mixing device; continuously monitoring the patient's end-tidal carbon dioxide partial pressure, the concentration of 8-isoprostaglandin in exhaled condensate, and pH value, among other oxidative stress biomarkers, using monitoring equipment; and precisely regulating gas composition and ventilation parameters through isocarbonyl hyperventilation to create a suitable microenvironment for alveolar epithelial cells, effectively neutralizing excessive intracellular oxidative substances, reducing direct damage to cells from oxidative stress, and decreasing adverse effects such as cell membrane lipid peroxidation and protein denaturation, thereby significantly improving the survival rate and normal function maintenance capacity of alveolar epithelial cells.

Description

Technical Field

[0001] This invention proposes a method for isocarbonic hyperventilation to protect alveolar epithelial cells from oxidative damage, belonging to the field of medical respiratory therapy technology. Background Technology

[0002] High-concentration oxygen therapy is a commonly used life support method in clinical practice, widely applied in the treatment of patients with respiratory failure and hypoxemia. However, prolonged exposure to high concentrations of oxygen (oxygen volume fraction > 950 ml / L) can lead to severe oxygen toxicity, causing oxidative stress-induced lung injury. In a hyperoxic environment, alveolar cells produce excessive reactive oxygen species (ROS), exceeding the scavenging capacity of the intracellular antioxidant system, resulting in an imbalance between the oxidative and antioxidant systems. This imbalance can trigger diffuse alveolitis and alveolar structural damage, leading to acute lung injury (ALI) or acute respiratory distress syndrome (ARDS) in adults, and bronchopulmonary dysplasia (BPD) in premature infants.

[0003] Type II alveolar epithelial cells (AECII) are key cells for lung tissue repair and regeneration, and are highly susceptible to oxidative damage under hyperoxia exposure. Studies have shown that hyperoxia can promote the over-differentiation of AECII cells into AECII-type cells and lead to a significant increase in apoptosis, thereby increasing the risk of alveolar structural damage and pulmonary fibrosis. Furthermore, hyperoxia also inhibits the protective effects of various growth factors (such as keratinocyte growth factor KGF), causing AECII cells to lose their repair capabilities.

[0004] Currently, clinical strategies for the prevention and treatment of hyperoxia-induced lung injury are limited, mainly including:

[0005] Antioxidant applications (such as alpha-lipoic acid, hydrogen);

[0006] Cytokine therapy (such as KGF);

[0007] Stem cells and related products (such as exosomes derived from mesenchymal stem cells);

[0008] However, these methods have significant limitations: traditional antioxidants may interfere with normal lung development while reducing hyperoxia damage; stem cell therapy carries potential tumorigenicity and embolism risks; and simply reducing oxygen concentration may not guarantee the tissue's oxygenation needs.

[0009] Isocapnic hyperventilation (IH) is a technique that maintains normal arterial carbon dioxide partial pressure (PaCO2) by supplementing exogenous CO2 while increasing ventilation volume. Originally used to accelerate the clearance of inhaled anesthetics and promote postoperative recovery, recent studies have found its application value in emergency treatment of gas poisoning and ventilator weaning. The core principle of IH is to precisely control the CO2 concentration in the inhaled air, increasing oxygen exchange while maintaining normal carbon dioxide levels. This improves blood oxygen concentration while avoiding adverse reactions such as cerebral vasoconstriction and respiratory depression caused by hypocapnia.

[0010] While IH technology has shown potential applications, its current focus is primarily on anesthetic gas clearance and ventilation improvement, and it has not yet been systematically applied to alveolar cell protection. Existing IH devices are mostly modified ventilators or built by researchers themselves, resulting in issues such as inaccurate gas mixing, insufficient safety monitoring, and a lack of standardization, limiting their application in the prevention and treatment of hyperoxia-induced lung injury. Furthermore, while existing patents (such as CN114768014B) involve CO2 supplementation and ventilation control, their core objective is to maintain macroscopic physiological homeostasis, without addressing microscopic cellular-level protection against oxidative damage to alveolar epithelial cells, nor have they incorporated oxidative stress biomarkers as core regulatory parameters. Summary of the Invention

[0011] This invention provides a method for protecting alveolar epithelial cells from oxidative damage during isocarbonic hyperventilation, thereby addressing the problems mentioned in the background section.

[0012] This invention proposes a method for protecting alveolar epithelial cells from oxidative damage through isocarbonate hyperventilation, the method comprising:

[0013] S1. Provide ventilation support to patients who require respiratory support, wherein the minute ventilation of the ventilation support is higher than the patient's physiological needs, and while providing the ventilation support, supplement the patient's inhaled air with exogenous carbon dioxide through a gas mixing device.

[0014] S2. Continuously monitor the patient's end-tidal carbon dioxide partial pressure (PetCO2) and at least one oxidative stress biomarker using monitoring equipment;

[0015] S3. Based on the monitored values ​​of PetCO2 and the oxidative stress biomarkers, the system dynamically adjusts the supplemental flow rate of exogenous CO2 and / or ventilation parameters through an integrated control system to maintain the patient's arterial blood carbon dioxide partial pressure within a preset target range. The target range is dynamically adjusted according to the level of oxidative stress: when the level of oxidative stress increases (e.g., the concentration of 8-isoprostaglandin in exhaled condensate is higher than 20 pg / ml), the system automatically increases the target PaCO2 to 45-50 mmHg to enhance the lung protective effect; when the level of oxidative stress decreases or is in the recovery period (e.g., the concentration of 8-isoprostaglandin is lower than 15 pg / ml), the system automatically decreases the target PaCO2 to 35-45 mmHg to avoid the side effect of hypercapnia.

[0016] S4. Based on the monitored blood oxygen saturation values, dynamically reduce FiO2 to the minimum effective level required to maintain the target SpO2, and optimize ventilation-perfusion matching.

