Evidence map›Paper›PMID 35448500›Full record

ReviewMetabolites2022

Cardiovascular/Stroke Risk Stratification in Parkinson's Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review.

Jasjit S Suri, Sudip Paul, Maheshrao A Maindarkar, Anudeep Puvvula, Sanjay Saxena, Luca Saba, Monika Turk, John R Laird, Narendra N Khanna, Klaudija Viskovic and 5 more

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
5.5field-weighted citation impact, top 3% 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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 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

15 authors at 9 institutions in 6 countries.

Jasjit S SuriStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USA.
Sudip PaulDepartment of Biomedical Engineering, North Eastern Hill University, Shillong 793022, India.ORCID 0000-0001-9856-539X
Maheshrao A MaindarkarDepartment of Biomedical Engineering, North Eastern Hill University, Shillong 793022, India.
Anudeep PuvvulaStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USA.
Sanjay SaxenaDepartment of CSE, International Institute of Information Technology, Bhuneshwar 751003, India.ORCID 0000-0002-8288-1010
Luca SabaDepartment of Radiology, University of Cagliari, 09121 Cagliari, Italy.
Monika TurkDeparment of Neurology, University Medical Centre Maribor, 1262 Maribor, Slovenia.
John R LairdHeart and Vascular Institute, Adventist Health St. Helena, St. Helena, CA 94574, USA.
Narendra N KhannaDepartment of Cardiology, Indraprastha APOLLO Hospitals, New Delhi 110001, India.
Klaudija ViskovicDepartment of Radiology and Ultrasound, University Hospital for Infectious Diseases, 10000 Zagreb, Croatia.
Inder M SinghStroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA 95661, USA.
Mannudeep KalraDepartment of Radiology, Harvard Medical School, Boston, MA 02115, USA.
Padukode R KrishnanNeurology Department, Fortis Hospital, Bangalore 560010, India.
Amer JohriDepartment of Medicine, Division of Cardiology, Queen's University, Kingston, ON K7L 3N6, Canada.
Kosmas I ParaskevasDepartment of Vascular Surgery, Central Clinic of Athens, 106 80 Athens, Greece.ORCID 0000-0001-6865-2919
North Eastern Hill University · INFortis Hospital · INHarvard University · USInternational Institute of Information Technology · INQueen's University · CASt. Helena Hospital · USUniversity Clinical Centre Maribor · SIUniversity Hospital Centre Zagreb · HRUniversity of Cagliari · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson’s disease (PD) is a severe, incurable, and costly condition leading to heart failure. The link between PD and cardiovascular disease (CVD) is not available, leading to controversies and poor prognosis. Artificial Intelligence (AI) has already shown promise for CVD/stroke risk stratification. However, due to a lack of sample size, comorbidity, insufficient validation, clinical examination, and a lack of big data configuration, there have been no well-explained bias-free AI investigations to establish the CVD/Stroke risk stratification in the PD framework. The study has two objectives: (i) to establish a solid link between PD and CVD/stroke; and (ii) to use the AI paradigm to examine a well-defined CVD/stroke risk stratification in the PD framework. The PRISMA search strategy selected 223 studies for CVD/stroke risk, of which 54 and 44 studies were related to the link between PD-CVD, and PD-stroke, respectively, 59 studies for joint PD-CVD-Stroke framework, and 66 studies were only for the early PD diagnosis without CVD/stroke link. Sequential biological links were used for establishing the hypothesis. For AI design, PD risk factors as covariates along with CVD/stroke as the gold standard were used for predicting the CVD/stroke risk. The most fundamental cause of CVD/stroke damage due to PD is cardiac autonomic dysfunction due to neurodegeneration that leads to heart failure and its edema, and this validated our hypothesis. Finally, we present the novel AI solutions for CVD/stroke risk prediction in the PD framework. The study also recommends strategies for removing the bias in AI for CVD/stroke risk prediction using the PD framework.

Indexed as

artificial intelligencecardiac autonomic dysfunctioncardiovascular diseasedeep learningmachine learningParkinson’s diseaserecommendationsstroke

Identifiers

PMID35448500
PMCPMC9033076
OpenAlexW4220681293

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.