ArticleJournal of clinical laboratory analysis2021
Analysis of the diagnostic capabilities of urinary neutrophil gelatinase-associated lipocalin and serum procalcitonin for acute kidney injury at the early stage of critical care intensive care unit admission.
Article in Journal of clinical laboratory analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.
- Right Heart Function in Cardiorenal Syndrome.Current heart failure reports · 2022Pooled it
- Comparative accuracy of biomarkers for the prediction of hospital-acquired acute kidney injury: a systematic review and meta-analysis.Critical care (London, England) · 2022Pooled it
- An early warning model for predicting major adverse kidney events within 30 days in acute pancreatitis patients.Renal failure · 2024Article
- Article
- Urinary neutrophil gelatinase-associated lipocalin predicted to contrast-associated acute kidney injury after planned percutaneous coronary intervention in elderly patients.Journal of clinical laboratory analysis · 2022Article
- Biomarkers in Cardiorenal Syndrome.Journal of clinical medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute kidney injury (AKI) is a disease that negatively affects patient prognosis and requires early diagnosis and treatment. Biomarkers that predict AKI are needed for early diagnosis of this disease.
methodsWe compared the AKI group and the non-AKI group in patients who were admitted to our critical care intensive care unit (ICU) and conducted a comparative study focusing on urinary neutrophil gelatinase-associated lipocalin (U-NGAL) and serum procalcitonin (PCT).
resultsSeventy-one out of 106 ICU inpatients were diagnosed with AKI in accordance with the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Among the patients who were diagnosed with AKI stages 1 to 3, 94.4% of all patients reached the maximum stage by day 5 after admission. Comparing the non-AKI group and AKI stage 1 to 3 on days 1 to 3 after admission, U-NGAL and PCT levels in the stage 3 group were significantly higher than those in the non-AKI group. Additionally, in receiver operating characteristic curve (ROC) analysis on days 1-3 after admission, U-NGAL and PCT levels can be used as biomarkers for the diagnosis of AKI, and in particular, AKI stage 3 can be predicted and diagnosed with high accuracy. U-NGAL and PCT levels were also significantly higher in AKI due to sepsis and acute pancreatitis and due to sepsis, respectively.
conclusionsMeasuring U-NGAL and PCT levels as biomarkers for AKI may further improve the accuracy of AKI diagnosis in critical care ICU.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.