CN115831359A - Dialysis state adjusting method and system based on multi-physiological sign information analysis - Google Patents
Dialysis state adjusting method and system based on multi-physiological sign information analysis Download PDFInfo
- Publication number
- CN115831359A CN115831359A CN202211424042.9A CN202211424042A CN115831359A CN 115831359 A CN115831359 A CN 115831359A CN 202211424042 A CN202211424042 A CN 202211424042A CN 115831359 A CN115831359 A CN 115831359A
- Authority
- CN
- China
- Prior art keywords
- dialysis
- sign information
- time
- preset
- physiological sign
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- External Artificial Organs (AREA)
Abstract
The invention discloses a dialysis state adjusting method and system based on multi-physiological sign information analysis, which relate to the technical field of dialysis adjustment and comprise the following steps: acquiring a real-time physiological sign information set of a target through a non-invasive sensor; synchronizing the physiological sign information according to the information acquisition interval; analyzing each physiological sign information after the synchronization processing through a neural network trained unsupervised based on the classification label to obtain each complication prediction evaluation; calculating and acquiring the real-time urea clearance of a target according to dialysis parameters obtained by the detection of the dialysis machine; and adjusting the dialysis state under a preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and a preset interval. According to the method, based on the urea clearance rate of the obtained target and the prediction of each complication, intelligent dialysis adjustment can be performed in advance according to the actual dialysis condition of the target, and the dependence on medical care personnel is reduced.
Description
Technical Field
The invention relates to the technical field of dialysis adjustment, in particular to a dialysis state adjustment method and system based on multi-physiological sign information analysis.
Background
A hemodialysis instrument, also called a hemodialysis instrument, is a treatment instrument which is most widely applied in hemodialysis treatment and mainly comprises a blood pump, a dialyzer and an extracorporeal circulation monitoring device. In recent years, with the exponential increase in the number of patients with end-stage renal disease, the supply and demand of public hemodialysis machines are seriously unbalanced. In addition, outbreaks of disastrous accidents such as epidemic situations and earthquakes prevent the patients with maintenance hemodialysis from going to medical institutions to receive treatment. The household hemodialysis instrument can not only relieve the resource shortage problem of public medical institutions, but also enable patients to still carry out hemodialysis treatment when a sudden disaster happens. Therefore, the development of home hemodialysis instruments is urgently needed. One of the safety performance of the home hemodialysis instrument is whether the abnormal condition can be detected or predicted in time and an optimal response is made.
Disclosure of Invention
In order to enable a maintenance hemodialysis patient to predict complications in time when using a household hemodialysis instrument and simultaneously make a timely optimized response according to a dialysis effect without external intervention, the invention provides a dialysis state adjustment method based on multi-physiological sign information analysis, which comprises the following steps:
s1: acquiring a real-time physiological sign information set of a target through a non-invasive sensor;
s2: synchronizing the physiological sign information according to the information acquisition interval;
s3: analyzing the physiological sign information after the synchronization processing through a neural network based on unsupervised training to obtain the prediction evaluation of each complication;
s4: calculating and acquiring the real-time urea removal rate of a target according to dialysis parameters obtained by detection of a dialyzer;
s5: and adjusting the dialysis state under a preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and a preset interval.
Further, in the step S2, the synchronization process is expressed as the following formula:
in the formula, B i,t For physiological sign information i at t 1 Data information collected at any moment
The data information at the time t obtained after the synchronization processing,
is t 1 The unit time change rate of the physiological sign information i at the moment, and delta t is the unit time change rate of the current physiological sign information i at t 1 The time is compared with the time advance difference of the reference physiological sign information acquisition time t.
Further, in the step S3, after obtaining the prediction evaluation of the complication, the method further includes the steps of:
s31: the complication prediction assessment is converted to boolean values by a hysteresis function.
Further, in the step S4, the urea removal rate is obtained as follows:
wherein spKt/V is urea clearance, C 0 For the pre-dialysis BUN concentration, C t The post-dialysis BUN concentration, t the dialysis time, V UF DW is dry body weight, as ultrafiltration volume.
