Intelligent input and output calculation device, equipment, medium and program product

Abstract

The embodiment of the invention provides an intelligent in-and-out amount calculating device, and relates to the technical field of patient liquid in-and-out amount recording. The device comprises a parameter acquisition module for acquiring prediction parameters of a to-be-detected sample; the risk prediction module inputs the prediction parameters into a capacity load risk prediction model and outputs a risk value; outputting a suggestion whether the first to-be-fed intake needs to be adjusted or not according to the risk value; and the food water content identification module is used for identifying and analyzing the water content of the food to be eaten, calculating a second food intake, and adjusting the second food intake according to the first food intake, so that the second food intake is matched with the first food intake. The method can accurately and efficiently record and calculate the liquid intake and discharge (inlet and outlet) of the patient, and is of great significance for evaluating the liquid balance state and water electrolyte balance of the patient and formulating a treatment scheme.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of patient fluid intake and output recording, and more particularly to an intelligent intake and output calculation device. BACKGROUND

[0002] Fluid volume management is an important part of the treatment and management of chronic kidney disease and chronic heart failure patients. It is a skill that clinical medical staff and chronic kidney disease and chronic heart failure patients need to master to record intake and output. Currently, in clinical practice, the intake and output of patients is recorded by the patient, and the daily food intake and estimated amount and daily urine output are recorded by the nurse at 14:00, 20:00 and 6:00 in the morning. The food water content table provided by the nutrition room (such as Figure 4 ) is used for conversion, and the daily intake and output of patients who need to record intake and output (regular bowel movements are not recorded) are calculated.

[0003] For example, patient A eats 1 bag of milk 250ml, 1 egg (water content 25ml), and a piece of bread (water content 25ml) in the morning; eats 1 steamed bun (water content 30ml), a dish (1 dish is determined by the catering staff, and the amount is the amount, regardless of weight) (water content 200ml); eats two pounds of rice (usually when the catering staff is on duty, the catering staff will follow the regulations of the nutrition room, and the amount of 1 pound of rice is given to the patient) (water content 200ml), a dish (water content 200), and an apple (water content 84ml). The patient records the daily diet and water intake on his own intake and output record paper, and the nurse asks and calculates the water content every day according to the above time points and enters the data into the computer.

[0004] The above process is not accurate and has individual differences, and the amount recorded by each patient and the conversion by the nurse are different, and standardization has not been achieved, and there are some problems in the management of intake and output. SUMMARY

[0005] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides an intelligent intake and output calculation device for accurately and efficiently recording and calculating the liquid intake and output of patients (intake and output), which is of great significance for evaluating the liquid balance state of patients, water and electrolyte balance, and formulating treatment plans.

[0006] The present application discloses an intelligent intake and output calculation device, which comprises: The parameter acquisition module acquires the prediction parameters of the to-be-detected sample, and the prediction parameters include age, diagnosis result, hemodialysis, admission weight, whether the body weight has not decreased for more than 2 consecutive days, degree of edema, creatinine value, hemoglobin, albumin, sodium urine peptide, medication, diuretic metabolism, whether combined with diabetes, and whether combined with heart failure. a risk prediction module configured to input the prediction parameter into a volume load risk prediction model, and output a risk value; and output a suggestion of whether the first to-be-eaten intake amount needs to be adjusted according to the risk value; a food water content identification module configured to identify and analyze a water content of the to-be-eaten food, calculate a second to-be-eaten intake amount, and adjust the second to-be-eaten intake amount according to the first to-be-eaten intake amount so as to match the two.

[0007] In some embodiments, the medication of the medication situation includes immunosuppressants and hormones.

[0008] In some embodiments, the volume load risk prediction model is: Y=X1*a1+X2*a2+X3*a3+X4*a4+X5*a5+X6*a6+X7*a7+X8*a8+X9*a9+X10*a10+X11*a11+X12*a12+X13*a13+X14*a14+X15*a15; wherein a1 to a15 are coefficients, X1 is age, X2 is diagnosis result, X3 is hemodialysis, X4 is admission weight, X5 is whether the weight has not decreased for more than 2 consecutive days, X6 is edema degree, X7 is creatinine value, X8 is hemoglobin, X9 is albumin, X10 is sodium urine peptide, X11 is immunosuppressants, X12 is hormones, X13 is diuretic metabolism, X14 is whether combined with diabetes, and X15 is combined with heart failure.

