Cooperative evaluation and adjustment system for heart and lung capacity after lung transplantation

Abstract

The invention, which belongs to the technical field of the medical equipment, discloses a lung transplantation post-operative cardiopulmonary capacity collaborative evaluation and adjustment system comprising a multi-parameter acquisition module, a cardiopulmonary interaction modeling module, a capacity strain test module, a haemodynamics target setting module, a treatment response prediction module and an adjustment execution module. The system quantitatively analyzes the complex relationship among the right heart function, the pulmonary vascular resistance and the pulmonary compliance through a cardiopulmonary interaction modeling engine, evaluates the tolerance of a patient to the capacity change through a capacity strain test, and formulates an individualized hemodynamic target according to a specific cardiopulmonary interaction mode of the patient. Potential influences of different intervention measures are simulated, treatment parameters are automatically adjusted, the hemodynamic stability and the oxygenation function of a lung transplantation patient are remarkably improved, and the occurrence rate of complications is reduced.

Description

Technical Field

[0001] This invention belongs to the field of medical device technology, specifically relating to a system for the coordinated assessment and regulation of cardiopulmonary volume after lung transplantation, which is suitable for the dynamic monitoring and precise management of cardiopulmonary function in lung transplant patients after surgery. Background Technology

[0002] Lung transplantation is an effective treatment for end-stage lung disease, but post-operative patients face complex challenges in managing cardiopulmonary function. Following lung transplantation, the patient's cardiopulmonary system is highly unstable, with complex interactions between right ventricular function, pulmonary vascular resistance, and lung compliance. Inadequate volume management can lead to serious complications such as pulmonary edema, right ventricular failure, or insufficient tissue perfusion, significantly impacting graft survival and patient prognosis.

[0003] In the prior art, CN118800458A discloses a postoperative complication prediction system for cardiothoracic surgery. This system predicts the risk of postoperative complications by monitoring indicators such as oxygenation factor, alveolar ventilation, and lung expansion capacity coefficient. Although this system can identify impaired lung oxygenation capacity, it has the following shortcomings: First, the system lacks the ability to quantitatively analyze the cardiopulmonary interaction and cannot accurately assess the dynamic balance between right ventricular function and pulmonary vascular resistance; second, the system only has predictive functions and lacks active adjustment capabilities, and cannot dynamically adjust the treatment plan according to the patient's cardiopulmonary interaction characteristics; third, the system does not consider the impact of volume overload on the cardiopulmonary system and cannot assess the patient's tolerance and responsiveness to fluid therapy; fourth, the system lacks an individualized hemodynamic target setting mechanism, making it difficult to formulate precise treatment goals for patients with different cardiopulmonary interaction patterns.

[0004] Volume management after lung transplantation requires striking a delicate balance between ensuring adequate tissue perfusion and preventing pulmonary edema. Excessive volume overload increases pulmonary vascular hydrostatic pressure, leading to transplanted lung edema, while insufficient volume can cause decreased right ventricular preload and inadequate tissue perfusion. Traditional hemodynamic monitoring methods primarily rely on static pressure parameters such as central venous pressure and pulmonary artery wedge pressure, but these parameters cannot accurately reflect cardiac volume responsiveness and are difficult to predict the effectiveness of fluid therapy. In recent years, functional hemodynamic monitoring methods such as stroke volume variability and pulse pressure variability have been increasingly applied clinically, but their application in lung transplant patients still faces challenges because changes in transplant lung compliance and pulmonary vascular remodeling significantly affect the cardiopulmonary interaction.

[0005] Furthermore, the assessment of right ventricular function in lung transplant recipients is extremely important. Long-term pulmonary hypertension before transplantation can lead to right ventricular hypertrophy and functional impairment, while the rapid changes in pulmonary vascular resistance after surgery can generate new stress on the right ventricle. Accurately assessing right ventricular reserve function and predicting its adaptability to changes in volume overload and afterload is a key issue in the management of lung transplant recipients. Current technology lacks comprehensive assessment tools that integrate cardiac function, pulmonary function, and hemodynamic parameters, thus failing to provide accurate decision support for clinicians.

[0006] Therefore, there is an urgent need to develop a post-lung transplant cardiopulmonary volume co-assessment and regulation system that can quantitatively analyze cardiopulmonary interaction, assess volume tolerance, set individualized hemodynamic goals, and provide treatment decision support, in order to improve the quality of post-lung transplant patient management and clinical outcomes. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a system for the coordinated assessment and regulation of cardiopulmonary volume after lung transplantation. It aims to achieve accurate assessment and dynamic regulation of postoperative cardiopulmonary function in lung transplant patients through cardiopulmonary interaction modeling, volume strain testing, and individualized target setting, thereby improving hemodynamic stability, optimizing oxygenation, and reducing the incidence of postoperative complications.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] The post-lung transplant cardiopulmonary volume collaborative assessment and regulation system includes a multi-parameter acquisition module, a cardiopulmonary interaction modeling module, a volume strain testing module, a hemodynamic target setting module, a treatment response prediction module, and a regulation execution module.

[0010] The multi-parameter acquisition module collects real-time cardiac, pulmonary function, and hemodynamic parameters from lung transplant recipients. The cardiopulmonary interaction modeling module constructs a cardiopulmonary coupling coefficient and pulmonary vascular afterload index based on the acquired parameters, establishing a cardiopulmonary interaction model reflecting the dynamic relationship between right ventricular function and pulmonary vascular resistance. The volume strain testing module assesses patients' volume tolerance through precisely controlled fluid load challenges. The hemodynamic target setting module determines individualized hemodynamic target values ​​based on the cardiopulmonary interaction model and volume tolerance assessment results. The treatment response prediction module simulates the potential impact of different interventions on cardiopulmonary function and generates treatment recommendations. The adjustment execution module automatically adjusts fluid infusion, drug dosage, and ventilator parameters according to the treatment recommendations.

[0011] Compared with the prior art, the present invention has the following advantages:

[0012] First, this invention constructs the cardiopulmonary coupling coefficient and pulmonary vascular afterload index through a cardiopulmonary interaction modeling module, enabling quantitative analysis of the complex relationship between right ventricular function and pulmonary vascular resistance. This accurately reflects the dynamic balance of the cardiopulmonary system after lung transplantation, providing a scientific basis for clinical decision-making. Traditional methods focus only on changes in a single parameter, failing to reveal the intrinsic mechanism of cardiopulmonary interaction. In contrast, this invention significantly improves the accuracy and comprehensiveness of the assessment through multi-parameter integrated modeling.

[0013] Secondly, this invention innovatively introduces a volume strain testing module, which dynamically assesses a patient's tolerance and adaptability to volume changes through precisely controlled fluid load challenges. This module can identify patients with good volume responsiveness, avoiding blindly restricting fluids and causing insufficient tissue perfusion, while also identifying patients with poor volume tolerance early on, preventing pulmonary edema caused by excessive fluid load. Compared to traditional static pressure monitoring, this dynamic assessment method can more accurately guide fluid therapy decisions and reduce the incidence of pulmonary edema by more than 35%.

[0014] Third, this invention achieves individualized treatment goal setting through a hemodynamic target setting module. Different patients exhibit significant differences in their cardiopulmonary interaction patterns, making it difficult to meet individualized needs with uniform treatment goals. This invention sets optimal preload, afterload, and myocardial contractility target values ​​based on the patient's specific cardiopulmonary interaction characteristics, resulting in more precise treatment plans, a hemodynamic target achievement rate increase of over 40%, and significant improvement in tissue perfusion indicators.

[0015] Fourth, the treatment response prediction module of this invention can simulate the potential effects of different treatment options before implementing intervention, avoiding the risks associated with traditional trial-and-error treatment. Based on a cardiopulmonary interaction model, this module performs predictive analysis, enabling early identification of interventions that may lead to hemodynamic deterioration, selection of the optimal treatment plan, and significant reduction in the incidence of iatrogenic complications.

[0016] Fifth, this invention achieves automated and precise adjustment of fluid, medication, and ventilation parameters through the adjustment execution module, reducing the workload of medical staff and improving the timeliness and accuracy of treatment. Based on real-time monitoring data and prediction results, the system dynamically optimizes treatment plans, achieving closed-loop management, significantly improving the patient's hemodynamic stability, and shortening ICU stay by more than 20%.

[0017] In summary, this invention significantly improves the quality of postoperative cardiopulmonary function management in lung transplant patients, reduces the incidence of complications, and increases graft survival rate through innovative technologies such as cardiopulmonary interaction modeling, volume strain testing, individualized target setting, and treatment response prediction. It has important clinical application value. Attached Figure Description

[0018] Figure 1This is a schematic diagram of the overall structure of the post-lung transplant cardiopulmonary volume collaborative assessment and regulation system of the present invention;

[0019] Figure 2 This is a schematic diagram of the workflow of the cardiopulmonary interactive modeling module of the present invention;

[0020] Figure 3 This is a schematic diagram of the workflow of the capacity strain testing module of the present invention;

[0021] Figure 4 This is a schematic diagram of the workflow of the hemodynamic target setting module of the present invention;

[0022] Figure 5 This is a schematic diagram of the workflow of the treatment response prediction module of the present invention;

[0023] Figure 6 This is a schematic diagram of the workflow of the adjustment and execution module of the present invention.

[0024] The numbers in the diagram are explained as follows: 1-Multi-parameter acquisition module, 2-Cardiopulmonary interaction modeling module, 3-Volume strain testing module, 4-Hemodynamic target setting module, 5-Treatment response prediction module, 6-Regulation execution module. Detailed Implementation

[0025] Please refer to the attached document. Figures 1-6 The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0026] Reference Figure 1 This invention provides a system for coordinated assessment and regulation of cardiopulmonary volume after lung transplantation, comprising a multi-parameter acquisition module 1, a cardiopulmonary interaction modeling module 2, a volume strain testing module 3, a hemodynamic target setting module 4, a treatment response prediction module 5, and a regulation execution module 6. These modules are interconnected and work collaboratively to achieve accurate assessment and dynamic regulation of cardiopulmonary function in patients after lung transplantation.

[0027] The multi-parameter acquisition module 1 is used to collect various physiological parameters of patients after lung transplantation in real time, providing a data basis for subsequent evaluation and adjustment. This module includes a cardiac function monitoring unit, a pulmonary function monitoring unit, and a hemodynamic monitoring unit.

[0028] The cardiac function monitoring unit acquires cardiac function parameters via echocardiography. Specifically, this unit uses transthoracic or transesophageal echocardiography to monitor right ventricular ejection fraction (RVB), tricuspid regurgitation velocity, and ventricular wall motion velocity in real time. RVB reflects the overall systolic function of the right heart, with a normal range of 45%-55%. In lung transplant recipients, RVB may be reduced due to right ventricular dysfunction caused by long-term pulmonary hypertension before transplantation, or it may recover due to a sharp decrease in pulmonary vascular resistance after surgery. Tricuspid regurgitation velocity is used to estimate pulmonary artery systolic pressure. Using the simplified Bernoulli equation, pulmonary artery systolic pressure can be estimated from the peak tricuspid regurgitation velocity and right atrial pressure. Ventricular wall motion velocity is measured using tissue Doppler imaging, reflecting local myocardial systolic function and allowing for early detection of right ventricular dysfunction. The acquisition frequency is set to once every 5 minutes, increasing to once every 1 minute during volume strain testing to ensure timely capture of dynamic changes in cardiac function.

[0029] The pulmonary function monitoring unit collects pulmonary function parameters through respiratory mechanics monitoring equipment. This unit is integrated into the mechanical ventilation system and continuously monitors lung compliance, airway resistance, and oxygenation index. Lung compliance is defined as the change in lung volume caused by a unit change in pressure, calculated as tidal volume divided by the difference between plateau pressure and positive end-expiratory pressure; the normal value is 50-100 mL / cmH2O. After lung transplantation, the compliance of the transplanted lung may decrease due to ischemia-reperfusion injury, pulmonary edema, or acute rejection. Airway resistance reflects the degree of airway patency and is calculated by measuring airflow rate and airway pressure difference; the normal value is 0.5-2.5 cmH2O / (L·s). The oxygenation index is defined as the ratio of arterial blood oxygen partial pressure to inhaled oxygen concentration and is a key indicator for assessing pulmonary gas exchange function; the normal value is greater than 400 mmHg. An oxygenation index below 300 mmHg indicates moderate to severe oxygenation dysfunction, and below 200 mmHg is defined as severe acute respiratory distress syndrome. The monitoring system automatically calculates and updates the above parameters every 30 seconds to achieve continuous monitoring of lung function.

[0030] The hemodynamic monitoring unit collects hemodynamic parameters via a pulmonary artery catheter and arterial pressure waveform analysis equipment. After pulmonary artery catheter insertion, pulmonary artery pressure and central venous pressure can be directly measured. Pulmonary artery pressure includes systolic pressure, diastolic pressure, and mean pressure, with normal values ​​of 15-30 mmHg, 4-12 mmHg, and 9-18 mmHg, respectively. After lung transplantation, pulmonary artery pressure is usually significantly lower than pre-operatively, but some patients may experience elevated pulmonary artery pressure due to graft dysfunction or volume overload. Central venous pressure reflects right ventricular preload, with a normal value of 2-8 mmHg. Excessively high values ​​suggest volume overload or right ventricular dysfunction, while excessively low values ​​suggest volume insufficiency. Stroke volume variability is calculated using arterial pressure waveform analysis technology, reflecting the heart's responsiveness to volume changes. This parameter is calculated based on the change in stroke volume during the respiratory cycle, with a normal value of less than 13%. A stroke volume variability greater than 13% indicates a volume-responsive state, suggesting that fluid therapy may improve cardiac output, while a variability less than 13% indicates poor response to fluid therapy. This unit also simultaneously collects parameters such as cardiac output and systemic vascular resistance, with a sampling frequency of 10 times per second to ensure the timeliness of the data.

[0031] Reference Figure 2 The cardiopulmonary interaction modeling module 2 constructs a quantitative model reflecting the complex interactions of the cardiopulmonary system based on the data acquired by the multi-parameter acquisition module 1. This module includes a coupling coefficient calculation unit, an afterload index calculation unit, and an interaction model construction unit.

[0032] The coupling coefficient calculation unit is responsible for calculating the cardiopulmonary coupling coefficient, which quantitatively describes the strength of the association between right ventricular function and lung compliance. The calculation process is as follows: First, the right ventricular ejection fraction at baseline is obtained. and lung compliance Then, the right ventricular ejection fraction was obtained in real time. and lung compliance ;Calculate the rate of change of right ventricular ejection fraction and lung compliance change rate The cardiopulmonary coupling coefficient is calculated using the following innovative formula:

[0033] ,

[0034] in, The cardiopulmonary coupling coefficient, The rate of change of right ventricular ejection fraction. The rate of change in lung compliance, The smoothing factor is set to 0.01 to avoid the denominator being zero. The attenuation coefficient is set to 2.0 to reflect the nonlinear attenuation of coupling strength when lung compliance changes significantly. It is the base of the natural logarithm. The design of this formula considers two key factors: first, the numerator term... Divide by the denominator This reflects the sensitivity of right ventricular function to changes in lung compliance; a larger ratio indicates a stronger response of right ventricular function to changes in lung compliance. Secondly, the exponential decay term... This reflects the decreased stability of the cardiopulmonary coupling relationship when lung compliance changes drastically. This ensures that the coupling coefficient accurately reflects the decoupling state of the cardiopulmonary system when lung compliance deteriorates rapidly. In a preferred embodiment, when A value greater than 1.5 indicates good cardiopulmonary coupling, meaning the right ventricular function has sufficient compensatory capacity to respond to changes in lung condition; when... A value between 0.8 and 1.5 indicates moderate cardiopulmonary coupling, requiring close monitoring; when... A value less than 0.8 indicates poor cardiopulmonary coupling, meaning that the right heart function has limited compensatory capacity for the deterioration of lung condition, requiring active intervention.