[0017] This invention proposes an isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage. The system is used to implement any of the methods described above, and the system comprises:

[0018] The gas supply module includes independent oxygen, air, and carbon dioxide sources;

[0019] A gas mixing module, connected to the gas supply module, is used to fully mix oxygen, air and carbon dioxide from the gas supply module to form an inhalation gas with a specific concentration;

[0020] A gas delivery module, connected to the gas mixing module, includes a mechanical ventilator capable of providing high tidal volume and high respiratory rate ventilation for delivering the mixed inhaled gas to the patient;

[0021] The monitoring module is used to monitor the patient's physiological parameters in real time, including at least an end-tidal carbon dioxide sensor, a blood oxygen saturation sensor, and an analysis unit for detecting oxidative stress biomarkers in exhaled condensate;

[0022] The control feedback module, which is communicatively connected to the monitoring module, the gas supply module, the gas mixing module, and the gas delivery module, is configured as follows:

[0023] Receive real-time data from the monitoring module;

[0024] Based on the real-time data, the required exogenous CO2 supplementation flow rate and / or the required ventilator parameter adjustment values ​​are calculated through the built-in control algorithm;

[0025] Instructions are sent to the gas supply module and / or the gas delivery module to execute the above-calculated adjustments, thereby maintaining the patient's PaCO2 within the target range.

[0026] The beneficial effects of this invention are as follows: By establishing oxidative stress biomarkers (such as 8-isoprostaglandin concentration and pH value) as core regulatory variables and dynamically coupling them with the target PaCO2 range, a paradigm shift from macroscopic gas management to microscopic cell monitoring is achieved; through isocarbonic hyperventilation, precise regulation of gas composition and ventilation parameters creates a suitable microenvironment for alveolar epithelial cells, effectively neutralizing excessive intracellular oxidative substances, reducing the direct damage of oxidative stress to cells, and reducing adverse conditions such as cell membrane lipid peroxidation and protein denaturation, thereby significantly improving the survival rate and normal function maintenance capacity of alveolar epithelial cells; by using 8-isoprostaglandin concentration as a core regulatory parameter and setting specific concentration thresholds (20 pg / ml and 15 pg / ml) to trigger PaCO2 target range adjustment, the oxidative damage of alveoli is effectively controlled. Early and precise intervention: Experimental data shows that after applying the method of this invention, the survival rate of alveolar epithelial cells increased by 25-30%, and the concentration of 8-isoprostaglandin decreased by ≥35%. Real-time monitoring and dynamic adjustment of ventilation strategies can quickly respond to changes in the cell environment, promptly capture early signs of oxidative damage and intervene, avoid further expansion and deterioration of damage, reduce the proportion of cell apoptosis and necrosis caused by oxidative damage, and buy valuable time for the self-repair and regeneration of alveolar epithelial cells. By comparing the oxidative damage indicators of alveolar epithelial cells before and after implementing this method, the protective effect can be clearly assessed, and the ventilation program can be optimized according to individual differences, avoiding the limitations that may be caused by a single ventilation mode, reducing the problem of residual cell damage caused by inappropriate protective measures, and improving the precision and effectiveness of the protection against oxidative damage to alveolar epithelial cells. Attached Figure Description

[0027] Figure 1 This is a diagram of the method described in this invention. Detailed Implementation

[0028] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0029] One embodiment of the present invention, such as Figure 1 As shown, a method for isocarbonic hyperventilation to protect alveolar epithelial cells from oxidative damage includes:

[0030] S1. Provide ventilation support to patients requiring respiratory support, wherein the minute ventilation of the ventilation support is higher than the patient's physiological needs in order to increase oxygen exchange efficiency; and while providing the ventilation support, supplement the patient's inhaled air with precisely controlled exogenous carbon dioxide (CO2) through a specially designed gas mixing device.

[0031] S2. Continuously monitor the patient's end-tidal carbon dioxide partial pressure (PetCO2) and at least one oxidative stress biomarker, such as the concentration and / or pH value of 8-iso-prostaglandin (8-iso-PGF2α) in exhaled condensate, using a monitoring device to achieve near real-time monitoring at 30-minute intervals via rapid electrochemical detection.

[0032] S3. Based on the monitored values ​​of PetCO2 and the oxidative stress biomarkers, the system dynamically adjusts the supplemental flow rate of exogenous CO2 and / or ventilation parameters (including tidal volume, respiratory rate, and inhaled oxygen concentration FiO2) through an integrated control system to precisely maintain the patient's arterial blood carbon dioxide partial pressure (PaCO2) within a preset target range. The target range is dynamically adjusted according to the level of oxidative stress: when the level of oxidative stress increases (e.g., the concentration of 8-isoprostaglandin in exhaled condensate is higher than 20 pg / ml), the system automatically increases the target PaCO2 to 45-50 mmHg to enhance the lung protective effect; when the level of oxidative stress decreases or is in the recovery period (e.g., the concentration of 8-isoprostaglandin is lower than 15 pg / ml), the system automatically decreases the target PaCO2 to 35-45 mmHg to avoid the side effect of hypercapnia.

[0033] S4. Based on the monitored value of blood oxygen saturation (SpO2), dynamically reduce FiO2 to the minimum effective level required to maintain the target SpO2, so as to reduce the generation of reactive oxygen free radicals; and optimize ventilation-perfusion matching to improve regional ventilation efficiency and reduce damage caused by alveolar overexpansion and collapsed circulation.

[0034] The working principle and effects of the above technical solution are as follows:

[0035] By precisely controlling the amount of exogenous CO2 supplementation and dynamically adjusting the PaCO2 target range based on the level of oxidative stress (increased to 45-50 mmHg to enhance protection when oxidative stress is elevated, and decreased to 35-45 mmHg to avoid side effects during the recovery period), apoptosis of alveolar epithelial cells caused by oxidative stress was reduced, avoiding the risk of insufficient protection or hypercapnia caused by PaCO2 fixation, and improving the stability of the alveolar microenvironment.

[0036] By reducing FiO2 to the minimum effective level to maintain target oxygenation based on SpO2 monitoring values, the reactive oxygen free radicals generated by high concentrations of oxygen are reduced, avoiding oxygen toxicity caused by long-term high oxygen exposure (such as ALI / ARDS in adults and BPD in premature infants), reducing the probability of alveolar structure damage, and enhancing the protective effect against oxidative damage to alveolar cells.

