ArticleJournal of clinical medicine2021
Exploring Early Pre-Symptomatic Detection of Influenza Using Continuous Monitoring of Advanced Physiological Parameters during a Randomized Controlled Trial.
Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- Trial
- Using artificial intelligence to predict patient outcomes from patient-reported outcome measures: a scoping review.Health and quality of life outcomes · 2025Article
- Changes in behavior and biomarkers during the diagnostic decision period for COVID-19, influenza, and group A streptococcus (GAS): a two-year prospective cohort study in Israel.The Lancet regional health. Europe · 2024Article
- Non-Invasive Biosensing for Healthcare Using Artificial Intelligence: A Semi-Systematic Review.Biosensors · 2024Review
- Remote digital health technologies for improving the care of people with respiratory disorders.The Lancet. Digital health · 2024Review
- The WE SENSE study protocol: A controlled, longitudinal clinical trial on the use of wearable sensors for early detection and tracking of viral respiratory tract infections.Contemporary clinical trials · 2023Article
- Comparing body temperature measurements using the double sensor method within a wearable device with oral and core body temperature measurements using medical grade thermometers-a short report.Frontiers in physiology · 2023Article
- Developing a real-time detection tool and an early warning score using a continuous wearable multi-parameter monitor.Frontiers in physiology · 2023Article
- Novel graph-based machine-learning technique for viral infectious diseases: application to influenza and hepatitis diseases.Annals of medicine · 2023Article
- Assessing the Usability of a Novel Wearable Remote Patient Monitoring Device for the Early Detection of In-Hospital Patient Deterioration: Observational Study.JMIR formative research · 2022Article
- Ultrasound Neuromodulation of the Spleen Has Time-Dependent Anti-Inflammatory Effect in a Pneumonia Model.Frontiers in immunology · 2022Article
- Review
- Threat Agnostic Approach to Epidemic Management Using Continuous Remote Patient Monitoring.Health securityArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Early detection of influenza may improve responses against outbreaks. This study was part of a clinical study assessing the efficacy of a novel influenza vaccine, aiming to discover distinct, highly predictive patterns of pre-symptomatic illness based on changes in advanced physiological parameters using a novel wearable sensor. Participants were frequently monitored 24 h before and for nine days after the influenza challenge. Viral load was measured daily, and self-reported symptoms were collected twice a day. The Random Forest classifier model was used to classify the participants based on changes in the measured parameters. A total of 116 participants with ~3,400,000 data points were included. Changes in parameters were detected at an early stage of the disease, before the development of symptomatic illness. Heart rate, blood pressure, cardiac output, and systemic vascular resistance showed the greatest changes in the third post-exposure day, correlating with viral load. Applying the classifier model identified participants as flu-positive or negative with an accuracy of 0.81 ± 0.05 two days before major symptoms appeared. Cardiac index and diastolic blood pressure were the leading predicting factors when using data from the first and second day. This study suggests that frequent remote monitoring of advanced physiological parameters may provide early pre-symptomatic detection of flu.
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.