[0009] In some embodiments, the diagnosis result includes nephrotic syndrome, chronic glomerulonephritis, AKI, and rapidly progressive glomerulonephritis.

[0010] In some embodiments, the device further includes a food increase / decrease module configured to recalculate the water content of the eaten food according to the second to-be-eaten intake amount according to whether there is surplus or deficiency of the to-be-eaten food.

[0011] In some embodiments, when there is surplus of the to-be-eaten food, the water content of the surplus food is calculated, the difference between the second to-be-eaten intake amount and the water content of the surplus food is calculated to obtain the water content of the eaten food.

[0012] In some embodiments, when there is deficiency of the to-be-eaten food, the water content of the newly added food is calculated, the total amount of the second to-be-eaten intake amount and the water content of the newly added food is calculated to obtain the water content of the eaten food.

[0013] In some embodiments, the device further comprises a reasonable amount judgment module for calculating an absolute value of a difference between the water content of the food eaten and the first amount of food to be eaten, and judging whether the amount of the sample to be detected is reasonable according to the result of the difference; outputting a result that the amount of the sample to be detected is reasonable when the absolute value is greater than a first threshold value; and outputting a result that the amount of the sample to be detected is unreasonable when the absolute value is less than the first threshold value.

[0014] In some embodiments, the suggestion further comprises adjusting the medication regimen or the medication route, and the medication route is intravenous or oral.

[0015] In some embodiments, the degree of edema includes mild, moderate and severe.

[0016] The present application has the following beneficial effects: The present application innovatively discloses an intelligent intake and output amount calculation device, constructs a risk prediction model according to key prediction parameters, and outputs a suggestion on whether the food intake needs to be adjusted according to the risk value result; and uses a food water content recognition module with AI function to quickly recognize the water content of the food to be eaten, so as to calculate the water content of the food to be eaten, i.e. the second amount of food to be eaten, adjust the second amount of food to be eaten according to the first amount of food to be eaten, increase or decrease the food, make the intake and output amount record more accurate, and provide a basis for adjusting the clinical treatment regimen. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0018] Figure 1 is a schematic diagram of the intelligent intake and output amount calculation device provided by the embodiments of the present application; Figure 2 is a specific analysis table of prediction parameters provided by the embodiments of the present application; Figure 3 is a nomogram of the prediction model provided by the embodiments of the present application; Figure 4 is a method for converting food water content currently used in the nutrition room in the clinic. DETAILED DESCRIPTION

[0019] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings of the embodiments of the present application.

[0020] In some of the flow diagrams described in this specification and the accompanying drawings, multiple operations are described in a particular order. However, it should be understood that, unless otherwise specifically noted, the operations can be performed in any order, or in parallel, and that the sequence of operations is not necessarily required to achieve the described results. Additionally, some of the flow diagrams can include more or fewer operations than those depicted and described. Further, these operations can be performed in serial, in parallel, or in some other order as can be useful in one implementation. It will further be appreciated that the descriptions used herein are provided to illustrate the technologies described in this patent document and are not meant to limit or restrict the scope of the technologies described in this patent document to the examples provided.

[0021] The technical solutions in the embodiments of the present application will be clearly and completely described in connection with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0022] Figure 1 Figure 1 is a schematic diagram of an intelligent access amount calculation device provided by an embodiment of the present application. Specifically, the method comprises: The parameter acquisition module acquires the prediction parameters of the sample to be detected. The prediction parameters include age, diagnosis result, hemodialysis, admission weight, whether the weight is continuously reduced for more than 2 days, degree of edema, creatinine value, hemoglobin, albumin, sodium urine peptide, medication, diuretic metabolism, whether combined with diabetes, and whether combined with heart failure. Specifically, as shown in Table 1, it is a specific analysis table of the prediction parameters, wherein B represents the weight coefficient of different prediction parameters. Figure 2

[0023] In some embodiments, the term "subject" or "testee" or "test sample" used herein refers to any animal (for example, a mammal), including but not limited to a human, a non-human primate, a rodent, etc., which will be the recipient of a particular treatment. Generally, the terms "subject" and "patient" are used interchangeably herein when referring to a human subject. Preferably, the subject is a human.

