ArticleGlobal health research and policy2025
Differentiating network structures and sex differences of pain-related outcomes, analgesic opioid dosages, and psychosocial factors for postoperative management: a study of PAIN OUT registry in seven Asian regions.
Article in Global health research and policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite advancements in global healthcare, Asia lacks a systematic framework for postoperative pain-related symptoms, particularly in addressing pain identification/prevention and reporting sex differences. This study used network analysis to unravel the complex interplay of pain-related symptoms, analgesic opioid dosages, and psychosocial factors, with a particular focus on sex differences in the Asian population.
methodsUtilizing anonymized data from 5,093 adult patients across seven Asian regions between 2018 and 2021 from the PAIN OUT registry, this study applied network analysis: 1) to map the relationships between analgesic opioid dosages and multidimensional pain-related symptoms and 2) to explore sex differences. This network analysis was performed based on information from the International Pain Outcomes Questionnaire (IPO-Q), which included pain severity, adverse events, perceptions of pain care perception, and pain treatment satisfaction within 24h of an operation. The model utilized Least Absolute Shrinkage and Selection Operator (LASSO) for regularization and edge estimation, a penalized estimation method allowing for the identification of the most relevant connections while effectively controlling for overfitting.
resultsNetwork structures demonstrated high stability, revealing distinct sex-based patterns. Chronicity of pain (#CP) emerged as the most central node in the overall network structure (EI = 1.50) and among male patients (EI = 1.80), reflecting the profound effect of persistent pain on their functional activities and sensory-focused symptoms, such as dizziness (#AE4). In contrast, helplessness (#MH2) was a significant symptom in female patients (EI = 1.70), highlighting the emotional and psychological dimensions of their pain experience. Comparative analysis uncovered significant structural differences between males and females (M = 0.154, p = 0.023), emphasizing the unique interplay of psychological, emotional, societal, and pathophysiological symptoms in shaping postoperative pain experiences.
conclusionsThis study was the first comprehensive network analysis of pain-related symptoms with sex differences. The results highlighted a significant difference in associations between analgesic opioid dosages and multidimensional pain-related symptoms among males and females, implying the necessity for region-specific, multimodal interventions to optimize postoperative care in Asian populations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.