Evidence map›Paper›PMID 37118662›Full record

ArticleBMC cardiovascular disorders2023

Association between albumin corrected anion gap and 30-day all-cause mortality of critically ill patients with acute myocardial infarction: a retrospective analysis based on the MIMIC-IV database.

Linhao Jian, Zhixiang Zhang, Quan Zhou, Xiangjie Duan, Haiqin Xu, Liangqing Ge

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Albumin-corrected anion gap and risk of mortality among US adults.Archives of public health = Archives belges de sante publique · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

6 authors.

Linhao JianDepartment of the First Clinical College, Jinan University, 601 Huangpu Avenue West, Guangzhou, 510632, China.
Zhixiang ZhangDepartment of Cardiology, The First People's Hospital of Changde, 818 Renmin Avenue, Changde City, 415003, China.
Quan ZhouDepartment of Science and Education, The First People's Hospital of Changde, 818 Renmin Avenue, Changde City, 415003, China.
Xiangjie DuanDepartment of Infectious Diseases, The First People's Hospital of Changde, 818 Renmin Avenue, Changde City, 415003, China.
Haiqin XuDepartment of Cardiac Electrophysiology, The First People's Hospital of Changde, 818 Renmin Avenue, Changde City, 415003, China.
Liangqing GeDepartment of Cardiology, The First People's Hospital of Changde, 818 Renmin Avenue, Changde City, 415003, China. geliangqing@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe anion gap (AG) has been linked to the prognosis of many cardiovascular disorders. However, the correlation between albumin-corrected anion gap (ACAG) and 30 d all-cause mortality of intensive care patients with acute myocardial infarction (AMI) is unclear. Furthermore, owing to the lack of studies, it is also unknown whether ACAG is more accurate than AG in predicting the mortality of AMI.

methodsThe Medical Information Mart for Intensive Care IV (MIMIC IV) dataset was used to provide patient data in this retrospective cohort study. ACAG is computed using the formulae: [4.4-{albumin (g/dl)}] × 2.5 + AG. The primary outcome was 30 d all-cause mortality intensive care patients with AMI. To explore the prognostic worthiness of ACAG, the receiver operating characteristic curve, smooth curve fitting, Cox regression model, and Kaplan survival analysis was performed.

resultsWe enrolled 2,160 patients in this study. ACAG had a better predictive value for 30 d all-cause mortality than AG, with an area under the curve of 0.66. The association between ACAG levels and overall mortality was nonlinear. In our model, after correcting for confounding factors, the ACAG was the independent predictor for 30 d all-cause mortality (HR 1.75, 95%CI 1.24, 2.47). ACAG K-M estimator curve analyses revealed that the group with ACAG ≥ 21.75 mmol/l had poor survival rate than the other group.

conclusionsHigh serum ACAG levels were a significant risk factor for 30 d all-cause mortality in critically ill patients with AMI. ACAG concentration and 30 d all-cause mortality had a nonlinear relationship. ACAG had better predictive value in identifying 30 d all-cause mortality of patients with AMI in ICU than the AG.

Indexed as

Acid-Base EquilibriumMyocardial InfarctionAlbuminsCritical IllnessHumansRetrospective StudiesAlbumins30 d all-cause mortalityACAGAcute myocardial infarctionCardiovascular disorderMIMIC IV

Identifiers

PMID37118662
PMCPMC10148465

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.