[0024] In some embodiments, the medication of the medication condition includes immunosuppressants and hormones.

[0025] In some embodiments, the diagnosis result includes nephrotic syndrome, chronic glomerulonephritis, AKI, and rapidly progressive glomerulonephritis.

[0026] In some embodiments, the degree of edema includes mild, moderate, and severe.

[0027] ​a risk prediction module configured to input the prediction parameters into a volume load risk prediction model, and output a risk value; and output a suggestion of whether the first to-be-eaten volume needs to be adjusted according to the risk value; In some embodiments, the volume load risk prediction model is: Y = X1 * a1 + X2 * a2 + X3 * a3 + X4 * a4 + X5 * a5 + X6 * a6 + X7 * a7 + X8 * a8 + X9 * a9 + X10 * a10 + X11 * a11 + X12 * a12 + X13 * a13 + X14 * a14 + X15 * a15; wherein a1 to a15 are coefficients, X1 is age, X2 is diagnosis result, X3 is hemodialysis, X4 is admission weight, X5 is whether the weight has not decreased for more than 2 consecutive days, X6 is edema degree, X7 is creatinine value, X8 is hemoglobin, X9 is albumin, X10 is sodium urine peptide, X11 is immunosuppressant, X12 is hormone, X13 is diuretic metabolism, X14 is whether diabetes is combined, and X15 is whether heart failure is combined.

[0028] In some embodiments, the suggestion further comprises an adjustment of a medication regimen, and the medication regimen is an adjustment of a medication or a medication route, and the medication route is intravenous or oral.

[0029] a food water content identification module configured to identify and analyze the water content of the to-be-eaten food, calculate a second to-be-eaten volume, and adjust the second to-be-eaten volume according to the first to-be-eaten volume so that the two volumes match.

[0030] In some embodiments, the device further comprises a food increase / decrease module configured to recalculate the water content of the eaten food according to the second to-be-eaten volume according to whether there is surplus or deficiency of the to-be-eaten food.

[0031] In some embodiments, when there is surplus of the to-be-eaten food, the water content of the surplus food is calculated, a difference between the second to-be-eaten volume and the water content of the surplus food is calculated, and the water content of the eaten food is obtained.

[0032] In some embodiments, when there is deficiency of the to-be-eaten food, the water content of the newly added food is calculated, a total amount of the second to-be-eaten volume and the water content of the newly added food is calculated, and the water content of the eaten food is obtained.

[0033] In some embodiments, the device further comprises a volume reasonableness judgment module configured to calculate an absolute value of a difference between the water content of the eaten food and the first to-be-eaten volume, and output a result of whether the volume of the to-be-tested sample is reasonable according to the difference; when the absolute value is greater than a first threshold value, output a result that the volume of the to-be-tested sample is reasonable; and when the absolute value is less than the first threshold value, output a result that the volume of the to-be-tested sample is unreasonable.

[0034] In some embodiments, the device mainly involves a base, an AI image water content identification module, a food increase / decrease module, a nurse workstation uploading module, and a patient reasonable intake calculation module.

[0035] The base is provided with a display on the front side, and the above-mentioned modules can be selected on the display. The AI image water content identification module can analyze the water content of the food eaten by the patient by AI intelligent scanning, automatically calculate the intake, and remind the patient whether the intake is reasonable according to the doctor's advice. The food increase / decrease module can place the remaining food on the base again, press the food decrease button, and automatically subtract the identified water content from the last time after AI recognition and uploading. The application can judge whether the patient's intake and output are balanced the day before, prompt the patient whether to reduce the intake or appropriately increase the intake, before breakfast every day at 7:00, combined with the total intake A, total output B of the previous day, and the body weight C at 6:00 and the body weight D at 6:00 of the previous day.