[0037] By monitoring ventilation-perfusion matching indices (V / Q, dead space ventilation rate) and optimizing parameters accordingly (such as increasing PEEP when ventilation is insufficient and adjusting tidal volume / respiratory rate when ventilation is excessive), circulatory damage from alveolar overexpansion and collapse is reduced, regional ventilation inefficiency caused by ventilation-perfusion imbalance is avoided, and the overall effectiveness of lung ventilation is improved.

[0038] The integrated control system automatically adjusts CO2 flow and ventilation parameters, and sets differentiated targets (such as oxygenation range and tidal volume) for adults and premature infants, reducing errors and workload of manual adjustments by medical staff, avoiding the compatibility issues of a one-size-fits-all treatment, and enhancing the individualization and convenience of treatment plans.

[0039] In one embodiment of the present invention, S1 includes:

[0040] S11. Conduct a comprehensive assessment of patients requiring respiratory support, including weight, age (e.g., preterm infants / adults), type of underlying lung disease (e.g., risk of acute respiratory distress syndrome (ARDS) / bronchopulmonary dysplasia (BPD), current oxygenation status (initial SpO2 value), and respiratory mechanics parameters (airway resistance, lung compliance). Based on the assessment results, calculate a baseline minute ventilation value higher than physiological needs (usually 10-15 L / min for adults, and 8-12 ml / kg × respiratory rate for preterm infants based on weight) and an initial exogenous CO2 supplementation flow rate (calculated using the formula: FlowCO2(ml / min) = 0.3 × weight (kg) × baseline minute ventilation value (L / min)) using the built-in individualized algorithm of the integrated control system, and generate an individualized initial parameter table for the patient.

[0041] S12. Based on the generated individualized initial parameter table for the patient, select the appropriate ventilation interface (tracheal intubation is preferred for adults, and nasal continuous positive airway pressure is preferred for premature infants); connect the intelligent ventilator in the gas delivery module, start the isocarbonate hyperventilation (IH) mode of the ventilator, and set the parameters (tidal volume (adults 8-12ml / kg, premature infants 8-10ml / kg), respiratory rate (adults 16-25 breaths / min, premature infants 20-30 breaths / min)) to the baseline values ​​calculated in S11, complete the establishment of the artificial ventilation pathway, ensure that the ventilation support meets the core requirements higher than the physiological needs, and initially improve the oxygen exchange efficiency;

[0042] S13. Based on the established ventilation path, activate the specially designed vortex mixing chamber gas mixing device. This device receives medical-grade oxygen (from the hospital's central oxygen supply system or high-pressure oxygen cylinder) and medical-grade CO2 (from a dedicated CO2 cylinder) supplied by the gas supply module. The airflow is guided by guide vanes within the chamber to form a high-speed vortex, and then dispersed by a buffer flow equalization network to achieve molecular-level uniform mixing of O2 and CO2. Simultaneously, O2 and CO2 concentration sensors at the device outlet collect real-time concentration data of the premixed gas, generating a real-time premixed gas concentration record table to ensure that the mixed gas concentration fluctuation error is <0.1%.

[0043] S14. Based on the generated real-time record table of premixed gas concentration, if the CO2 concentration in the mixed gas meets the concentration corresponding to the initial supplemental flow rate calculated in S11 (usually 1.5%-2.0%), the premixed gas is delivered to the patient's ventilation interface through the inhalation circuit of the gas delivery module; if the concentration deviates, the CO2 input flow rate is adjusted through the mass flow controller (MFC) in the gas supply module until the concentration reaches the target before delivery is started, thus realizing the initial system construction of high ventilation support + precise exogenous CO2 supplementation.

[0044] The working principle and effects of the above technical solution are as follows:

[0045] By comprehensively assessing indicators such as patient weight, age, and underlying lung disease, the individualized algorithm of the integrated control system calculates ventilation volume and initial CO2 flow rate, generating a parameter table, which improves the adaptability of initial treatment parameters and reduces the risk of under-ventilation or over-ventilation caused by inappropriate parameters.

[0046] Select the appropriate ventilation interface (endotracheal intubation for adults, nasal ventilation for premature infants) according to the parameter table, start the IH mode to set the baseline value, improve the fit of the ventilation route, reduce complications caused by interface discomfort in different groups (such as nasal mucosal damage in premature infants), ensure that ventilation meets the requirements higher than physiological needs, and initially improve oxygen exchange efficiency.

[0047] By using a vortex mixing chamber, guide vanes, and buffer flow equalization net to mix the gas and monitor the concentration in real time, the uniformity of O2 and CO2 mixing is improved, the concentration fluctuation error is <0.1%, the problem of local oxygen concentration being too high or CO2 being insufficient caused by uneven gas mixing is reduced, and the stability of gas delivery is enhanced.

[0048] By adjusting the CO2 flow rate to the target level according to the concentration table before delivery, the risk of PaCO2 runaway caused by CO2 concentration deviation was reduced. This successfully established an initial system of high ventilation support + precise CO2 supplementation, providing a reliable foundation for subsequent alveolar protection and improving the reliability of the treatment initiation phase.

[0049] In one embodiment of the present invention, S2 includes:

[0050] S21. Through the constructed ventilation and CO2 supplementation system, various sensors of the monitoring module are deployed on the patient: the end-tidal carbon dioxide (PetCO2) sensor is connected to the expiratory limb of the ventilation circuit, the SpO2 sensor is clipped to the patient's fingertip / the sole of the premature infant's foot, the airway pressure sensor is integrated into the ventilator tubing, and an expiratory condensate collection device (such as a low-temperature condensate sampling tube) is placed at the end of the expiratory circuit; after the monitoring equipment is started, the PetCO2 sensor is calibrated using a standard calibration gas (a mixture of 5% CO2 and 21% O2), the SpO2 sensor is calibrated using a standard blood oxygen simulation signal, and a calibration qualification report of the monitoring equipment is generated;

[0051] S22. Based on the generated calibration report of the monitoring equipment, start the continuous sampling mode of the monitoring equipment: collect PetCO2, SpO2 and airway pressure data once every 1 second, and collect exhaled condensate samples once every 2 hours; send the collected exhaled condensate samples to the analysis unit, detect the concentration of 8-iso-prostaglandin (8-iso-PGF2α) by enzyme-linked immunosorbent assay, detect the pH value of the sample by precision pH meter, and generate a real-time monitoring data sequence list (including time-series data of PetCO2 / SpO2 / airway pressure) and an oxidative stress marker detection report (including 8-iso-prostaglandin concentration and pH value).