Further, in the step S5, the dialysis state adjustment under the preset judgment criterion specifically includes:
when the Boolean values of various complications in a preset time period are zero and the urea clearance is in a preset interval, dialyzing by preset parameters before dialysis;
when the Boolean values in the preset time period are zero and the urea clearance rate is lower than a preset interval, increasing the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is one, reducing the temperature of the dialysate and the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is zero, the Boolean value of the dialysis unbalance syndrome is one, and the urea clearance rate is higher than a preset interval, the blood flow is reduced, the ultrafiltration rate is reduced, and the dialysis time is shortened for dialysis;
when the Boolean value of the hypotension risk is one or the Boolean value of the dialysis imbalance syndrome is one and exceeds the preset time, stopping dialysis and sending out an HMI alarm.
The invention also provides a dialysis state adjusting system based on multi-physiological sign information analysis, which comprises:
the non-invasive sensor is used for acquiring a real-time physiological sign information set of a target;
the synchronization processing unit is used for carrying out synchronization processing on the physiological sign information according to the information acquisition interval;
the complication prediction unit is used for analyzing the physiological sign information after the synchronization processing through a neural network based on unsupervised training to obtain the prediction evaluation of each complication;
the clearance calculation unit is used for calculating and acquiring the real-time urea clearance of the target according to the dialysis parameters detected and acquired by the dialyzer;
and the dialysis adjusting unit is used for adjusting the dialysis state under the preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and the preset interval.
Further, in the synchronization processing unit, synchronization processing is expressed by the following formula:
in the formula, bi ,t For physiological sign information i at t 1 Data information collected at any moment
The data information at the time t obtained after the synchronization processing,
is t 1 The unit time change rate of the physiological sign information i at the moment, and delta t is the current physiological sign information i at t 1 The time is compared with the time advance difference of the reference physiological sign information acquisition time t.
Further, the complication prediction unit further comprises:
and the Boolean conversion unit is used for converting the complication prediction evaluation into a Boolean value through a hysteresis function after the complication prediction evaluation is obtained.
Further, in the clearance calculation unit, the urea clearance is obtained as follows:
wherein spKt/V is the urea clearance, C 0 The concentration of BUN before dialysis, C t The post-dialysis BUN concentration, t the dialysis time, V UF DW is dry body weight.
Further, in the dialysis adjustment unit, the adjustment of the dialysis state under the preset judgment criterion specifically comprises:
when the Boolean values of various complications in a preset time period are zero and the urea clearance is in a preset interval, dialyzing by preset parameters before dialysis;
when the Boolean values in the preset time period are zero and the urea clearance rate is lower than a preset interval, increasing the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is one, reducing the temperature of the dialysate and the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is zero, the Boolean value of the dialysis unbalance syndrome is one, and the urea clearance is higher than the preset interval, the blood flow is reduced, the ultrafiltration rate is reduced, and the dialysis time is shortened for dialysis;
when the Boolean value of the hypotension risk is one or the Boolean value of the dialysis imbalance syndrome is one and exceeds the preset time, stopping dialysis and sending out an HMI alarm.
Compared with the prior art, the invention at least has the following beneficial effects:
(1) According to the dialysis state adjusting method and system based on multi-physiological sign information analysis, intelligent dialysis adjustment can be performed in advance according to the actual dialysis condition of the target based on the urea removal rate of the target and the prediction of each complication, so that a dialyzer applying the method can meet the household use requirement, and the dependence on medical care personnel is greatly reduced;
(2) The advanced dialysis state adjustment is carried out through the prediction of the target dialysis condition, so that the occurrence of dialysis complications can be reduced, and the safety of the household dialysis machine is ensured to a great extent.