[0035] The afterload index calculation unit is responsible for calculating the pulmonary vascular afterload index, which comprehensively reflects the afterload burden faced by the right ventricle. The calculation process integrates pulmonary artery pressure and stroke volume variability. Specifically, the mean pulmonary artery pressure is first obtained. pulmonary artery systolic blood pressure pulmonary artery diastolic pressure and stroke volume variation rate The pulmonary vascular afterload index is calculated using the following innovative formula:

[0036] ,

[0037] in, Pulmonary vascular afterload index (unit: dimensionless) Mean pulmonary artery pressure (unit: mmHg) Pulmonary artery systolic blood pressure (unit: mmHg) Pulmonary artery diastolic pressure (unit: mmHg) The percentage of variation in stroke volume (in percentage, need to be divided by 100 to convert to a decimal). The weighting coefficient is set to 0.5 for adjustment. The contribution to the afterload index. The design principle of this formula is as follows: First, the numerator term... Divide by the denominator The ratio of mean pulmonary artery pressure to pulse pressure reflects the relationship between the mean resistance load and pulsatile load of the pulmonary vessels. A higher ratio indicates poorer vascular compliance and a heavier afterload. Secondly, The item reflects the impact of capacity responsiveness on afterload assessment, when An elevated level indicates that the patient is in a volume-responsive state, where right ventricular preload reserve is insufficient, relatively increasing afterload burden. In a preferred embodiment, when A value less than 1.2 indicates that the afterload is within the normal range; when A value between 1.2 and 2.0 indicates a slight increase in afterload, requiring optimized fluid management; when A value greater than 2.0 indicates a severely elevated afterload, requiring active efforts to reduce pulmonary vascular resistance.

[0038] The interactive model building unit establishes a cardiopulmonary interaction model based on the cardiopulmonary coupling coefficient and the pulmonary vascular afterload index. This model employs a nonlinear dynamic method to describe the interaction among right ventricular function, pulmonary vascular resistance, and lung compliance. The core equation of the model is:

[0039] ,

[0040] ,

[0041] in, The right ventricular function index (which comprehensively reflects the right ventricular ejection fraction and cardiac output) For pulmonary vascular resistance, For time, , , , , , All model parameters were determined by fitting clinical data. The target is pulmonary vascular resistance. In a preferred embodiment, , , , , , The first equation describes the variation of the right ventricular function index: The item indicates that good cardiopulmonary coupling promotes improvement in right ventricular function. The item indicates that increased afterload suppresses right ventricular function. The term represents the natural decline in right ventricular function. The second equation describes the changing pattern of pulmonary vascular resistance: The item indicates that an increase in the afterload index leads to an increase in pulmonary vascular resistance. The item indicates that good cardiopulmonary coupling helps reduce pulmonary vascular resistance. The term represents the trend of pulmonary vascular resistance regressing towards the target value. This model can dynamically predict the evolutionary trajectory of the cardiopulmonary system under different interventions, providing a theoretical basis for treatment decisions.

[0042] Reference Figure 3The volume strain testing module 3 assesses a patient's tolerance and adaptation to volume changes through a precisely controlled fluid load challenge. This module includes a load challenge unit, a response monitoring unit, and a tolerance assessment unit.

[0043] The fluid challenge unit implemented a standardized fluid challenge protocol. After baseline data stabilized, the unit controlled the infusion pump to infuse 250 mL of balanced crystalloid solution at a constant rate of 25 mL / min over 10 minutes. This infusion volume and rate were chosen based on the following considerations: firstly, the 250 mL volume was sufficient to produce measurable hemodynamic changes without causing significant volume overload; secondly, the 10-minute infusion time allowed the cardiopulmonary system to fully respond to the volume changes, avoiding transient effects caused by excessively rapid infusion. Throughout the infusion, the patient remained supine, and ventilator parameters were kept constant to avoid the influence of changes in position and ventilation mode on the outcome.

[0044] The response monitoring unit continuously monitors multiple hemodynamic and pulmonary function parameters during fluid overload challenges. Key monitoring parameters include cardiac output, right ventricular ejection fraction, lung compliance, pulmonary artery pressure, and oxygenation index. Cardiac output is measured using either the thermodilution method or arterial pressure waveform analysis, with values ​​recorded every 1 minute. The cardiac output response amplitude is defined as the difference between the maximum cardiac output after infusion and the baseline value, expressed as a percentage. Lung compliance is calculated in real time using a respiratory mechanics monitoring system; the rate of change in lung compliance is defined as the absolute value of the difference between the minimum lung compliance after infusion and the baseline value, expressed as a percentage. The unit also simultaneously monitors changes in pulmonary artery pressure to assess the impact of volume overload on pulmonary vessels. All data are transmitted in real time to the system database, providing complete time-series data for subsequent analysis.

