Evidence map›Paper›PMID 38883704›Full record

ArticleInternational journal of general medicine2024

Inflammation-Associated Tubulopathy in Patients with Acute Bacterial Infections.

Tal Levinson, Shani Shenhar-Tsarfaty, Ayelet Grupper, Tamar Witztum, Shlomo Berliner, Moshe Shtark

Abstract read
In one paragraph

Article in International journal of general medicine, 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

6 authors.

Tal LevinsonFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0003-0364-7128
Shani Shenhar-TsarfatyFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Ayelet GrupperFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Tamar WitztumFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Shlomo BerlinerFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Moshe ShtarkFaculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute kidney injury associated with the underlying inflammatory process of an acute bacterial infection affects patient morbidity and mortality. Clinicians use creatinine and estimated glomerular filtration rate (EGFR) to assess this renal injury, however, these measures may lag behind and change only once significant kidney injury has occurred. Neutrophil gelatinase-associated lipocalin (NGAL) is up-regulated by inflammation and infection and may serve as an early detection biomarker of kidney injury. Methods: Patients hospitalized with bacterial infections were assessed demographically, clinically and had their creatinine levels, EGFR and inflammatory biomarker levels, including urinary NGAL measured. Findings were compared between controls and patients across different EGFRs. Results: Fifty-one participants were included in the study. Among this cohort, 31 suffered bacterial infection. Inflammatory biomarkers including urinary NGAL were found to be higher in the infection group compared to the control group. Urinary NGAL level was significantly higher across all EGFRs of patients diagnosed with infection, including those with normal EGFR. Conclusion: Urinary NGAL identifies early kidney damage associated with bacterial infection even at normal EGFR and alerts the treating physician to undertake the necessary measures to mitigate the renal injury.

Indexed as

acute kidney injurybacterial infectionestimated glomerular filtration rateinflammationurinary NGAL

Identifiers

PMID38883704
PMCPMC11178074

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Registered trials

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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.