Skin Temperature of Acupoints in Health and Disease: A Systematic Review
Bibliographic record
Abstract
Introduction: Despite substantial progress made in the field of acupuncture research, the existence and specificity of acupoints remain controversial. In recent years, the concept of acupoint sensitization has emerged as a theoretical framework for understanding acupoints as dynamic functional entities that are sensitized in pathological conditions. Based on this premise, some have claimed that specific acupoints are thermally distinct between healthy and clinical populations, but no systematic review has been conducted to synthesize and evaluate the quality of studies supporting such claims. In this review, we provide a summary and quality assessment of the existing literature addressing the question of whether changes in skin temperature at specific acupoints are indicative of pathological conditions. Methods: A systematic literature search was performed in PubMed, EMBASE, and AltHealthWatch (EBSCO Host), by combining variations of search terms relevant to acupoints and temperature. The search was limited to the English language, and publication dates ranged from database inception to December 2020. Two authors independently screened all resulting abstracts and subsequently read full-text articles for eligibility. Information on study design, sample, acupoints, parameters of skin temperature assessments, and main findings were extracted from included studies. Quality of the thermal sensing methodology was evaluated using a thermal assessment checklist, adapted from the Thermographic Imaging in Sports and Exercise Medicine (TISEM) consensus checklist, and a modified Newcastle–Ottawa Scale (NOS) for case–control studies. Results: The search strategy yielded a total of 1771 studies, of which 10 articles met the eligibility criteria. Eight studies compared skin temperature at acupoints in healthy versus clinical populations, and two studies assessed within-subject changes in temperature of acupoints in relation to changes in health status. There were seven clinical conditions examined in the included studies: chronic bronchial asthma, chronic hepatitis, hyperplasia of mammary glands, infertility, intracranial hypertension, obesity, and primary dysmenorrhea. There were numerous methodological quality issues related to skin temperature measurements. Eight studies with case–control designs reported significant differences between healthy and clinical populations in temperature at certain acupoints. Two studies with pre–post designs reported that changes in health-disease status could be associated with changes in temperature at specific acupoints. Conclusion: A review of the available literature suggests that certain acupoints may be thermally distinct between healthy and unhealthy states. However, given the methodological limitations and heterogeneity across included studies, no definitive conclusion could be drawn as to whether changes in skin temperature at specific acupoints are indicative of pathological conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".