Post-operative Pain Prediction
Post-operative Pain Prediction - Related Videos
14:56
An Experimental Paradigm for the Prediction of Post-Operative Pain (PPOP)
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Cited by 107 •
2010
Diffuse noxious inhibitory control, temporal summation and wound hyperalgesia testing are demonstrated in the obstetric patient. These tests evaluate inhibitory and excitatory mechanisms of pain processing and are here utilized to evaluate endogenous analgesia at different time-points during pregnancy and the peripartum period to help reveal individual s risk for persistent pain.
12:20
Use of the Operant Orofacial Pain Assessment Device (OPAD) to Measure Changes in Nociceptive Behavior
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Cited by 42 •
2013
We present a user-friendly, high-throughput operant system for the evaluation of pain behaviors in awake, conscious rodents. The Orofacial Pain Assessment Device (OPAD) can assess pain through a reward/conflict paradigm thus providing a more humane way of testing. This protocol will yield more clinically relevant and translational data from rodents.
![Autoradiographic Measurements of [<sup>14</sup>C]-Iodoantipyrine in Rat Brain Following Central Post-Stroke Pain](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F53947.jpg%3Fv%3D2026-09-01%252006%253A32%253A11&w=750&q=75)
07:27
Autoradiographic Measurements of [14C]-Iodoantipyrine in Rat Brain Following Central Post-Stroke Pain
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Cited by 1 •
2016
We present a protocol to measure [14C]-iodoantipyrine (IAP) uptake and assess the activation of neural substrates that are involved in central post-stroke pain (CPSP) in a rodent model.
07:12
Chronic Post-Ischemia Pain Model for Complex Regional Pain Syndrome Type-I in Rats
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Cited by 15 •
2020
Provided here is a protocol that details steps to establish an animal model of chronic post-ischemia pain (CPIP). This is a well-recognized model mimicking human complex regional pain syndrome type-I. Mechanical and thermal hypersensitivities are further evaluated, as well as capsaicin-induced nocifensive behaviors observed in the CPIP rat model.
09:38
Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery
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Cited by 17 •
2016
Human pain models are valuable tools used to assess the analgesic potential of novel compounds and predict their clinical efficacy, especially when used in an integrated manner. Although implementation of these models is complex, with proper execution, the pain models described in this protocol can provide predictive and reliable results.
FAQs
Prediction performance depends on the information available before surgery, details of the operation, and measures collected during early recovery. Preoperative pain, patient characteristics, surgical details, and early recovery measures may each reveal different aspects of risk. Considering these variables together can help identify clinically meaningful patterns more effectively than focusing on a single factor.
Information collected at different perioperative stages can support different kinds of estimates. Preoperative findings may indicate baseline vulnerability, while surgical details add procedure-related context and early recovery measures provide updated evidence after the operation. This staged perspective allows clinicians to refine expectations as the patient’s course develops rather than relying only on an initial assessment.
Acute and persistent pain represent different clinical time frames and may require different monitoring priorities. An estimate of immediate pain can support timely analgesic selection and observation during early recovery, whereas identifying risk for prolonged pain can guide follow-up and additional counseling. Separating these outcomes helps align clinical attention with the patient’s evolving needs.
Patient characteristics provide context for interpreting preoperative pain, surgical details, and recovery findings. The same operation or early symptom pattern may not imply identical risk for every patient, so models use individual information to support more personalized estimates. This approach can help clinicians recognize patients who may need closer monitoring or more targeted follow-up.
Clinicians can use the available preoperative, surgical, and early recovery information to identify patterns associated with expected pain or prolonged symptoms. The resulting estimate may inform analgesic selection, monitoring intensity, patient counseling, and follow-up planning. Its value lies in supporting individualized decisions while helping reduce both undertreatment and unnecessary medication exposure.
Research models can reveal which combinations of preoperative pain, patient characteristics, surgical details, and early recovery measures are associated with acute or persistent pain. These findings help clarify risk factors for prolonged symptoms and evaluate how prediction may improve perioperative decision-making. Over time, such evidence can support more personalized approaches to monitoring and follow-up in medicine.