[0045] The tolerance assessment unit generates volume tolerance assessment results based on monitoring data. The assessment algorithm is based on the cardiac output response amplitude. and lung compliance change rate Multi-level judgment is performed. Specific judgment criteria are as follows: If... and If the fluid level is within acceptable limits, it is considered that the patient has good volume tolerance, indicating that the patient is in a volume-responsive state and the lungs tolerate volume overload well. In this case, appropriately increasing fluid infusion to improve tissue perfusion can be considered. and If the patient exhibits poor volume tolerance, it indicates insufficient cardiac response to volume overload and significantly decreased lung compliance. Strict fluid restriction and consideration of diuretic use are advised. or If the volume tolerance is low, it is considered moderate, requiring careful decision-making based on other clinical indicators. The assessment also considers changes in pulmonary artery pressure; if the mean pulmonary artery pressure increases by more than 5 mmHg after volume loading, the tolerance rating is downgraded by one level to ensure safety. Compared to traditional static pressure monitoring, this assessment method can more accurately predict the efficacy and risks of fluid therapy, guiding individualized volume management decisions.

[0046] Reference Figure 4 The hemodynamic target setting module 4 sets individualized hemodynamic targets for patients based on the cardiopulmonary interaction model and volume tolerance assessment results. This module includes a preload target calculation unit, an afterload target calculation unit, and a contractility target calculation unit.

[0047] The preload target calculation unit determines the optimal preload target value based on the volume tolerance assessment results. Preload is characterized by central venous pressure (CVP) or right ventricular end-diastolic volume index. For patients with good volume tolerance, the system recommends a CVP target value of 10-12 mmHg to fully utilize the Frank-Starling mechanism to increase cardiac output. For patients with moderate volume tolerance, a CVP target value of 8-10 mmHg is recommended to ensure tissue perfusion while avoiding excessive volume overload. For patients with poor volume tolerance, a CVP target value of 6-8 mmHg is recommended, employing a restrictive fluid management strategy. The unit also adjusts the target value based on the cardiopulmonary coupling coefficient: when... When the preload target value is lowered by 10%, the burden on the heart is reduced; when At this time, the preload target value is increased by 10% to optimize cardiac output. The revised target value serves as a reference standard for fluid management, guiding clinicians in their fluid infusion decisions.

[0048] The afterload target calculation unit determines the optimal afterload target value based on the pulmonary vascular afterload index. Afterload is mainly characterized by pulmonary vascular resistance and pulmonary artery pressure. The system calculates the afterload target value based on... The numerical target is set when When the target value for pulmonary vascular resistance is set at 1.5-2.5 Wood units and the target value for mean pulmonary artery pressure is set at 12-18 mmHg, no special intervention is required; when At this time, the target value for pulmonary vascular resistance is set at 1.0-1.5 Wood units, and the target value for mean pulmonary artery pressure is set at 10-15 mmHg. Volume management needs to be optimized, and the use of vasodilators should be considered. At this time, the target value for pulmonary vascular resistance is set to be less than 1.0 Wood unit, and the target value for mean pulmonary artery pressure is set to be less than 12 mmHg. It is necessary to actively reduce afterload, including the use of inhaled nitric oxide, intravenous vasodilators, or prostacyclin drugs. The setting of afterload targets fully considers right ventricular functional reserve and avoids systemic hypotension caused by excessive reduction of afterload.

[0049] The contractility target calculation unit determines the optimal target value of myocardial contractility based on the right ventricular ejection fraction and a cardiopulmonary interaction model. Myocardial contractility is characterized by the right ventricular ejection fraction and the right ventricular work index. The system sets the target based on the baseline right ventricular ejection fraction: when the baseline... At that time, the contraction force target was set to maintain. Normally, positive inotropic drugs are not required; when baseline... When the contraction force is between 35% and 45%, the target is set to increase. If the baseline level reaches 40%-45%, low-dose dobutamine support can be considered; when the baseline level is... At that time, the contraction force target was set to increase. When the contractility level is greater than 35%, positive inotropic drugs are needed to support the system and afterload should be reduced preferentially. This unit uses a cardiopulmonary interaction model to predict the effects of different contractility levels on cardiac output and pulmonary vascular resistance, ensuring that increased contractility does not lead to excessively high pulmonary vascular resistance, and achieving coordinated optimization of contractility and afterload targets.

[0050] Reference Figure 5 The treatment response prediction module 5, based on a cardiopulmonary interaction model, simulates the potential impact of different interventions on cardiopulmonary function, providing predictive support for clinical decision-making. This module includes an intervention simulation unit, an effect prediction unit, and a protocol optimization unit.

[0051] The intervention simulation unit simulates three commonly used clinical interventions: fluid management protocols, vasoactive drug protocols, and mechanical ventilation parameter adjustment protocols. Fluid management protocols include strategies such as restrictive fluid resuscitation, free fluid resuscitation, and goal-oriented fluid resuscitation, simulating the effects of different infusion rates and total volumes on hemodynamics. Vasoactive drug protocols include different dosage combinations of drugs such as dobutamine, norepinephrine, milrinone, and inhaled nitric oxide, simulating the combined effects of each drug on myocardial contractility, vascular resistance, and cardiac output. Mechanical ventilation parameter adjustment protocols include different settings for tidal volume, positive end-expiratory pressure, and inhaled oxygen concentration, simulating the effects of ventilation parameters on lung compliance, oxygenation, and cardiopulmonary interaction. The simulation process is based on the kinetic equations of a cardiopulmonary interaction model, using numerical methods to calculate the system state trajectory after each protocol is implemented.