[0036] The calculation formula is: A-B>500ml above C-D>0, that is, the daily intake should be reduced; C-D<0, that is, the current intake can be maintained.

[0037] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned system, device and unit can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0038] In the several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented by other ways. For example, the device embodiments described above are only schematic, and for example, the division of the units is only a logical function division, and there can be another division manner in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between the units can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0039] The example embodiments of the present disclosure described in detail above are only illustrative, not restrictive. Those skilled in the art should understand that various modifications and combinations of these embodiments or features can be made without departing from the principles and spirits of the present disclosure, and such modifications should fall within the scope of the present disclosure.

Claims

1. An intelligent access quantity calculating device, characterized by, The device comprises: a parameter acquisition module, which acquires a prediction parameter of a sample to be detected; the prediction parameter comprises age, diagnosis result, hemodialysis, admission weight, whether the weight is continuously reduced for more than two days, degree of edema, creatinine value, hemoglobin, albumin, sodium urine peptide, medication, diuretic metabolism, whether diabetes is combined, and whether heart function failure is combined; a risk prediction module, which inputs the prediction parameter into a volume load risk prediction model, and outputs a risk value; and outputs whether the first food intake amount needs to be adjusted according to the risk value; a food water content identification module, which is used for identifying and analyzing the water content of food to be eaten, calculating a second food intake amount, and adjusting the second food intake amount according to the first food intake amount so as to match the two.

2. The intelligent access quantification device of claim 1, wherein, The medication includes immunosuppressants and hormones.

3. The intelligent access quantification device of claim 2, wherein, The volume load risk prediction model is: Y=X1*a1+X2*a2+X3*a3+X4*a4+X5*a5+X6*a6+X7*a7+X8*a8+X9*a9+X10*a10+X11*a11+X12*a12+X13*a13+X14*a14+X15*a15; wherein a1 to a15 are coefficients, X1 is age, X2 is diagnosis result, X3 is hemodialysis, X4 is admission weight, X5 is whether the weight is continuously reduced for more than two days, X6 is degree of edema, X7 is creatinine value, X8 is hemoglobin, X9 is albumin, X10 is sodium urine peptide, X11 is immunosuppressants, X12 is hormones, X13 is diuretic metabolism, X14 is whether diabetes is combined, and X15 is whether heart function failure is combined.

4. The intelligent access quantification device of claim 1, wherein, The diagnosis result comprises nephrotic syndrome, chronic glomerulonephritis, AKI, and rapidly progressive glomerulonephritis.

5. The intelligent access quantification device of claim 1, wherein, The device further comprises a food increase / decrease module, which is used for recalculating the water content of food eaten according to the second food intake amount according to the situation of surplus or deficiency of food to be eaten.

6. The intelligent access quantification device of claim 5, wherein, When there is surplus of food to be eaten, the water content of the surplus food is calculated, the difference between the second food intake amount and the water content of the surplus food is calculated, and the water content of the food eaten is obtained.

7. The intelligent access quantification device of claim 5, wherein, When there is deficiency of food to be eaten, the water content of the newly added food is calculated, the total amount of the second food intake amount and the water content of the newly added food is calculated, and the water content of the food eaten is obtained.

8. The intelligent access quantification device of claim 3, wherein, The device further comprises an intake reasonableness judgment module, which is used for calculating the absolute value of the difference between the water content of the food eaten and the first food intake amount, and judging whether the intake of the sample to be detected is reasonable according to the result; when the absolute value is greater than a first threshold value, the result that the intake of the sample to be detected is reasonable is output; and when the absolute value is less than the first threshold value, the result that the intake of the sample to be detected is unreasonable is output.

9. The intelligent access quantification device of claim 1, wherein, The suggestion further comprises a medication scheme of adjusting medication or medication route, and the medication route is intravenous or oral.

10. The intelligent access quantification device of claim 1, wherein, The degree of edema comprises mild, moderate, and severe.

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