General surgery department patient postoperative complication risk prediction and nursing decision-making system

By using multidimensional state-space mapping and dynamic threshold adjustment, the problems of baseline drift and dynamic mismatch in traditional monitoring are solved, enabling accurate prediction and early warning of postoperative complications and optimizing nursing decisions.

CN121839151APending Publication Date: 2026-04-10FOURTH MILITARY MEDICAL UNIVERSITY
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Patent Information

Application Number
CN202610304955.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-13
Publication Date
2026-04-10

AI Technical Summary

Technical Problem

Traditional monitoring methods often use fixed thresholds, which can lead to baseline drift. Single-dimensional signals can mask the cascading mechanisms of the disease, resulting in a dynamic mismatch between high-frequency physiological data and occasional nursing interventions in the spatiotemporal dimensions, making it difficult to accurately predict postoperative complications.

Method used

The system employs a data acquisition and interface module, a baseline manifold construction module, a perturbation response topology evaluation module, a yaw vector decoding module, and a risk prediction module. Through multidimensional state space mapping, steady-state dissipation index calculation, and yaw vector decoding, it generates individualized physiological benchmarks, dynamically adjusts thresholds, and outputs diagnostic intervention actions.

Benefits of technology

Overcoming baseline drift, quantifying the physiological compensation exhaustion process in advance, accurately predicting postoperative complications, optimizing the efficiency of multidisciplinary consultation and triage, and improving the scientific nature of nursing decisions.

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Abstract

The invention relates to the technical field of medical informatization and intelligent nursing, in particular to a general surgery department patient postoperative complication risk prediction and nursing decision-making system, which comprises a baseline manifold construction module for initializing an individualized steady state manifold in a preset multi-dimensional state space based on historical operation parameters and basic state data; the perturbation response topology evaluation module is used for calculating a recovery attenuation coefficient after the real-time phase trajectory deviates from the individualized steady state manifold so as to generate a steady state dissipation index and a growth rate; the offset course quantity decoding module is used for adjusting a dynamic threshold value based on a time delay parameter and an embedded dimension parameter on the basis of the basic state data; the risk prediction module is used for weighting, merging and normalizing the growth rate of the steady-state dissipation index and the modulus length of the course deviation vector to generate a risk prediction evaluation result; the decision closed-loop module is used as a secondary perturbation variable and sends the secondary perturbation variable to the perturbation response topology evaluation module for continuous monitoring; according to the invention, the baseline anchoring precision in different clinical scenes is improved.
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