[0052] S23. Based on the generated real-time monitoring data sequence list and oxidative stress biomarker detection report, a sliding window filtering algorithm is used to remove abnormal fluctuations in PetCO2 and SpO2 data (such as a sudden drop in SpO2 caused by patient agitation). Data consistency verification is used to determine whether the exhaled condensate sample is contaminated (e.g., if the pH value exceeds the normal physiological range of 4.5-7.0, it is determined to be an invalid sample). The filtered data is marked for validity to generate a post-cleaning monitoring dataset.

[0053] S24. Based on the generated post-cleaning monitoring dataset, the PetCO2 value is correlated with the PaCO2 estimate (converted according to the formula PaCO2=PetCO2+2-5mmHg) through the damage risk assessment model built into the integrated control system. The concentration of 8-isoprostaglandin (normal reference value <10pg / ml), pH value (normal reference value 6.8-7.2) and alveolar oxidative damage level (mild damage: 8-iso-PGF2α 10-20pg / ml, moderate damage: 20-30pg / ml, severe damage: >30pg / ml) are correlated to generate a real-time alveolar damage risk assessment table.

[0054] The working principle and effects of the above technical solution are as follows:

[0055] By precisely deploying PetCO2, SpO2, airway pressure sensors, and condensate collection devices, and calibrating the PetCO2 sensor with standard gases (5% CO2, 21% O2) and the SpO2 sensor with standard blood oxygenation signals, a calibration report is generated, which improves the initial accuracy of monitoring data, reduces errors caused by uncalibrated sensors, and avoids the risk of using erroneous data to guide subsequent treatment.

[0056] Continuous sampling mode was activated (physiological parameters were collected every second and condensate was collected every 2 hours). 8-isoprostaglandin was measured by enzyme-linked immunosorbent assay and pH was measured by a precision pH meter. Time-series data tables and biomarker reports were generated, which improved the timeliness of data collection, reduced the problem of lag in the detection of oxidative stress biomarkers, and enhanced the ability to perceive early alveolar damage.

[0057] Sliding window filtering is used to remove abnormal fluctuations (such as a sudden drop in SpO2) and data consistency verification is used to determine sample contamination (such as pH exceeding 4.5-7.0), generating a clean dataset. This improves the cleanliness of the monitoring data, reduces interference from invalid data to the analysis, and avoids misjudgment of damage risk caused by data impurities.

[0058] By linking PetCO2 and PaCO2 (converted according to the formula), biomarkers and damage levels (e.g., 8-iso-PGF2α > 30 pg / ml indicates severe damage), a risk assessment table is generated. This improves the intuitiveness of damage risk assessment, reduces the difficulty for medical staff to interpret data, provides a clear basis for subsequent dynamic control, and enhances the pertinence of treatment decisions.

[0059] In one embodiment of the present invention, S3 includes:

[0060] S31. Based on the generated real-time alveolar injury risk assessment table, the control feedback module of the integrated control system receives data in real time and analyzes two core control requirements: first, whether PaCO2 deviates from the target range, which is 35-50 mmHg; second, whether the alveolar oxidative damage level changes (e.g., from mild to moderate). If PaCO2 is within the target range and the damage level does not increase, it is determined that no adjustment is needed. If either condition is not met, the parameter control process is triggered, and a control requirement trigger command is generated.

[0061] S32. Based on the generated regulatory demand trigger command, if an increase in alveolar oxidative damage level is detected (e.g., 8-isoprostaglandin concentration >20 pg / ml), the system automatically adjusts the PaCO2 target range upward to 45-50 mmHg to enhance the anti-inflammatory and anti-apoptotic protective effects of hypercapnia; if a decrease in oxidative damage level is detected (e.g., 8-isoprostaglandin concentration <15 pg / ml) or the patient is in the recovery period (e.g., the symptoms of the primary disease are relieved), the system automatically adjusts the PaCO2 target range downward to 35-45 mmHg to avoid side effects such as intracellular acidosis and pulmonary hypertension caused by long-term hypercapnia, and generates a dynamic target PaCO2 interval table;

[0062] S33. Based on the generated dynamic target PaCO2 interval table, a hybrid algorithm of PID controller + fuzzy logic is used to calculate the adjustment amount: The PID controller calculates the basic adjustment amount of CO2 supplementation flow rate based on the deviation (ΔPaCO2) between the current estimated PaCO2 value and the target value (e.g., when ΔPaCO2 = 5 mmHg, the CO2 flow rate increases by 0.2 ml / min / kg); the fuzzy logic combines airway pressure data (e.g., when plateau pressure > 30 cmH2O, the increase of tidal volume is limited) and SpO2 data (e.g., when SpO2 < 88%, oxygenation is prioritized) to correct the basic adjustment amount; finally, a parameter adjustment detail is generated, which includes the CO2 supplementation flow rate adjustment value and the tidal volume / respiratory rate adjustment value (if necessary).

[0063] S34. Perform parameter adjustments and verify the control effect. Based on the parameter adjustment details generated in S33, the control feedback module sends a CO2 flow adjustment command to the gas supply module (executed through the mass flow controller) and a ventilator parameter adjustment command (adjusting tidal volume or respiratory rate) to the gas delivery module. After adjustment, monitor continuously for 3-5 minutes, collect new PetCO2 and PaCO2 data, and verify whether PaCO2 falls within the dynamic target range set in S3.2. If it meets the target, a control qualification record is generated. If it does not meet the target, repeat S33-S34 until PaCO2 accurately meets the target, forming a closed-loop control of monitoring-calculation-adjustment-verification.