[0052] The effect prediction unit quantitatively assesses the expected effects of each intervention. Predictive indicators include changes in cardiac output, lung compliance, oxygenation index, pulmonary artery pressure, and cardiopulmonary coupling coefficient. Specifically, the system substitutes the parameters of each intervention into the cardiopulmonary interaction model to calculate the predicted values ​​of each indicator at 1 hour, 4 hours, and 24 hours after implementation. The prediction algorithm considers the synergistic and antagonistic effects between interventions; for example, fluid infusion may improve preload but increase afterload, while vasodilators may reduce afterload but decrease venous return. The system quantitatively evaluates each intervention using a comprehensive scoring function.

[0053] ,

[0054] in, For the comprehensive evaluation of the proposal, To predict the extent of improvement in cardiac output, For the target improvement value of cardiac output, The predicted improvement in oxygenation index, The target improvement value for the oxygenation index. The predicted increase in pulmonary artery pressure, The upper limit of pulmonary artery pressure, This represents the predicted decrease in lung compliance (0 if it increases). Baseline lung compliance, , , , This refers to the weighting coefficient. In a preferred embodiment, , , , This weighting reflects the clinical emphasis on cardiac output and oxygenation, while also taking safety constraints into account. A higher score indicates a better expected outcome and lower risk.

[0055] The intervention unit selects the best intervention based on the predicted score. The optimization process employs a multi-objective algorithm to minimize the risks of increased pulmonary artery pressure and decreased lung compliance while improving cardiac output and oxygenation. For multiple interventions with similar scores, the system prioritizes the simplest, safest, and least costly option. The optimization results are output as treatment recommendations, including recommended fluid infusion rates, types and dosages of vasoactive drugs, mechanical ventilation parameter settings, and the expected time to reach the target. The treatment recommendations also include risk warnings, clearly indicating potential adverse reactions and key monitoring points to help clinicians make informed decisions.

[0056] Reference Figure 6The regulation and execution module 6 automatically adjusts fluid infusion, drug dosage, and ventilator parameters based on the treatment recommendations generated by the treatment response prediction module 5, achieving closed-loop management. This module includes a fluid regulation unit, a drug regulation unit, and a ventilation regulation unit.

[0057] The fluid regulation unit automatically adjusts the infusion rate of the infusion pump based on the preload target and volume tolerance. The regulation strategy employs a feedback control algorithm, comparing the current central venous pressure with the target value in real time. Adjust the infusion rate according to the magnitude of the deviation. When mmHg, the infusion rate is increased to 100 mL / h; when When mmHg, the infusion rate is set to 50 mL / h; when When mmHg, the infusion rate is set to 25 mL / h to maintain the current state; when When the blood pressure reaches mmHg, the infusion should be paused and the need for diuresis assessed. Safety limits should be set during the adjustment process; the change in infusion rate should not exceed 50 mL / h in a single adjustment. After each adjustment, observe for 15 minutes before making the next adjustment to avoid excessively rapid volume changes. The fluid regulation unit also monitors cumulative infusion volume and urine output. When the cumulative positive balance exceeds 1000 mL, the system will issue a warning prompting an assessment of the volume status.

[0058] The drug regulation unit automatically adjusts the infusion dose of vasoactive drugs based on afterload and contractility targets. For positive inotropic drugs such as dobutamine, the regulation strategy is based on real-time monitoring of right ventricular ejection fraction. When the level is more than 2% below the target value, the dobutamine dose should be increased by 1 μg / (kg·min); when If the target value is reached within ±2%, maintain the current dose; when When the dobutamine dose exceeds the target value by more than 2%, the dose should be reduced by 1 μg / (kg·min). The dose adjustment range is 2.5-10 μg / (kg·min), and the effect should be evaluated after 30 minutes following each adjustment. For vasodilators such as nitroglycerin or milrinone, the adjustment strategy is based on monitoring pulmonary artery pressure and systemic blood pressure. When the mean pulmonary artery pressure is more than 3 mmHg above the target value and the mean systemic blood pressure is greater than 65 mmHg, the vasodilator dose is increased; when the pulmonary artery pressure reaches the target value or the mean systemic blood pressure is less than 60 mmHg, the dose increase is stopped or the dose is reduced. The drug adjustment unit is equipped with multiple safety checks, including real-time monitoring of heart rate, blood pressure, and heart rhythm. When the heart rate is greater than 120 beats / min, the blood pressure is lower than the safety limit, or a malignant arrhythmia occurs, the dose increase is automatically stopped and an alarm is issued.

[0059] The ventilation regulation unit automatically adjusts ventilator parameters based on oxygenation targets and lung-protective ventilation principles. Oxygenation optimization strategies are achieved by adjusting the inhaled oxygen concentration and positive end-expiratory pressure (PEEP). When the oxygenation index (OI) is below 300 mmHg, the system first increases PEEP, gradually increasing it by 2 cmH2O from baseline, up to a maximum of 12 cmH2O, while monitoring lung compliance and hemodynamic changes. If increasing PEEP results in a decrease in lung compliance exceeding 15% or a decrease in cardiac output exceeding 10%, further increases in PEEP are stopped, and the inhaled oxygen concentration is increased instead. The inhaled oxygen concentration is gradually increased by 5% from baseline, up to a maximum of 60%, to avoid oxygen toxicity caused by high oxygen concentrations. When the OI reaches above 400 mmHg, the system begins to reduce the inhaled oxygen concentration and PEEP, following a weaning sequence of first reducing oxygen concentration and then reducing PEEP. Tidal volume settings strictly adhere to lung-protective ventilation principles, maintaining 6-8 mL / kg of ideal body weight, with a plateau pressure not exceeding 30 cmH2O. After each adjustment of the ventilation regulation unit parameters, observe for 20 minutes to assess changes in gas exchange and hemodynamics to ensure the safety and effectiveness of the adjustment.

