ArticleJournal of critical care2021
Preventing infectious diseases in Intensive Care Unit by medical devices remote control: Lessons from COVID-19.
Article in Journal of critical care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Health Information Technology-Related Loss of Central Surveillance Data in a Heart Intensive Care Unit: Multi-Framework Case Report.JMIR human factors · 2026Article
- Tele-monitoring system for intensive care ventilators in isolation rooms.Scientific reports · 2023Article
- ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units.Sensors (Basel, Switzerland) · 2023Article
- Strengthening the ICUs' human resource-related responses to Covid-19: A rapid review of the experience during the first year of public health emergency.The International journal of health planning and management · 2023Review
- Novel Technology Deployed for Remote Ventilator Management by Respiratory Therapists During the COVID-19 Pandemic: Lessons Learned.Journal of intensive care medicine · 2022Article
- The Supporting Role of Combined and Sequential Extracorporeal Blood Purification Therapies in COVID-19 Patients in Intensive Care Unit.Biomedicines · 2022Review
- Dual ModeSensors (Basel, Switzerland) · 2022Article
- A qualitative study of orthodontic patients' experiences in quarantine during the COVID-19 pandemic outbreak.American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics · 2022Article
- The patient safety in extracorporeal blood purification treatments of critical patients.Frontiers in nephrology · 2022Review
- Prolonged progressive hypermetabolism during COVID-19 hospitalization undetected by common predictive energy equations.Clinical nutrition ESPEN · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The management of COVID-19 patients in the ICUs requires several and prolonged life-support systems (mechanical ventilation, continuous infusions of medications and nutrition, renal replacement therapy). Parameters have to be entered continuously into the device user interface by healthcare personnel according to the dynamic clinical condition. This leads to an increased risk of cross-contamination, use of personal protective equipment and the need for stringent and demanding protocols. Cables and tubing extensions have been utilized to make certain devices usable outside the patient's room but at the cost of introducing further hazards. Remote control of these devices decreases the frequency of unnecessary interventions and reduces the risk of exposure for both patients and healthcare personnel.
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.