ArticleScientific reports2023
Predicting vasovagal reactions to needles with anticipatory facial temperature profiles.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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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
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial Intelligence-based predictive models for adverse blood donor reactions: a systematic review of immediate and delayed events and clinical data approaches.BMC medical informatics and decision making · 2026Pooled it
- Risk factors for vasovagal reactions in blood donors: A systematic review and meta-analysis.Transfusion · 2025Pooled it
- Factors associated with documented distress during venipuncture in routine health checkups.Frontiers in psychiatry · 2026Article
- Predicting vasovagal reactions to needles from video data using 2D-CNN with GRU and LSTM.PloS one · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Around one-third of adults are scared of needles, which can result in adverse emotional and physical responses such as dizziness and fainting (e.g. vasovagal reactions; VVR) and consequently, avoidance of healthcare, treatments, and immunizations. Unfortunately, most people are not aware of vasovagal reactions until they escalate, at which time it is too late to intervene. This study aims to investigate whether facial temperature profiles measured in the waiting room, prior to a blood donation, can be used to classify who will and will not experience VVR during the donation. Average temperature profiles from six facial regions were extracted from pre-donation recordings of 193 blood donors, and machine learning was used to classify whether a donor would experience low or high levels of VVR during the donation. An XGBoost classifier was able to classify vasovagal groups from an adverse reaction during a blood donation based on this early facial temperature data, with a sensitivity of 0.87, specificity of 0.84, F1 score of 0.86, and PR-AUC of 0.93. Temperature fluctuations in the area under the nose, chin and forehead have the highest predictive value. This study is the first to demonstrate that it is possible to classify vasovagal responses during a blood donation using temperature profiles.
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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.