[0064] The working principle and effects of the above technical solution are as follows:

[0065] By analyzing whether PaCO2 deviates from the target range of 35-50 mmHg and whether the alveolar oxidative damage level changes, it is determined whether regulation is triggered, which improves the targeting of parameter adjustment, reduces unnecessary operations when no adjustment is needed, and avoids treatment fluctuations caused by frequent parameter changes.

[0066] The PaCO2 range is dynamically adjusted according to the damage level (adjusted to 45-50 mmHg for enhanced protection when it rises, and adjusted to 35-45 mmHg during the decline / recovery period), which enhances the adaptability of lung protection at different treatment stages and reduces the risk of side effects such as intracellular acidosis and pulmonary hypertension caused by long-term hypercapnia.

[0067] Using a PID controller to calculate the basic adjustment of CO2 flow rate, and then combining it with airway pressure (such as plateau pressure > 30 cmH2O limiting tidal volume) and SpO2 (such as < 88% prioritizing oxygenation) corrections, the accuracy of parameter adjustment is improved, the adjustment deviation caused by looking at only a single indicator is reduced, and alveolar damage is avoided due to improper parameters.

[0068] After adjustment, monitor for 3-5 minutes to verify whether PaCO2 meets the target. If it does not meet the target, repeat the calculation and adjustment to form a closed-loop control, which improves the stability of PaCO2 target achievement, reduces the problem of parameter runaway after adjustment, and provides a reliable blood gas basis for subsequent protection against alveolar epithelial cell oxidative damage.

[0069] In one embodiment of the present invention, step S4 includes:

[0070] S41. Based on the SpO2 time-series data in the generated post-cleaning monitoring dataset, set a safe oxygenation target range (92-95% for adults, 88-92% for preterm infants); through the FiO2 optimization algorithm of the integrated control system, deduce the minimum inhaled oxygen concentration (FiO2) required to maintain this range. For example, if SpO2 is consistently >95% (adults), the FiO2 target value is reduced by 5%; if SpO2 fluctuates between 88-90% (preterm infants), the FiO2 target value is maintained at the current level, generating a minimum effective FiO2 target table.

[0071] S42. Based on the generated minimum effective FiO2 target table, a gradual downward adjustment strategy is adopted to adjust FiO2: each downward adjustment is controlled at 2-5%, and continuous monitoring is performed for 15-20 minutes after the adjustment, collecting SpO2 and PaO2 data (obtained through blood gas analysis); if SpO2 remains within the safe target range and PaO2 > 60 mmHg (adults) / > 50 mmHg (premature infants), then the current FiO2 is determined to be the effective minimum value, and a qualified FiO2 downward adjustment record is generated; if SpO2 is lower than the target range, the downward adjustment is paused and FiO2 is restored to the previous effective level to avoid the risk of hypoxemia;

[0072] S43. Based on the constructed ventilation system, the ventilation-perfusion matching related indicators are continuously collected through the respiratory mechanics monitoring function built into the ventilator, including: regional ventilation distribution (obtained through electrical impedance tomography (EIT) to identify under-ventilated / over-ventilated areas), ventilation / perfusion ratio (V / Q, normal range 0.8-1.2), and dead space ventilation rate (VD / VT, normal <0.3). If V / Q <0.8 (indicating under-ventilation) or VD / VT >0.4 (indicating increased dead space) is detected, it is marked as a ventilation-perfusion imbalance area, and a ventilation-perfusion imbalance analysis report is generated.

[0073] S44. Based on the generated ventilation-perfusion imbalance analysis report, targeted optimization measures are taken for the imbalanced areas: If it is an underventilated area (such as the bottom of the lungs), the positive end-expiratory pressure (PEEP) is appropriately increased by 2-3 cmH2O to promote the re-expansion of collapsed alveoli; if it is an overventilated area (such as the upper part of the lungs), while maintaining the minute ventilation unchanged, the tidal volume is appropriately reduced (reduced by 1 ml / kg each time) and the respiratory rate is increased (increased by 2 breaths / min each time) to avoid excessive alveolar expansion; after optimization, the ventilation-perfusion indicators are monitored again until V / Q returns to the range of 0.8-1.2, and a ventilation-perfusion optimization report is generated to reduce the mechanical damage and oxidative stress superimposed effects caused by the alveolar expansion-collapse cycle;

[0074] S45. Based on the generated ventilation and blood flow optimization report, collect exhaled condensate samples every 4-6 hours to detect 8-isoprostaglandin concentration and pH value; compare the oxidative damage indicators before and after optimization. If the 8-isoprostaglandin concentration decreases by ≥20% and the pH value rises back to the range of 6.8-7.2, the optimization is deemed effective, and the current parameters are maintained; if the indicators do not improve, return to S43 to re-analyze the causes of ventilation and blood flow imbalance and adjust the optimization strategy.

[0075] The working principle and effects of the above technical solution are as follows:

[0076] Differentiated safe oxygenation ranges were set for adults and premature infants. The minimum effective concentration was derived from the FiO2 optimization algorithm to generate a target table, which improved the accuracy of FiO2 setting, reduced the use of high-concentration oxygen, and reduced the risk of reactive oxygen free radicals damaging alveolar epithelial cells.

[0077] A gradual downward adjustment strategy of 2-5% was adopted each time. After monitoring for 15-20 minutes, SpO2 and PaO2 were combined to determine whether the target was reached. If the target was not reached, the adjustment was reversed. This improved the safety of FiO2 adjustment, avoided the occurrence of hypoxemia, and reduced the treatment risks caused by oxygenation fluctuations.

[0078] By collecting indicators such as V / Q and dead space ventilation rate, and using EIT to identify ventilation imbalance areas and generate reports, the efficiency of identifying ventilation-perfusion imbalance is improved, and the problem of low regional ventilation efficiency due to undetected imbalance is reduced, providing a clear basis for targeted optimization.

[0079] Parameter adjustments were made to address imbalanced areas (increasing H2O and OPEEP by 2-3 cmH2 during underventilation and decreasing tidal volume and increasing respiratory rate during overventilation), allowing V / Q to return to 0.8-1.2, which enhanced the effectiveness of regional ventilation, reduced mechanical damage and oxidative stress from alveolar expansion and collapse circulation, and protected alveolar structure.

[0080] Oxidation indicators were measured every 4-6 hours to verify the effect. If the effect was not satisfactory, the strategy was re-analyzed and adjusted. This improved the adaptability of the optimization plan, reduced the situation of blindly maintaining ineffective parameters, and ensured the continuous and reliable alveolar protection effect.

[0081] In one embodiment of the present invention, S41 includes:

[0082] Continuous time-series data of blood oxygen saturation (SpO2) were selected from the post-cleaning monitoring dataset. Abnormal data points caused by patient limb movement or poor sensor contact (such as a single SpO2 surge / drop >5% and a duration <3 seconds) were removed using the 3σ principle. Stable data sequences that meet clinical monitoring standards were retained to generate a post-cleaning SpO2 time-series dataset.

[0083] Based on the basic patient information (adults / premature infants) associated with the purified SpO2 time-series dataset, and referring to the clinical lung protection guidelines, population-specific safe oxygenation target intervals were set: the target interval for adult patients was 92-95%, and the target interval for premature infants was 88-92%. The oxygenation safety boundaries for different populations were clarified, and a population-adaptive safe oxygenation target interval table was generated.

[0084] The purified SpO2 time-series dataset and the population-adapted safe oxygenation target interval table are input into the FiO2 optimization algorithm of the integrated control system. The algorithm uses the SpO2-FiO2 dynamic correlation model to deduce the following: if the adult SpO2 is consistently >95% (continuous monitoring ≥5 minutes), the theoretical value of reducing FiO2 by 5% is calculated; if the premature infant's SpO2 fluctuates between 88-90% (continuous monitoring ≥10 minutes), the theoretical value of maintaining the current FiO2 is calculated, and an initial FiO2 adjustment suggestion form is generated.

[0085] Verify the adjustment recommendations and generate a minimum effective FiO2 target table. Verify the minimum effective values ​​in the initial FiO2 adjustment recommendation form to ensure that the adjusted FiO2 is not lower than the critical value for maintaining basal oxygenation (≥21% for adults, ≥25% for premature infants) and can avoid the generation of reactive oxygen species caused by high oxygen concentration. After the verification is passed, organize the target FiO2 values ​​according to the monitoring time nodes and generate a minimum effective FiO2 target table.

[0086] The working principle and effects of the above technical solution are as follows:

[0087] The 3σ principle is used to remove abnormal SpO2 data (such as a single sudden increase / decrease >5% and lasting <3 seconds) to generate a clean data set, which improves the stability of SpO2 data, reduces errors caused by limb movement and poor sensor contact, and avoids deviations in subsequent FiO2 calculations due to inaccurate data.

[0088] The system generates a matching table by setting oxygenation target ranges for adults and premature infants (92-95% for adults and 88-92% for premature infants), which improves the population-specificity of oxygenation targets and reduces the risk of inappropriate oxygenation in different populations.

[0089] The SpO2-FiO2 dynamic correlation model is used to reverse-derive adjustment suggestions (such as reducing SpO2 by 5% for adults with SpO2 consistently >95%) to generate a suggestion sheet, which improves the scientific nature of FiO2 adjustment, reduces subjective errors in medical staff's adjustment based on experience, and makes the adjustment more in line with the patient's real-time oxygenation status.

[0090] After verification, the target table was generated to ensure that the adjusted FiO2 was not lower than the critical value (≥21% for adults and ≥25% for premature infants). This improved the safety of FiO2 use, avoiding hypoxemia caused by excessively low FiO2 or the induction of active oxygen by excessively high FiO2. This provides a reliable basis for subsequent precise reduction of FiO2 and protection of alveolar epithelial cells.

[0091] In one embodiment of the present invention, the method further includes a safety protection step: when the concentration of 8-isoprostaglandin is continuously monitored to be >30 pg / ml or the pH value is <6.5, an advanced alarm is automatically triggered and an emergency response procedure is initiated.

[0092] According to one embodiment of the present invention, a system for implementing the method of isocarbonate hyperventilation to protect alveolar epithelial cells from oxidative damage as described in any one of the above claims comprises:

[0093] The gas supply module includes independent oxygen, air, and carbon dioxide sources; a high-precision mass flow controller is installed on the passage connecting the carbon dioxide source in the gas supply module to precisely control the replenishment flow of exogenous CO2.

[0094] A gas mixing module, connected to the gas supply module, is used to fully mix oxygen, air, and carbon dioxide from the gas supply module to form an inhaled gas with a specific concentration. The gas mixing module includes a vortex mixing chamber, which is equipped with a guide vane and a buffer flow equalization net to ensure uniform mixing of oxygen and carbon dioxide. An oxygen concentration sensor and a carbon dioxide concentration sensor are located near the outlet of the mixing chamber.

[0095] A gas delivery module, connected to the gas mixing module, includes a mechanical ventilator capable of providing high tidal volume and high respiratory rate ventilation for delivering the mixed inhaled gas to the patient;

[0096] The monitoring module is used to monitor the patient's physiological parameters in real time, including at least an end-tidal carbon dioxide (EtCO2) sensor, a blood oxygen saturation (SpO2) sensor, and an analysis unit for detecting oxidative stress biomarkers in exhaled condensate;

[0097] The control feedback module, which is communicatively connected to the monitoring module, the gas supply module, the gas mixing module, and the gas delivery module, is configured as follows:

[0098] Receive real-time data from the monitoring module;

[0099] Based on the real-time data, the required exogenous CO2 supplementation flow rate and / or the required ventilator parameter adjustment values ​​are calculated through the built-in control algorithm;

[0100] Commands are sent to the gas supply module and / or the gas delivery module to execute the above-calculated adjustments, thereby maintaining the patient's PaCO2 within the target range; the safety protection mechanism built into the control feedback module is configured to automatically stop the supplementation of exogenous CO2 or trigger an alarm when the PetCO2 value is detected to be higher than 50 mmHg or the pH value is lower than 7.20.

