Evidence map›Paper›PMID 39734941›Full record

ReviewCureus2024

Newer Insulin Preparations and Insulin Analogs.

Devkumar D Tiwari, Vandana M Thorat, Dr Prathamesh V Pakale

Abstract readReview
In one paragraph

Review in Cureus, 2024. 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. Article
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

3 authors.

Devkumar D TiwariDepartment of Pharmacology, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, IND.
Vandana M ThoratDepartment of Pharmacology, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, IND.
Dr Prathamesh V PakaleDepartment of Pharmacology, Krishna Vishwa Vidyapeeth (Deemed to be University), Karad, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus represents a significant and growing global health challenge, with its prevalence steadily increasing. Insulin therapy remains a cornerstone of diabetes management. Since its discovery in 1921, insulin has undergone substantial advancements, evolving from crude animal extracts to highly refined recombinant formulations and biosimilars. This review explores the progression of insulin therapies, emphasizing the evolution from conventional insulins to modern analogs designed to mimic endogenous insulin more effectively. The limitations of early insulin formulations, such as unpredictable absorption, rigid dosing regimens, and an increased risk of hypoglycemia, highlighted the need for improved therapies. Modern insulin analogs, including fast-acting (e.g., insulin lispro), long-acting (e.g., insulin glargine and insulin degludec), and ultra-long-acting (e.g., insulin icodec) options, address these challenges by providing stable and consistent pharmacokinetics, along with enhanced glycemic control. Furthermore, biosimilar insulins, produced via recombinant DNA technology, have increased accessibility while maintaining therapeutic efficacy and safety. Recent innovations, such as ultra-long-acting insulins and combination therapies like insulin icodec with semaglutide, offer the potential to reduce injection frequency and enable personalized diabetes care. These advancements contribute to improved patient compliance, reduced glycemic variability, and an enhanced quality of life. This review highlights the critical role of ongoing research and innovation in insulin therapy to meet the evolving needs of diabetes management.

Indexed as

diabetes mellitus type ifrederick bantinglong-acting insulinporcinereference insulin glargine

Identifiers

PMID39734941
PMCPMC11676328

What OpenQuestion holds

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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.