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Accepted for/Published in: JMIR Perioperative Medicine

Date Submitted: Feb 7, 2022
Date Accepted: Jun 29, 2022

The final, peer-reviewed published version of this preprint can be found here:

Long-Term Postoperative Pain Prediction Using Higher-Order Singular Value Decomposition of Intraoperative Physiological Responses: Prospective Cohort Study

Baharloo R, Principe J, Rashidi P, Tighe P

Long-Term Postoperative Pain Prediction Using Higher-Order Singular Value Decomposition of Intraoperative Physiological Responses: Prospective Cohort Study

JMIR Perioper Med 2022;5(1):e37104

DOI: 10.2196/37104

PMID: 36103231

PMCID: 9520382

Long-Term Postoperative Pain Prediction: Higher-Order Singular-Value Decomposition of Intraoperative Physiological Responses

  • Raheleh Baharloo; 
  • Jose Principe; 
  • Parisa Rashidi; 
  • Patrick Tighe

ABSTRACT

Background:

Long-term pain conditions after surgery and patient responses to pain relief medications are not yet fully understood. Although recent studies have developed an index for the nociception level of patients under general anesthesia based on multiple physiological parameters, it remains unclear whether and how dynamic of these parameters indicate long-term postoperative pain.

Objective:

To extract unbiased and interpretable descriptions of how the dynamics of physiological parameters change over time and across patients in response to surgical procedures and intraoperative medications, we used a multivariate-temporal analysis. We demonstrate that the main features of intraoperative physiological responses can be used to predict long-term postoperative pain.

Methods:

We propose to use a complex higher-order singular-value decomposition (complex-HOSVD) method to accurately decompose patients’ physiological responses into multivariate structures evolving over time. We used intraoperative vital signs of 175 patients from a mixed surgical cohort to extract three interconnected, low-dimensional, complex-valued descriptions of patients’ physiological responses: multivariate factors, reflecting subphysiological parameters; temporal factors, reflecting common intrasurgery temporal dynamics; and patients’ factors, describing interpatient changes in physiological responses.

Results:

Adoption of the complex-HOSVD allowed us to clarify the dynamic correlation structure included in intraoperative physiological responses. Instantaneous phases of the complex-valued physiological responses within the subspace of principal descriptors enabled us to discriminate between “mild” and “severe” levels of pain at postoperative days 30 and 90.

Conclusions:

By abstracting patients into different surgical groups, we identified significant surgery-related principal descriptors. Each of them potentially encodes different surgical stimulation. The dynamics of patients’ physiological responses to these surgical events were linked to long-term postoperative pain development.


 Citation

Please cite as:

Baharloo R, Principe J, Rashidi P, Tighe P

Long-Term Postoperative Pain Prediction Using Higher-Order Singular Value Decomposition of Intraoperative Physiological Responses: Prospective Cohort Study

JMIR Perioper Med 2022;5(1):e37104

DOI: 10.2196/37104

PMID: 36103231

PMCID: 9520382

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