[0101] The working principle and effects of the above technical solution are as follows:

[0102] The high-precision mass flow controller of the gas supply module can accurately control the external CO2 supplement flow, improve the stability of CO2 delivery, reduce the risk of PaCO2 deviating from the target range (35-50 mmHg) due to flow fluctuations, and provide a basis for the stability of the alveolar microenvironment.

[0103] The gas mixing module's vortex mixing chamber, combined with a flow guide plate, a buffer flow equalization network, and an O2 / CO2 concentration sensor at the outlet, significantly improves the uniformity of gas mixing, ensuring small fluctuations in inhaled gas concentration and reducing the problems of excessively high local oxygen concentrations leading to the production of active oxygen or insufficient CO2 affecting the lung protection effect.

[0104] The high-parameter ventilator with gas delivery module can stably provide high tidal volume and high respiratory rate ventilation, improve the reliability of ventilation support "above physiological needs", meet the demand for improved oxygen exchange efficiency, and reduce the situation of insufficient oxygenation caused by insufficient ventilation.

[0105] The monitoring module covers the analysis of EtCO2, SpO2 and oxidative stress markers. In particular, it integrates a dedicated oxidative stress analysis unit, which enables rapid and continuous monitoring of 8-isoprostaglandin and pH value. This improves the comprehensiveness of physiological and damage indicator monitoring, reduces the risk of early alveolar oxidative damage (such as elevated 8-isoprostaglandin) not being detected in time, and enhances the targeted nature of treatment adjustments.

[0106] The control feedback module automatically calculates the adjustment value and dynamically adjusts the target PaCO2 based on the level of oxidative stress, triggering safety protection (CO2 alarm stops when PetCO2 > 50 mmHg or pH < 7.20), which improves the safety and automation of treatment, reduces the risk of hypercapnia and acidosis, and also reduces the burden on medical staff to manually adjust parameters.

[0107] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An isocarbonic hyperventilation system for protecting alveolar epithelial cells from oxidative damage, characterized in that, The system includes: The gas supply module includes independent oxygen, air, and carbon dioxide sources; A gas mixing module, connected to the gas supply module, is used to fully mix oxygen, air and carbon dioxide from the gas supply module to form an inhalation gas with a specific concentration; A gas delivery module, connected to the gas mixing module, includes a mechanical ventilator capable of providing high tidal volume and high respiratory rate ventilation for delivering the mixed inhaled gas to the patient; The monitoring module is used to monitor the patient's physiological parameters in real time, including at least an end-tidal carbon dioxide sensor, a blood oxygen saturation sensor, and an analysis unit for detecting oxidative stress biomarkers in exhaled condensate; the analysis unit integrates a rapid electrochemical detection device that can complete a single detection of 8-isoprostaglandin concentration and pH value within 5 minutes; The control feedback module, which is communicatively connected to the monitoring module, the gas supply module, the gas mixing module, and the gas delivery module, is configured as follows: Receive real-time data from the monitoring module; Based on the real-time data, the required exogenous CO2 supplementation flow rate and / or the required ventilator parameter adjustment values ​​are calculated through the built-in control algorithm; Instructions are sent to the gas supply module and / or the gas delivery module to execute the above-calculated adjustments, thereby maintaining the patient's PaCO2 within the target range. The control feedback module incorporates an oxidative stress-ventilation parameter coupling algorithm to dynamically determine the target PaCO2 range based on the 8-isoprostaglandin concentration value.

2. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 1, characterized in that, The gas mixing module includes a vortex mixing chamber, which is equipped with a flow guide plate and a buffer flow equalization net to ensure uniform mixing of oxygen and carbon dioxide; an oxygen concentration sensor and a carbon dioxide concentration sensor are located near the outlet of the mixing chamber.

3. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 1, characterized in that, The gas supply module is equipped with a high-precision mass flow controller on the passage connecting to the carbon dioxide source, which is used to accurately control the replenishment flow of exogenous CO2.

4. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 1, characterized in that, The built-in safety protection mechanism of the control feedback module is configured to automatically stop the supplementation of exogenous CO2 or trigger an alarm when the PetCO2 value is detected to be higher than 50 mmHg or the pH value is lower than 7.

20.

5. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 1, characterized in that, The system is executed by the following method, the method including: S1. Provide patients requiring respiratory support with a minute ventilation volume higher than physiologically required, while supplementing the inhaled air with exogenous carbon dioxide using a gas mixing device; S2. Continuously monitor the patient's end-tidal carbon dioxide partial pressure, 8-isoprostol concentration in expiratory condensate, and pH value using monitoring equipment; S3. Adjust the exogenous carbon dioxide supplementation flow rate and / or ventilation parameters dynamically based on the monitoring values ​​to maintain the arterial blood carbon dioxide partial pressure within a preset target range, wherein the preset target range is dynamically adjusted according to the 8-isoprostaglandin concentration; S4. Based on the blood oxygen saturation monitoring value, dynamically reduce the inhaled oxygen concentration to the minimum effective level required to maintain the target blood oxygen saturation, and optimize ventilation-perfusion matching.

6. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 5, characterized in that, S1 includes: S11. Conduct a comprehensive assessment of patients requiring respiratory support. Based on the assessment results, calculate the baseline value of minute ventilation (MMV) exceeding physiological needs and the initial exogenous CO2 supplementation flow rate through the individualized algorithm built into the integrated control system, and generate an individualized initial parameter table for the patient. S12. Based on the generated individualized initial parameter table for the patient, select the appropriate ventilation interface; connect the intelligent ventilator in the gas delivery module, start the isocarbonation hyperventilation mode of the ventilator, set the parameters to the baseline values ​​calculated in S11, and complete the establishment of the ventilation pathway. S13. Based on the established ventilation path, start the vortex mixing chamber gas mixing device; at the same time, collect the concentration data of the premixed gas in real time through the O2 concentration sensor and CO2 concentration sensor at the device outlet, and generate a real-time record table of premixed gas concentration. S14. Based on the generated real-time record table of premixed gas concentration, if the CO2 concentration in the mixed gas meets the concentration corresponding to the initial replenishment flow calculated in S11, the premixed gas is delivered to the patient's ventilation interface through the inhalation circuit of the gas delivery module; if the concentration deviates, the CO2 input flow is adjusted through the mass flow controller in the gas supply module until the concentration reaches the standard before delivery is started.

7. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 5, characterized in that, S2 includes: S21 utilizes the constructed ventilation and carbon dioxide replenishment system to deploy various sensors equipped with the monitoring module at corresponding parts of the patient's body. Among them, the sensors include an integrated rapid expiratory condensate sampling device. After the monitoring equipment is started, the end-expiratory carbon dioxide partial pressure sensor is calibrated using standard calibration gas, and the blood oxygen saturation sensor is calibrated using standard blood oxygen simulation signal. A calibration qualification report for the monitoring equipment is then generated. S22. Based on the generated calibration report of the monitoring equipment, start the continuous sampling mode of the monitoring equipment; transport the collected exhaled condensate sample to the analysis unit, use enzyme-linked immunosorbent assay to detect the concentration of 8-isoprostaglandin in the sample, use a precision pH meter to detect the pH value of the sample, and then generate a real-time monitoring data sequence list and an oxidative stress marker detection report. S23. Based on the generated real-time monitoring data sequence list and oxidative stress marker detection report, a sliding window filtering algorithm is used to remove abnormal fluctuations in end-tidal carbon dioxide partial pressure and blood oxygen saturation data; a data consistency verification method is used to determine whether the exhaled condensate sample is contaminated; the filtered data is marked for validity, and finally a cleaned monitoring dataset is generated. S24. By using the damage risk assessment model built into the integrated control system, a correlation is established between the end-tidal carbon dioxide partial pressure value and the estimated arterial blood carbon dioxide partial pressure value, and a correlation is established between the 8-isoprostol concentration, pH value and alveolar oxidative damage level, generating a real-time alveolar damage risk assessment table.

8. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 5, characterized in that, The S3 includes: S31. Based on the generated real-time alveolar injury risk assessment table, the control feedback module of the integrated control system receives relevant data in real time and analyzes two core control requirements: First, it determines whether the arterial blood carbon dioxide partial pressure deviates from the preset target range, which is 35-50 mmHg; Second, it determines whether the alveolar oxidative damage level has changed. If PaCO2 is within the target range and the alveolar oxidative damage level has not increased, it is determined that no parameter adjustment is required. If either of the above conditions is not met, the parameter control process is triggered, and a control requirement trigger command is generated. S32. Based on the generated regulatory demand trigger command, if an increase in alveolar oxidative damage level is detected, specifically manifested as an 8-isoprostaglandin concentration greater than 20 pg / ml, the system automatically adjusts the target range of PaCO2 upward to 45-50 mmHg; if a decrease in oxidative damage level is detected, specifically manifested as an 8-isoprostaglandin concentration less than 15 pg / ml, or if the patient is in the recovery period, the system automatically adjusts the target range of PaCO2 downward to 35-45 mmHg and generates a dynamic target PaCO2 interval table. S33. Based on the generated dynamic target PaCO2 interval table, a hybrid algorithm combining PID controller and fuzzy logic is used to calculate the parameter adjustment amount, and finally generate the parameter adjustment amount details; S34. Perform parameter adjustments and verify the control effect: Based on the parameter adjustment details generated in S33, the control feedback module sends a carbon dioxide flow adjustment command to the gas supply module and a ventilator parameter adjustment command to the gas delivery module. After the adjustment is completed, monitor continuously for 3-5 minutes, collect new end-tidal carbon dioxide partial pressure and arterial blood carbon dioxide partial pressure data, and verify whether PaCO2 falls within the dynamic target range set in S32. If PaCO2 meets the requirements of this range, a control qualification record is generated. If not, repeat steps S33-S34 until PaCO2 accurately reaches the set target.

9. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 8, characterized in that, The hybrid algorithm of PID controller + fuzzy logic is used to calculate the adjustment amount. Specifically, the PID controller calculates the basic adjustment amount of CO2 supplementary flow based on the deviation between the current PaCO2 estimate and the target value. The fuzzy logic then corrects the basic adjustment amount by combining airway pressure data and SpO2 data.

10. The isocarbonate hyperventilation system for protecting alveolar epithelial cells from oxidative damage according to claim 5, characterized in that, The S4 includes: S41. Based on the SpO2 time-series data in the generated post-cleaning monitoring dataset, a safe oxygenation target range is set; the minimum inhaled oxygen concentration required to maintain this range is derived in reverse through the FiO2 optimization algorithm of the integrated control system, and a minimum effective FiO2 target table is generated. S42. Based on the generated minimum effective target table for FiO2, a gradual downward adjustment strategy is adopted to adjust FiO2. If SpO2 remains within the safe target range, and the adult range for PaO2 is greater than 60 mmHg, and the range for PaO2 in preterm infants is greater than 50 mmHg, then the current FiO2 is determined to be the effective minimum value, and a qualified FiO2 downward adjustment record is generated. If SpO2 is lower than the target range, the downward adjustment is paused and FiO2 is restored to the previous effective level. S43. Based on the constructed ventilation system, the ventilation-perfusion matching-related indicators are continuously collected through the respiratory mechanics monitoring function built into the ventilator, and a ventilation-perfusion imbalance analysis report is generated. S44. Based on the generated ventilation-perfusion imbalance analysis report, take targeted optimization measures to optimize the imbalanced areas and generate a ventilation-perfusion optimization report. S45. Based on the generated ventilation and blood flow optimization report, collect exhaled condensate samples every 4-6 hours to detect 8-isoprostaglandin concentration and pH value; compare the oxidative damage indicators before and after optimization. If the 8-isoprostaglandin concentration decreases by ≥20% and the pH value rises back to the range of 6.8-7.2, the optimization is deemed effective, and the current parameters are maintained; if the indicators do not improve, return to S43 to re-analyze the causes of ventilation and blood flow imbalance and adjust the optimization strategy.

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