Evidence map›Paper›PMID 35681950›Full record

ArticleInternational journal of environmental research and public health2022

Clinical Network for Big Data and Personalized Health: Study Protocol and Preliminary Results.

Simona Esposito, Sabatino Orlandi, Sara Magnacca, Amalia De Curtis, Alessandro Gialluisi, Licia Iacoviello, On Behalf Of The Neuromed Clinical Network Big Data And Personalised Health Investigators

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Observational
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

7 authors.

Simona EspositoDepartment of Epidemiology and Prevention, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Neuromed, 86077 Pozzilli, Italy.
Sabatino OrlandiDepartment of Epidemiology and Prevention, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Neuromed, 86077 Pozzilli, Italy.
Sara MagnaccaMediterranea Cardiocentro, 80122 Napoli, Italy.
Amalia De CurtisDepartment of Epidemiology and Prevention, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Neuromed, 86077 Pozzilli, Italy.
Alessandro GialluisiDepartment of Epidemiology and Prevention, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Neuromed, 86077 Pozzilli, Italy.ORCID 0000-0002-7388-4463
Licia IacovielloDepartment of Epidemiology and Prevention, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Neuromed, 86077 Pozzilli, Italy.ORCID 0000-0003-0514-5885
On Behalf Of The Neuromed Clinical Network Big Data And Personalised Health Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of secondary hospital-based clinical data and electronical health records (EHR) represent a cost-efficient alternative to investigate chronic conditions. We present the Clinical Network Big Data and Personalised Health project, which collects EHRs for patients accessing hospitals in Central-Southern Italy, through an integrated digital platform to create a digital hub for the collection, management and analysis of personal, clinical and environmental information for patients, associated with a biobank to perform multi-omic analyses. A total of 12,864 participants (61.7% women, mean age 52.6 ± 17.6 years) signed a written informed consent to allow access to their EHRs. The majority of hospital access was in obstetrics and gynaecology (36.3%), while the main reason for hospitalization was represented by diseases of the circulatory system (21.2%). Participants had a secondary education (63.5%), were mostly retired (25.45%), reported low levels of physical activity (59.6%), had low adherence to the Mediterranean diet and were smokers (30.2%). A large percentage (35.8%) were overweight and the prevalence of hypertension, diabetes and hyperlipidemia was 36.4%, 11.1% and 19.6%, respectively. Blood samples were retrieved for 8686 patients (67.5%). This project is aimed at creating a digital hub for the collection, management and analysis of personal, clinical, diagnostic and environmental information for patients, and is associated with a biobank to perform multi-omic analyses.

Indexed as

Big DataMedical Records Systems, ComputerizedAdultAgedChronic DiseaseFemaleHospitalsHumansInformed ConsentMaleMiddle Agedelectronical health recordspersonalized medicineprevention

Identifiers

PMID35681950
PMCPMC9180513

What Socratic 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 Socratic graph.