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Early prediction system for predicting severity of acute pancreatitis patient

Pending Publication Date: 2022-02-08
WEST CHINA HOSPITAL SICHUAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the nomogram reported in this literature mainly has the following problems: (1) The prediction model includes patients admitted within 72 hours of onset, which is not time-sensitive for AP, a disease that changes rapidly in the early stage of acute disease; ( 2) The predictive model lacks the evaluation of the clinical utility of the predictive model, such as decision curve analysis and clinical impact curve; (3) The predictive model lacks prospective trial design and multi-center verification, and it is not very generalizable from a scientific point of view. The application value is not high; (4) Insufficient and inconvenient visual applications, lack of mobile terminal applications

Method used

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  • Early prediction system for predicting severity of acute pancreatitis patient
  • Early prediction system for predicting severity of acute pancreatitis patient
  • Early prediction system for predicting severity of acute pancreatitis patient

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] Example 1 Establishing an Early Prediction System for Predicting the Probability of Acute Pancreatitis Patients Developing into Severe Acute Pancreatitis

[0053] The early prediction system of the present invention is a visual nomogram for predicting the probability of acute pancreatitis patients developing severe acute pancreatitis, and the construction method includes the following steps.

[0054] 1. Patient information

[0055] (1.1) Inclusion and exclusion criteria

[0056] Inclusion criteria: (1) clearly diagnosed AP, (2) aged from 18 to 80 years old, (3) from the onset of abdominal pain to hospital admission within 48 hours.

[0057] Exclusion criteria: chronic pancreatitis, pancreatic tumor, trauma or pregnancy as the etiology of AP, patients with serious systemic complications.

[0058] (1.2) Data source

[0059] Including the training queue, internal validation and external validation queues, as follows:

[0060] (1) Training cohort: A retrospective data s...

Embodiment 2

[0084] Embodiment 2 Nomogram Visualization Webpage Calculator

[0085] Based on the calculation formula of the nomogram obtained in Example 3, make a webpage calculator for predicting the occurrence of POF in AP patients when calculating admission, and input 6 independent prognostic factors (age, respiratory rate, albumin, lactate dehydrogenation) of the patient to be predicted. After enzyme LDH, oxygen support and pleural effusion), the corresponding predicted probability value can be automatically output.

[0086] Figure 4 For example: a 47-year-old patient had a respiratory rate (R) of 20 breaths / minute, albumin (Albumin) 43IU / L, lactate dehydrogenase (LDH) 257IU / L, and oxygen on admission. With supportive treatment but no pleural effusion, the probability of developing severe AP is 9.7%.

[0087] The prediction effect of the prediction system of the present invention is demonstrated through the following experimental examples.

experiment example 1

[0088] Experimental Example 1 Discrimination and Calibration Verification

[0089] 1. Experimental method

[0090] (1) Validation model discrimination: evaluated by the area under the receiver operating characteristic curve (AUC), also called the C index. The larger the AUC, the better the discrimination ability of the prediction model.

[0091] (2) Verify the calibration of the model: draw a calibration curve, and the closeness of the data points to the solid red line in the figure reflects the calibration of the model.

[0092] 2. Experimental results

[0093] In the training cohort, the C index of the nomogram was 0.88 ( figure 2 A), the calibration curve for predicting severe AP ( figure 2 B) Shows good agreement with actual occurrence of POF. In the internal validation cohort, compared with the training cohort, the C-index of the nomogram for predicting severe AP reached 0.91 ( figure 2 C) and has better consistency ( figure 2 D). The C-index in the external v...

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Abstract

The invention provides an early prediction system for predicting the severity of an acute pancreatitis patient, and belongs to the field of prediction models. The prediction system is constructed by taking the age, respiratory rate, albumin, lactic dehydrogenase LDH, oxygen support and pleural effusion of a patient with acute pancreatitis as prediction indexes. The prediction system is simple in construction method and high in prediction accuracy and distinction degree, can accurately judge the early severity of acute pancreatitis patients, accurately judges the probability that the patients develop into severe acute pancreatitis, helps clinicians to obtain the maximum income when making clinical decisions, helps guide the clinicians to make individual treatment decisions, improves the survival rate of patients and is wide in application prospect.

Description

technical field [0001] The invention belongs to the field of prediction models, in particular to an early prediction system for predicting the severity of patients with acute pancreatitis. Background technique [0002] Acute pancreatitis (AP) is a systemic inflammatory response involving multiple organ systems. Most people with AP have mild disease and usually recover within a week. However, in some patients, the inflammatory reaction will spread from the pancreas to the whole system, affecting the normal function of various organs, such as respiratory insufficiency, renal insufficiency, circulatory system insufficiency (lower blood pressure or even shock), coagulation disorder (high blood pressure, etc.) coagulation state), etc., and severe organ failure (organ failure, OF) will occur, accompanied by hypoalbuminemia, hypocalcemia, etc. OF is the main cause of early death in AP patients. The overall case fatality rate for AP ranges from 5-10%. However, if a patient devel...

Claims

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Application Information

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IPC IPC(8): G16H50/20G16H50/70
CPCG16H50/20G16H50/70
Inventor 石娜
Owner WEST CHINA HOSPITAL SICHUAN UNIV
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