Evidence map›Paper›PMID 37380824›Full record

ReviewReviews in endocrine & metabolic disorders2023

Hidden chronic metabolic acidosis of diabetes type 2 (CMAD): Clues, causes and consequences.

Hayder A Giha

Abstract readReview
PubMed Publisher
In one paragraph

Review in Reviews in endocrine & metabolic disorders, 2023. 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
1.0field-weighted citation impact, top 25% 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, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
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

1 author at 1 institution in 1 country.

Hayder A GihaMedical Biochemistry and Molecular Biology, Khartoum, Sudan. gehaha2002@yahoo.com.
Sudan Medical Specialization Board · SD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interpretation of existing data revealed that chronic metabolic acidosis is a pathognomic feature for type 2 diabetes (T2D), which is described here as "chronic metabolic acidosis of T2D (CMAD)" for the first time. The biochemical clues for the CMAD are summarised in the following; low blood bicarbonate (high anionic gap), low pH of interstitial fluid and urine, and response to acid neutralization, while the causes of extra protons are worked out to be; mitochondrial dysfunction, systemic inflammation, gut microbiota (GM), and diabetic lung. Although, the intracellular pH is largely preserved by the buffer system and ion transporters, a persistent systemic mild acidosis leaves molecular signature in cellular metabolism in diabetics. Reciprocally, there are evidences that CMAD contributes to the initiation and progression of T2D by; reducing insulin production, triggering insulin resistance directly or via altered GM, and inclined oxidative stress. The details about the above clues, causes and consequences of CMAD are obtained by searching literature spanning between 1955 and 2022. Finally, the molecular bases of CMAD are discussed in details by interpretation of an up-to-date data and aid of well constructed diagrams, with a conclusion unravelling that CMAD is a major player in T2D pathophysiology. To this end, the CMAD disclosure offers several therapeutic potentials for prevention, delay or attenuation of T2D and its complications.

Indexed as

AcidosisDiabetes Mellitus, Type 2Chronic DiseaseExtracellular SpaceGastrointestinal MicrobiomeHumansHydrogen-Ion ConcentrationIon TransportChronic metabolic acidosisGut microbiotaInsulin resistanceMitochondrial dysfunctionpHROST2D

Identifiers

PMID37380824
OpenAlexW4382362028

What OpenQuestion holds

Textmetadata
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.