[0060] All automatic adjustment functions in the adjustment execution module are equipped with a manual review mechanism. Important dosage adjustments require confirmation from clinicians before execution, ensuring the system's controllability and safety. The module also records the time, parameter changes, and patient responses of all adjustment operations, providing a complete operation log for clinical decision-making and supporting post-event analysis and quality improvement.

[0061] To verify the clinical effectiveness of the system of this invention, a prospective study was conducted on 60 patients who underwent lung transplantation in the Respiratory and Critical Care Medicine (RICU) of a tertiary hospital between January and December 2024. Patients were randomly divided into an experimental group and a control group, with 30 patients in each group. There were no statistically significant differences in baseline characteristics such as age, sex, primary disease, and preoperative pulmonary artery pressure between the two groups. Postoperatively, patients in the experimental group received cardiopulmonary function management using the system of this invention, while the control group received traditional hemodynamic monitoring and empirical treatment.

[0062] In the experimental group, the multi-parameter acquisition module was activated immediately postoperatively, and cardiopulmonary interaction modeling analysis was performed hourly. Volume strain testing was conducted on postoperative day 1, and individualized hemodynamic goals were established based on the test results. In the experimental group, 18 patients were deemed to have good volume tolerance and received a relatively flexible fluid management strategy, with an infusion volume of (3200±450) mL within 48 hours postoperatively; 7 patients were deemed to have moderate volume tolerance and received a goal-oriented fluid management strategy, with an infusion volume of (2400±350) mL; and 5 patients were deemed to have poor volume tolerance and received a strictly restrictive fluid management strategy, with an infusion volume of (1600±280) mL. The treatment response prediction module generated an individualized treatment plan for each patient, and the execution adjustment module optimized fluid, medication, and ventilation parameters in real time.

[0063] The results showed that the hemodynamic target achievement rate at 48 hours post-operation was 86.7% (26 / 30) in the experimental group, significantly higher than 60.0% (18 / 30) in the control group (P<0.05). The time to achieve target oxygenation index in the experimental group was (18.5±6.2) h, significantly shorter than (32.8±9.5) h in the control group (P<0.01). The incidence of pulmonary edema in the experimental group was 13.3% (4 / 30), significantly lower than 33.3% (10 / 30) in the control group (P<0.05). The duration of mechanical ventilation in the experimental group was (52.3±18.6) h, shorter than (78.5±24.3) h in the control group (P<0.01). The ICU stay in the experimental group was (5.2±1.8) days, which was shorter than that in the control group (7.8±2.5) days, and the difference was statistically significant (P<0.01). There was no significant difference in in-hospital mortality between the two groups, but the incidence of primary graft dysfunction in the experimental group showed a decreasing trend.

[0064] Subgroup analysis showed that the system of this invention provided the most significant benefit to patients with poor volume tolerance. These patients were identified early through cardiopulmonary interaction modeling, and with restrictive fluid management and aggressive pulmonary vasodilation, the incidence of pulmonary edema decreased from 60% in the control group to 20% in the experimental group. Patients with good volume tolerance showed significant improvement in tissue perfusion parameters, accelerated blood lactate clearance, and a reduced incidence of multiple organ dysfunction after adequate fluid resuscitation.

[0065] This embodiment fully demonstrates the clinical value of the system of the present invention in the management of cardiopulmonary function after lung transplantation. Through cardiopulmonary interaction modeling, volume strain testing, individualized target setting, and treatment response prediction, the system achieves accurate cardiopulmonary function assessment and dynamic regulation, significantly improves the hemodynamic stability of patients, reduces the incidence of complications, and shortens the time of mechanical ventilation and ICU stay, which is of great significance for improving the quality of postoperative management of lung transplant patients.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A system for coordinated assessment and regulation of cardiopulmonary volume after lung transplantation, characterized in that... ,include: A multi-parameter acquisition module is used to acquire cardiac parameters, pulmonary function parameters, and hemodynamic parameters of patients after lung transplantation in real time. The cardiac parameters include right ventricular ejection fraction, tricuspid regurgitation velocity, and ventricular wall motion velocity. The pulmonary function parameters include lung compliance, airway resistance, and oxygenation index. The hemodynamic parameters include pulmonary artery pressure, central venous pressure, and stroke volume variability. The cardiopulmonary interaction modeling module, connected to the multi-parameter acquisition module, is used to construct the cardiopulmonary coupling coefficient and pulmonary vascular afterload index based on the cardiac parameters, pulmonary function parameters, and hemodynamic parameters. Based on the cardiopulmonary coupling coefficient and pulmonary vascular afterload index, a cardiopulmonary interaction model reflecting the dynamic relationship between right ventricular function and pulmonary vascular resistance is established. The volume strain testing module, connected to the multi-parameter acquisition module and the cardiopulmonary interaction modeling module, is used to monitor the cardiac output response amplitude and lung compliance change rate during the volume load change process through precisely controlled fluid load challenges, and generate volume tolerance assessment results based on the cardiac output response amplitude and lung compliance change rate. A hemodynamic target setting module, connected to the cardiopulmonary interaction modeling module and the volume strain testing module, is used to determine individualized optimal preload target values, optimal afterload target values, and optimal myocardial contractility target values ​​based on the cardiopulmonary interaction model and volume tolerance assessment results. The treatment response prediction module, connected to the hemodynamic target setting module, is used to simulate the potential impact of different interventions on cardiopulmonary function. These interventions include fluid management protocols, vasoactive drug protocols, and mechanical ventilation parameter adjustment protocols. Treatment recommendations are generated based on the simulation results. The adjustment execution module, connected to the treatment response prediction module, is used to automatically adjust the fluid infusion rate, vasoactive drug dosage, and ventilator parameters according to the treatment recommendations, and to monitor the adjustment effect in real time.

2. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 1, characterized in that... The multi-parameter acquisition module includes a cardiac function monitoring unit, a pulmonary function monitoring unit, and a hemodynamic monitoring unit; The cardiac function monitoring unit is used to acquire the right ventricular ejection fraction, tricuspid regurgitation velocity, and ventricular wall motion velocity via echocardiography. The lung function monitoring unit is used to collect lung compliance, airway resistance, and oxygenation index via respiratory mechanics monitoring equipment; The hemodynamic monitoring unit is used to collect pulmonary artery pressure, central venous pressure, and stroke volume variation rate through a pulmonary artery catheter and arterial pressure waveform analysis device.

3. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 1, characterized in that... The cardiopulmonary interaction modeling module includes a coupling coefficient calculation unit, an afterload index calculation unit, and an interaction model construction unit. The coupling coefficient calculation unit is used to determine the cardiopulmonary coupling coefficient based on the right ventricular ejection fraction and lung compliance; The afterload index calculation unit is used to determine the pulmonary vascular afterload index based on the pulmonary artery pressure and the stroke volume variation rate; The interactive model construction unit is used to establish the cardiopulmonary interactive model based on the cardiopulmonary coupling coefficient and the pulmonary vascular afterload index.

4. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 3, characterized in that... The coupling coefficient calculation unit is specifically used for: obtaining the baseline and real-time values ​​of the right ventricular ejection fraction and calculating the rate of change of the right ventricular ejection fraction; obtaining the baseline and real-time values ​​of the lung compliance and calculating the rate of change of the lung compliance; and determining the cardiopulmonary coupling coefficient based on the rate of change of the right ventricular ejection fraction and the rate of change of the lung compliance.

5. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 3, characterized in that... The afterload index calculation unit is specifically used to: obtain the average value, systolic pressure and diastolic pressure of the pulmonary artery pressure; obtain the stroke volume variation rate; and determine the pulmonary vascular afterload index based on the average value, systolic pressure, diastolic pressure and stroke volume variation rate of the pulmonary artery pressure.

6. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 1, characterized in that... The capacity strain testing module includes a load challenge unit, a response monitoring unit, and a tolerance assessment unit. The load challenge unit is used to implement precisely controlled liquid load challenges, infusing liquid at a preset rate within a preset time period; The response monitoring unit is used to continuously monitor the cardiac output response amplitude and the rate of change in lung compliance during the fluid load challenge. The tolerance assessment unit is used to generate the volume tolerance assessment result based on the cardiac output response amplitude and the rate of change in lung compliance.

7. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 6, characterized in that... The tolerance assessment unit is specifically used to: determine good volume tolerance if the cardiac output response amplitude exceeds a first threshold and the lung compliance change rate is lower than a second threshold; determine poor volume tolerance if the cardiac output response amplitude is lower than the first threshold and the lung compliance change rate exceeds the second threshold; and determine moderate volume tolerance if both the cardiac output response amplitude and the lung compliance change rate are within the threshold range.

8. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 1, characterized in that... The hemodynamic target setting module includes a preload target calculation unit, an afterload target calculation unit, and a contractile force target calculation unit; The preload target calculation unit is used to determine the optimal preload target value based on the cardiopulmonary interaction model and the volume tolerance assessment results. The afterload target calculation unit is used to determine the optimal afterload target value based on the cardiopulmonary interaction model and the pulmonary vascular afterload index; The contractility target calculation unit is used to determine the optimal myocardial contractility target value based on the cardiopulmonary interaction model and the right ventricular ejection fraction.

9. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 1, characterized in that... The treatment response prediction module includes an intervention simulation unit, an effect prediction unit, and a treatment plan optimization unit. The intervention simulation unit is used to simulate the effects of different interventions on cardiopulmonary function. The effect prediction unit is used to predict changes in cardiac output, lung compliance, and oxygenation index after each intervention measure is implemented, based on the cardiopulmonary interaction model. The scheme optimization unit is used to select the best intervention scheme and generate the treatment recommendation based on the prediction results.

10. The post-lung transplant cardiopulmonary volume co-assessment and regulation system according to claim 1, characterized in that... The regulation execution module includes a fluid regulation unit, a drug regulation unit, and a ventilation regulation unit; The fluid regulation unit is used to automatically adjust the fluid infusion rate according to the treatment recommendations; The drug adjustment unit is used to automatically adjust the dosage of the vasoactive drug according to the treatment recommendations; The ventilation regulation unit is used to automatically adjust the ventilator parameters according to the treatment recommendations. The ventilator parameters include tidal volume, positive end-expiratory pressure, and inhaled oxygen concentration.

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