Evidence map›Paper›PMID 42701666›Full record

ArticleCureus2026

Humanistic and Economic Burden of Spinal Muscular Atrophy in the Gulf Region.

Baher Elezbawy, Sherif Abaza, Amal Alnajjar, Hana Alabdulkarim, Hussain A Al-Omar, Sahar Fahmy, Sara Aldallal, Tamás Ágh, Ahmad Fasseeh

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Baher ElezbawyEvidence Synthesis, Syreon Middle East, Alexandria, EGY.
Sherif AbazaHealth Economics, Syreon Middle East, Alexandria, EGY.
Amal AlnajjarDrug and Poison Information Center, Security Forces Hospital, Riyadh, SAU.
Hana AlabdulkarimDoctoral School of Applied Informatics and Applied Mathematics, Óbuda University, Budapest, HUN.
Hussain A Al-OmarClinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, SAU.
Sahar FahmyUndersecretary Office, Department of Health, Abu Dhabi, ARE.
Sara AldallalHealth Economics, Emirates Health Economics Society, Dubai, ARE.
Tamás ÁghHealth Economics, Syreon Research Institute, Budapest, HUN.
Ahmad FasseehModelling, Syreon Middle East, Alexandria, EGY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpinal muscular atrophy (SMA) is a severe, fatal genetic disorder. This study aimed to quantify the humanistic and economic burden of SMA in four Gulf countries, the Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), Oman, and Bahrain, to provide decision-makers with evidence-based strategies for burden mitigation.

methodsA burden of disease model was developed to quantify SMA's humanistic burden via disability-adjusted life years (DALYs) and its economic burden through direct healthcare costs and indirect productivity losses experienced by patients and caregivers.

resultsType 1 SMA caused the highest burden across all countries, followed by types 2 and 3. Total DALYs were 274,008 in KSA, 35,877 in UAE, 33,459 in Oman, and 8,679 in Bahrain. National direct medical costs totaled 114.9 million USD, 25.0 million USD, 9.5 million USD, and 3.8 million USD in KSA, UAE, Oman, and Bahrain, respectively. Annual indirect costs, driven by productivity losses among patients and caregivers, were estimated at 28.1 million USD in KSA, 5.3 million USD in UAE, 3.9 million USD in Oman, and 0.99 million USD in Bahrain.

conclusionsThe burden of SMA is considerable, particularly in the more severe phenotypes, with a profound humanistic impact and high medical costs. While results vary by population size, the consistent patterns across countries underscore the disease's severity and the urgent need for effective mitigation strategies.

Indexed as

disease burdeneconomic burdenhumanistic burdenproductivity lostresource utilizationspinal muscular atrophy

Identifiers

PMID42701666
PMCPMC13545702

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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.