Drawings
FIG. 1 is a diagram of steps of a dialysis status adjustment method based on multi-physiological sign information analysis;
FIG. 2 is a block diagram of a dialysis status adjustment system based on multiple physiological sign information analysis;
FIG. 3 shows the difference diagrams of the BP, HR and RBV acquisition time sequences;
FIG. 4 is a schematic representation of the Boolean value step by step of the hysteresis function;
FIG. 5 is a logic diagram of a predetermined decision criterion.
Detailed Description
The following are specific embodiments of the present invention and are further described with reference to the drawings, but the present invention is not limited to these embodiments.
Example one
In order to promote the home hemodialysis instrument and provide safe and reliable use effect in the use process, as shown in fig. 1, the invention provides a dialysis state adjusting method based on multi-physiological sign information analysis, which comprises the following steps:
s1: acquiring a real-time physiological sign information set of a target through a non-invasive sensor;
s2: synchronizing the physiological sign information according to the information acquisition interval;
s3: analyzing the synchronized physiological sign information through a neural network based on unsupervised training to obtain each complication prediction evaluation;
s4: calculating and acquiring the real-time urea clearance of a target according to dialysis parameters obtained by the detection of a dialyzer;
s5: and adjusting the dialysis state under a preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and a preset interval.
First, in order to achieve the use of a hemodialysis machine without medical staff, complications must be reduced during the use of the hemodialysis machine. And compared with the hemodialysis instrument used under the condition of medical care, the household hemodialysis instrument lacks the adjustment of the dialysis state of medical care personnel according to the actual physical sign state of a target. Therefore, to enable the hemodialysis instrument to reduce the occurrence of complications in the household process, corresponding physiological sign information needs to be acquired, and here, the target real-time physiological sign information is acquired through a non-invasive sensor. The specific physiological sign information includes parameter information related to occurrence of dialysis complications, such as blood pressure BP, heart rate HR, blood volume RBV, blood temperature, and blood flow.
The acquisition time of various physiological sign information is inconsistent due to different acquisition modes and characteristics of the various physiological sign information, and at this time, if the physiological sign information is used for carrying out complication prediction analysis, the physiological sign information needs to be synchronized to the same acquisition time. Here, considering that the sign information acquisition interval is short, and the change rate does not change much in a short time, under the assumption of a constant change rate, the following synchronization processing formula can be constructed:
in the formula, bi ,t For physiological sign information i at t 1 Data information collected at any moment
The data information at the time t obtained after the synchronization processing,
is t 1 The unit time change rate of the physiological sign information i at the moment, and delta t is the unit time change rate of the current physiological sign information i at t 1 The time is compared with the time advance difference of the reference physiological sign information acquisition time t.
As shown in FIG. 3, taking BP, HR, and RBV as examples, HR data is received once at time t, and RBV measurement time is t 1 ＝t-Δt 1 -Δt 2 BP measurement time t 2 ＝t-Δt 2 . Three physiological sign information need to be synchronized to the same time (t) for the accuracy of the assessment. Predicting BP and RBV based on a constant change rate model, namely, the change rate is not changed within a sampling time interval delta t, and the prediction calculation formula is as follows:
after obtaining the physiological sign information after the synchronization treatment, the predictive assessment of the dialysis complications can be carried out according to the information. Here, the method actually includes the synchronous prediction of multiple types of complication risk assessment models, and since the prediction of related complications is supported by the corresponding prior art, only the hypotension risk assessment model is taken as an example here, and the risk coefficient of target hypotension occurring in the dialysis process is predicted by analyzing the real-time physiological sign information, dialysis personalized parameters, medication conditions and patient basic information in the dialysis process of the patient. For the consideration that risk assessment needs to be based on historical information, the model employs an RNN (recurrent neural network) network. Meanwhile, GRU (gated cycle unit) is adopted to solve the problem of RNN gradient disappearance at the time of practical application, and the method has the advantage of saving calculation power compared with LSTM (long-short-term neural network). Meanwhile, considering the serious unbalance of positive and negative samples of real data, the neural network training effect is not good, so that an unsupervised learning mode is adopted in the training process to increase the accuracy of model prediction after the training is finished.
