Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Remote Monitoring of Cancer Patients With Suspected Covid-19

The Christie NHS Foundation Trust · 2020
ClinicalTrials.gov · Datasets · License: Public Domain · 2020
Open Source ↗
covidoncology
Since emerging in December 2019, coronavirus disease 2019 (Covid-19) has developed into an unprecedented global pandemic. The causative pathogen, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to cause a wide range of clinical syndromes, from fever, dyspnoea and cough to respiratory failure and cardiac injury necessitating critical care support. A number of patients have a more indolent clinical course and can be safely managed in the community. Characterising the clinical course of Covid-19 infection in the oncology population and distinguishing this from other acute oncology presentations which can mimic Covid-19 is a key unmet research need. Current standard of care for monitoring patients at high risk of chemotherapy associated neutropenic sepsis involves asking them to contact their cancer centre when they feel unwell or develop a fever. No standard of care for monitoring ambulatory Covid-19 patients has yet been established. We hypothesise that using wearable biosensors to detect patients who exhibit 'red flags' for sepsis or deterioration due to Covid-19 may allow earlier assessment and intervention. There is no current evidence for wearable biosensors in ambulatory patients receiving chemotherapy, and there is no existing research into this proposed use of biosensors in patients with suspected or confirmed Covid-19 infection. In order to justify performing a randomised controlled study comparing standard of care with biosensor driven monitoring it is important to establish the tolerability and validity of these devices. We aim to collect patient reported outcome measures (PROMs) on tolerability and assess the reliability of data transmission to a central data collection server. We will also perform an initial analysis of physiological data and correlation with clinical events
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1410302
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive