Evidence map›Paper›PMID 34834469›Full record

ArticleJournal of personalized medicine2021

Results of the Second Phase of the GER-e-TEC Experiment concerning the Telemonitoring of Elderly Patients Affected by COVID-19 Disease to Detect the Exacerbation of Geriatric Syndromes.

Abrar-Ahmad Zulfiqar, Delwende Noaga Damien Massimbo, Mohamed Hajjam, Bernard Geny, Samy Talha, Jawad Hajjam, Sylvie Erve, Amir Hajjam, Emmanuel Andrès

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 37% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 3 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Abrar-Ahmad ZulfiqarService de Médecine Interne, Diabète et Maladies Métaboliques de la Clinique Médicale B, Hôpitaux Universitaires de Strasbourg, Equipe EA 3072 "Mitochondrie, Stress Oxydant et Protection Musculaire", Faculté de Médecine, Université de Strasbourg, 67000 Strasbourg, France.ORCID 0000-0003-0669-5678
Delwende Noaga Damien MassimboPredimed Technology Society, 67300 Schiltigheim, France.
Mohamed HajjamPredimed Technology Society, 67300 Schiltigheim, France.
Bernard GenyService de Physiologie et d'Explorations Fonctionnelles, Hôpitaux Universitaires de Strasbourg, Equipe EA 3072 "Mitochondrie, Stress Oxydant et Protection Musculaire", Faculté de Médecine, Université de Strasbourg, 67000 Strasbourg, France.
Samy TalhaService de Physiologie et d'Explorations Fonctionnelles, Hôpitaux Universitaires de Strasbourg, Equipe EA 3072 "Mitochondrie, Stress Oxydant et Protection Musculaire", Faculté de Médecine, Université de Strasbourg, 67000 Strasbourg, France.ORCID 0000-0002-2094-2842
Jawad HajjamCentre d'Expertise des TIC pour l'Autonomie (CenTich), Mutualité Française Anjou-Mayenne (MFAM)-Angers, 49000 Angers, France.
Sylvie ErveCentre d'Expertise des TIC pour l'Autonomie (CenTich), Mutualité Française Anjou-Mayenne (MFAM)-Angers, 49000 Angers, France.
Amir HajjamLaboratoire IRTES-SeT, Université de Technologie de Belfort-Montbéliard (UTBM), Belfort-Montbéliard, 90000 Belfort, France.ORCID 0000-0002-8470-806X
Emmanuel AndrèsService de Médecine Interne, Diabète et Maladies Métaboliques de la Clinique Médicale B, Hôpitaux Universitaires de Strasbourg, Equipe EA 3072 "Mitochondrie, Stress Oxydant et Protection Musculaire", Faculté de Médecine, Université de Strasbourg, 67000 Strasbourg, France.ORCID 0000-0002-7914-7616
Hôpitaux Universitaires de Strasbourg · FRLaboratoires d'Anjou (France) · FRUniversité de technologie de belfort-montbéliard · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) has wreaked health and economic damage globally. This pandemic has created a difficult challenge for global public health. The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including elderly patients. Our team developed a telemonitoring program focused on the prevention of geriatric syndromes, the "GER-e-TEC COVID study".

methodsThis second phase took place during the 3rd wave of the epidemic in France, between 14 December 2020 and 25 February 2021, conducted in the University Hospital of Strasbourg.

results30 elderly patients affected by COVID-19 disease were monitored remotely; the mean age was 85.9 years and a male/female ratio of 1.5 to 1.11 (36.7%) died during the experiment. The patients used the telemedicine solution for an average of 27.3 days. 140,260 measurements were taken while monitoring the geriatric syndromes of the entire patient group. 4675 measurements were recorded per patient for geriatric disorders and risks. 319 measurements were recorded per patient per day. The telemedicine solution emitted a total of 1245 alerts while monitoring the geriatric syndromes of the entire patient group. In terms of sensitivity, the results were 100% for all geriatric risks and extremely satisfactory in terms of positive and negative predictive values. Survival analyses showed that gender played no role in the length of the hospital stay, regardless of the reason for the hospitalization (decompensated heart failure (

conclusionsThe MyPredi™ telemedicine system allows for the generation of automatic, non-intrusive alerts when the health of a COVID-19 elderly patient deteriorates due to risks associated with geriatric syndromes.

Indexed as

alertsCOVID-19geriatric syndromesMyPredi platformtelemonitoring

Identifiers

PMID34834469
PMCPMC8621367
OpenAlexW3208572650

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.