In the early training process of the model, the training data complete set is randomly divided into a training set (70%), a verification set (5%), a calibration set (5%) and a test set (20%). And optimizing and evaluating the trained model based on the PR curve and the ROC curve. And the characteristic weight can be reflected through the model performance change after the characteristics are deleted, so that the characteristic weight is used as the interpretability of the neural network, and the reasonability and the controllability of the RNN model are guaranteed.
After the prediction evaluation of each complication is obtained through the trained model, the risk coefficient a is used i In the form of a map at [0,1 ]]In the interval, the magnitude of the risk coefficient reflects the magnitude of the probability of occurrence of the corresponding complication. In order to prevent the decision from changing frequently, the invention also converts the risk coefficient into a Boolean value b by using a hysteresis function i (0 low risk or 1 high risk). Hysteresis function see FIG. 4, when a i A is greater than or equal to u When b is greater than i Is 1 when a i A is less than or equal to l When b is greater than i Equal to 0.
After various types of concurrent occurrence risk assessment are obtained, the urea clearance of a patient in the dialysis process needs to be considered, because the dialysis mainly filters urea in blood, the aim of considering the occurrence of complications and whether the dialysis effect reaches the standard needs to be fully considered. For this reason, in step S4, a calculation of the urea removal rate is required, and specifically, the urea removal rate is obtained as follows:
wherein spKt/V is urea clearance, C 0 For the pre-dialysis BUN concentration, C t The post-dialysis BUN concentration, t the dialysis time, V UF DW is dry body weight, as ultrafiltration volume. Wherein V UF DW is a patient-specific parameter.
After the risk assessment and urea clearance of each complication are obtained, the dialysis state can be adjusted according to preset judgment criteria, as shown in fig. 5, the preset judgment criteria are specifically as follows:
c0: when the Boolean values of various complications in a preset time period are zero and the urea clearance is in a preset interval, dialyzing by preset parameters before dialysis; (Normal dialysis)
c1: when the Boolean values in the preset time period are zero and the urea clearance rate is lower than a preset interval, increasing the ultrafiltration rate for dialysis; (high efficiency dialysis)
c2: when the Boolean value of the hypotension risk is one, reducing the temperature of the dialysate and the ultrafiltration rate for dialysis; (Low temperature dialysis)
c3: when the Boolean value of the hypotension risk is zero, the Boolean value of the dialysis unbalance syndrome is one, and the urea clearance rate is higher than a preset interval, the blood flow is reduced, the ultrafiltration rate is reduced, and the dialysis time is shortened for dialysis; (Low efficiency dialysis)
c4: when the boolean value of the hypotension risk is one or the boolean value of the dialysis imbalance syndrome is one and exceeds a preset time, the dialysis is stopped and the HMI alarm is issued (and the nearest medical institution is called). (stop dialysis)
In a preferred embodiment, additionally considered parameters stdKt/V (standard urea clearance rate, long-term index based on past treatment data of the patient) and URR (urea clearance rate) of arteriovenous fistula patients and central venous catheter patients in the hemodialysis process are considered, and the parameters are dialysis adequacy indexes. Wherein, for arteriovenous internal fistula patients, the eKt/V calculation formula is as follows:
eKt/V＝spKt/V-(0.6×spKt/V)/T+0.03
for central venous catheter patients, the eKt/V calculation formula is:
eKt/V＝spKt/V-(0.47×spKt/V)/T-0.02
accordingly, their stdKt/V calculation formula is:
wherein F is the number of dialysis cycles per week, kru is the residual renal function urea clearance (mL/min), U f The ultrafiltration volume (L/min) and V are the urea distribution volume (L).
And the URR calculation formula is:
according to the two newly added parameters, when the dialysis state is actually adjusted:
in case c3, it is also necessary to consider whether stdKt/V and URR are too high, and to perform dialysis by reducing blood flow, ultrafiltration rate and dialysis time when either is too high.
