Prospective Randomized Controlled Study of Individualized PCA Model Based on Multi-dimensional Strategies (Fixed-rate Basal Infusion Mode and Time-programmed Decremental Background Infusion Mode)
Prospective Randomized Controlled Study of Individualized PCA Model Based on Multi-dimensional Strategies (Fixed-rate Basal Infusion Mode and Time-programmed Decremental Background Infusion Mode)
Perioperative pain management affects patient recovery. However, the rate of moderate to severe postoperative pain is as high as 73.8%, which hinders recovery and increases the risk of complications. Although opioids are the first-line analgesics, excessive use leads to adverse reactions. The traditional fixed-rate PCA mode is difficult to match the changes in postoperative pain. This study will compare different PCA mode optimization strategies, assuming that they can reduce opioid dosage, improve analgesic effect, and reduce adverse reactions, providing high-quality evidence-based basis for postoperative analgesia and promoting individualized and intelligent management.
Perioperative pain management significantly impacts patient recovery outcomes. However, the incidence of moderate to severe postoperative pain remains high at 73.8%, which impedes recovery and increases complication risks. Although opioids serve as first-line analgesics, excessive use causes numerous adverse reactions. The traditional fixed-rate Patient-Controlled Analgesia (PCA) mode fails to adapt to dynamic postoperative pain variations. This study will compare different PCA optimization strategies, hypothesizing that these approaches can reduce opioid dosage, enhance analgesic effectiveness, and minimize adverse reactions. The research aims to provide evidence-based foundations for postoperative analgesia, promoting individualized and intelligent pain management systems that better serve patient needs throughout recovery.
Inclusion Criteria:
Exclusion Criteria:
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