Example two
For better understanding of the technical content of the present invention, the present implementation illustrates the present invention in the form of a system structure, as shown in fig. 2, a dialysis status adjustment system based on multiple physiological sign information analysis, comprising:
the non-invasive sensor is used for acquiring a real-time physiological sign information set of a target;
the synchronization processing unit is used for carrying out synchronization processing on the physiological sign information according to the information acquisition interval;
the complication prediction unit is used for analyzing the physiological sign information after the synchronization processing through a neural network based on unsupervised training to obtain the prediction evaluation of each complication;
the clearance calculation unit is used for calculating and acquiring the real-time urea clearance of a target according to the dialysis parameters detected by the dialyzer;
and the dialysis adjusting unit is used for adjusting the dialysis state under the preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and the preset interval.
Further, in the synchronization processing unit, the synchronization processing is expressed as the following formula:
in the formula, B i,t For physiological sign information i at t 1 Data information collected at any moment
The data information at the time t obtained after the synchronization processing,
is t 1 The unit time change rate of the physiological sign information i at the moment, and delta t is the current physiological sign information i at t 1 The time is compared with the time advance difference of the reference physiological sign information acquisition time t.
Further, the complication prediction unit further comprises:
and the Boolean conversion unit is used for converting the complication prediction evaluation into a Boolean value through a hysteresis function after the complication prediction evaluation is obtained.
Further, in the clearance calculation unit, the urea clearance is obtained as follows:
wherein spKt/V is urea clearance, C 0 To penetrate throughBUN concentration before analysis, C t The BUN concentration after dialysis, t is the dialysis time, V UF DW is dry body weight, as ultrafiltration volume.
Further, in the dialysis adjustment unit, the adjustment of the dialysis state under the preset judgment criterion specifically includes:
when the Boolean values of various complications in a preset time period are zero and the urea clearance is in a preset interval, dialyzing by preset parameters before dialysis;
when the Boolean values in the preset time period are zero and the urea clearance rate is lower than a preset interval, increasing the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is one, reducing the temperature of the dialysate and the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is zero, the Boolean value of the dialysis unbalance syndrome is one, and the urea clearance rate is higher than a preset interval, the blood flow is reduced, the ultrafiltration rate is reduced, and the dialysis time is shortened for dialysis;
when the Boolean value of the hypotension risk is one or the Boolean value of the dialysis imbalance syndrome is one and exceeds the preset time, stopping dialysis and sending out an HMI alarm.
In conclusion, the dialysis state adjustment method and system based on multi-physiological sign information analysis, provided by the invention, can perform intelligent dialysis adjustment in advance according to the actual target dialysis condition based on the urea clearance rate of the obtained target and the prediction of each complication, so that a dialyzer applying the method can meet the household use requirement, and the dependence on medical care personnel is greatly reduced.
The advanced dialysis state adjustment is carried out through the prediction of the target dialysis condition, so that the occurrence of dialysis complications can be reduced, and the safety of the household dialysis machine is ensured to a great extent.
It should be noted that all directional indicators (such as up, down, left, right, front, back \8230;) in the embodiments of the present invention are only used to explain the relative positional relationship between the components, the motion situation, etc. in a specific posture (as shown in the attached drawings), and if the specific posture is changed, the directional indicator is changed accordingly.
Furthermore, descriptions of the present invention as related to "first," "second," "a," etc. are for descriptive purposes only and are not to be construed as indicating or implying relative importance or to imply that the number of technical features indicated is indicative. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "connected," "secured," and the like are to be construed broadly, and for example, "secured" may be a fixed connection, a removable connection, or an integral part; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the technical solutions in the embodiments of the present invention may be combined with each other, but it must be based on the realization of those skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination of technical solutions should not be considered to exist, and is not within the protection scope of the present invention.
Claims (10)
1. A dialysis state adjustment method based on multi-physiological sign information analysis is characterized by comprising the following steps:
s1: acquiring a real-time physiological sign information set of a target through a non-invasive sensor;
s2: synchronizing the physiological sign information according to the information acquisition interval;
s3: analyzing the physiological sign information after the synchronization processing through a neural network based on unsupervised training to obtain the prediction evaluation of each complication;
s4: calculating and acquiring the real-time urea clearance of a target according to dialysis parameters obtained by the detection of a dialyzer;
s5: and adjusting the dialysis state under a preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and a preset interval.
2. The method for adjusting dialysis status based on multi-physiological-sign information analysis of claim 1, wherein in the step S2, the synchronization process is expressed as the following formula:
in the formula, B i,t For physiological sign information i at t 1 Data information collected at any moment
The data information at the time t obtained after the synchronization processing,
is t 1 The unit time change rate of the physiological sign information i at the moment, and delta t is the unit time change rate of the current physiological sign information i at t 1 The time is compared with the time advance difference of the reference physiological sign information acquisition time t.
3. The dialysis status adjustment method based on multi-physiological-sign information analysis of claim 1, wherein in the step S3, after obtaining the complication prediction assessment, the method further comprises the steps of:
s31: the complication prediction assessment is converted to boolean values by a hysteresis function.
4. The method for adjusting dialysis status based on multi-physiological-sign information analysis of claim 1, wherein in the step S4, the urea clearance is obtained according to the following formula:
wherein spKt/V is urea clearance, C 0 The concentration of BUN before dialysis, C t The post-dialysis BUN concentration, t the dialysis time, V UF DW is dry body weight, as ultrafiltration volume.
5. The method for adjusting dialysis state based on multi-physiological-sign information analysis according to claim 3, wherein in the step S5, the adjustment of dialysis state under the preset judgment criterion specifically comprises:
when the Boolean values of various complications within a preset time period are zero and the urea clearance is within a preset interval, dialyzing by preset parameters before dialysis;
when the Boolean values in the preset time period are zero and the urea clearance rate is lower than a preset interval, increasing the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is one, reducing the temperature of the dialysate and the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is zero, the Boolean value of the dialysis unbalance syndrome is one, and the urea clearance rate is higher than a preset interval, the blood flow is reduced, the ultrafiltration rate is reduced, and the dialysis time is shortened for dialysis;
when the Boolean value of the hypotension risk is one or the Boolean value of the dialysis imbalance syndrome is one and exceeds the preset time, stopping dialysis and sending out an HMI alarm.
6. A dialysis status adjustment system based on multi-physiological sign information analysis, comprising:
the non-invasive sensor is used for acquiring a real-time physiological sign information set of a target;
the synchronization processing unit is used for carrying out synchronization processing on the physiological sign information according to the information acquisition interval;
the complication prediction unit is used for analyzing the physiological sign information after the synchronization processing through a neural network based on unsupervised training to obtain the prediction evaluation of each complication;
the clearance calculation unit is used for calculating and acquiring the real-time urea clearance of the target according to the dialysis parameters detected and acquired by the dialyzer;
and the dialysis adjusting unit is used for adjusting the dialysis state under a preset judgment criterion according to the evaluation grade of the complication prediction evaluation and the relation between the urea clearance and a preset interval.
7. The system of claim 6, wherein the synchronization process unit is configured to perform the synchronization process according to the following formula:
in the formula, B i,t For physiological sign information i at t 1 Data information collected at any moment
The data information at the time t obtained after the synchronization processing,
is t 1 The unit time change rate of the physiological sign information i at the moment, and delta t is the unit time change rate of the current physiological sign information i at t 1 The time is compared with the time advance difference of the reference physiological sign information acquisition time t.
8. The dialysis state adjustment system based on multi-physiological-sign information analysis of claim 6, wherein the complication prediction unit further comprises:
and the Boolean conversion unit is used for converting the complication prediction evaluation into a Boolean value through a hysteresis function after the complication prediction evaluation is obtained.
9. The system of claim 6, wherein the urea clearance calculation unit obtains the urea clearance according to the following formula:
wherein spKt/V is urea clearance, C 0 For the pre-dialysis BUN concentration, C t The post-dialysis BUN concentration, t the dialysis time, V UF DW is dry body weight, as ultrafiltration volume.
10. The system according to claim 8, wherein the dialysis adjustment unit adjusts the dialysis status under a preset criterion specifically by:
when the Boolean values of various complications in a preset time period are zero and the urea clearance is in a preset interval, dialyzing by preset parameters before dialysis;
when the Boolean values are zero in the preset time period and the urea clearance is lower than the preset interval, increasing the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is one, reducing the temperature of the dialysate and the ultrafiltration rate for dialysis;
when the Boolean value of the hypotension risk is zero, the Boolean value of the dialysis unbalance syndrome is one, and the urea clearance rate is higher than a preset interval, the blood flow is reduced, the ultrafiltration rate is reduced, and the dialysis time is shortened for dialysis;
when the Boolean value of the hypotension risk is one or the Boolean value of the dialysis imbalance syndrome is one and exceeds the preset time, stopping dialysis and sending out an HMI alarm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211424042.9A CN115831359A (en) | 2022-11-15 | 2022-11-15 | Dialysis state adjusting method and system based on multi-physiological sign information analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211424042.9A CN115831359A (en) | 2022-11-15 | 2022-11-15 | Dialysis state adjusting method and system based on multi-physiological sign information analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115831359A true CN115831359A (en) | 2023-03-21 |
Family
ID=85528095
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211424042.9A Pending CN115831359A (en) | 2022-11-15 | 2022-11-15 | Dialysis state adjusting method and system based on multi-physiological sign information analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115831359A (en) |
-
2022
- 2022-11-15 CN CN202211424042.9A patent/CN115831359A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP2019150651A (en) | Monitoring body fluid volume for patients with renal disease | |
| JP2014518688A5 (en) | ||
| US8303807B2 (en) | Dialyser with measuring devices for monitoring the blood pressure, method of determining the blood pressure and a storage medium for use in a dialyser | |
| EP2519280A1 (en) | Method and device for detecting a configuration of withdrawal and return devices | |
| EP2519145A1 (en) | Monitoring a property of the cardiovascular system of a subject | |
| EP0027470A1 (en) | Computer-controlled medical care system. | |
| WO2010039876A1 (en) | Physiological characteristic determination for a medical device user | |
| US20240082472A1 (en) | Parameter Monitoring in Medical Treatment Systems | |
| CN108986419A (en) | A kind of data alarm method for haemodialysis | |
| CN116682566B (en) | Hemodialysis data processing method and system | |
| CN110151153A (en) | Fuzzy logic | |
| CN209884874U (en) | Hemodialysis intelligent service system | |
| CN110124135A (en) | A kind of haemodialysis monitoring nursing control system and method based on Internet of Things | |
| CN110064086A (en) | Ultrafiltration monitoring method in a kind of blood dialysis | |
| CN110152087A (en) | A kind of monitoring method of blood dialysis | |
| CN115831359A (en) | Dialysis state adjusting method and system based on multi-physiological sign information analysis | |
| US20220347363A1 (en) | Correlation between intraperitoneal pressure ("ipp") measurements and patient intraperitoneal volume ("ipv") methods, apparatuses, and systems | |
| Kramer et al. | Clinical experience with continuously monitored fluid balance in automatic hemofiltration | |
| CN112354033A (en) | Hemodialysis information management system, hemodialysis information management method, hemodialysis information management computer equipment and hemodialysis information management storage medium | |
| CN113080906A (en) | Method for improving accuracy and efficiency of blood pressure measurement | |
| CN115297910A (en) | Ultrafiltration control in extracorporeal blood treatment | |
| US20220313879A1 (en) | Calculation device and dialysis apparatus | |
| CN113577424B (en) | Waste liquid discharge method for blood purification apparatus, and storage medium | |
| CN116077765A (en) | Infusion system and storage medium | |
| WO2023218200A1 (en) | Fluid delivery system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |