Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 1253594

Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate


Lijović, Lada; Pelajić, Stipe; Hawchar, Fatime; Minev, Ivaylo; da Silva, Beatriz Helena Cermaria Soares; Angelucci, Alessandra; Ercole, Ari; de Grooth, Harm-Jan; Thoral, Patrick; Radočaj, Tomislav; Elbers, Paul
Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate // Journal of Critical Care, 75 (2023), 154276, 7 doi:10.1016/j.jcrc.2023.154276 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1253594 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate

Autori
Lijović, Lada ; Pelajić, Stipe ; Hawchar, Fatime ; Minev, Ivaylo ; da Silva, Beatriz Helena Cermaria Soares ; Angelucci, Alessandra ; Ercole, Ari ; de Grooth, Harm-Jan ; Thoral, Patrick ; Radočaj, Tomislav ; Elbers, Paul

Izvornik
Journal of Critical Care (0883-9441) 75 (2023); 154276, 7

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Acute kidney injuryEarly detectionGlomerular filtration rateKinetic eGFR

Sažetak
Introduction Accurate and actionable diagnosis of Acute Kidney Injury (AKI) ahead of time is important to prevent or mitigate renal insufficiency. The purpose of this study was to evaluate the performance of Kinetic estimated Glomerular Filtration Rate (KeGFR) in timely predicting AKI in critically ill septic patients. Methods We conducted a retrospective analysis on septic ICU patients who developed AKI in AmsterdamUMCdb, the first freely available European ICU database. The reference standard for AKI was the Kidney Disease: Improving Global Outcomes (KDIGO) classification based on serum creatinine and urine output (UO). Prediction of AKI was based on stages defined by KeGFR and UO. Classifications were compared by length of ICU stay (LOS), need for renal replacement therapy and 28-day mortality. Predictive performance and time between prediction and diagnosis were calculated. Results Of 2492 patients in the cohort, 1560 (62.0%) were diagnosed with AKI by KDIGO and 1706 (68.5%) by KeGFR criteria. Disease stages had agreement of kappa = 0.77, with KeGFR sensitivity 93.2%, specificity 73.0% and accuracy 85.7%. Median time to recognition of AKI Stage 1 was 13.2 h faster for KeGFR, and 7.5 h and 5.0 h for Stages 2 and 3. Outcomes revealed a slight difference in LOS and 28-day mortality for Stage 1. Conclusions Predictive performance of KeGFR combined with UO criteria for diagnosing AKI is excellent. Compared to KDIGO, deterioration of renal function was identified earlier, most prominently for lower stages of AKI. This may shift the actionable window for preventing and mitigating renal insufficiency.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti



POVEZANOST RADA


Profili:

Avatar Url Tomislav Radočaj (autor)

Avatar Url Lada Lijović (autor)

Poveznice na cjeloviti tekst rada:

doi www.sciencedirect.com

Citiraj ovu publikaciju:

Lijović, Lada; Pelajić, Stipe; Hawchar, Fatime; Minev, Ivaylo; da Silva, Beatriz Helena Cermaria Soares; Angelucci, Alessandra; Ercole, Ari; de Grooth, Harm-Jan; Thoral, Patrick; Radočaj, Tomislav; Elbers, Paul
Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate // Journal of Critical Care, 75 (2023), 154276, 7 doi:10.1016/j.jcrc.2023.154276 (međunarodna recenzija, članak, znanstveni)
Lijović, L., Pelajić, S., Hawchar, F., Minev, I., da Silva, B., Angelucci, A., Ercole, A., de Grooth, H., Thoral, P., Radočaj, T. & Elbers, P. (2023) Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate. Journal of Critical Care, 75, 154276, 7 doi:10.1016/j.jcrc.2023.154276.
@article{article, author = {Lijovi\'{c}, Lada and Pelaji\'{c}, Stipe and Hawchar, Fatime and Minev, Ivaylo and da Silva, Beatriz Helena Cermaria Soares and Angelucci, Alessandra and Ercole, Ari and de Grooth, Harm-Jan and Thoral, Patrick and Rado\v{c}aj, Tomislav and Elbers, Paul}, year = {2023}, pages = {7}, DOI = {10.1016/j.jcrc.2023.154276}, chapter = {154276}, keywords = {Acute kidney injuryEarly detectionGlomerular filtration rateKinetic eGFR}, journal = {Journal of Critical Care}, doi = {10.1016/j.jcrc.2023.154276}, volume = {75}, issn = {0883-9441}, title = {Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate}, keyword = {Acute kidney injuryEarly detectionGlomerular filtration rateKinetic eGFR}, chapternumber = {154276} }
@article{article, author = {Lijovi\'{c}, Lada and Pelaji\'{c}, Stipe and Hawchar, Fatime and Minev, Ivaylo and da Silva, Beatriz Helena Cermaria Soares and Angelucci, Alessandra and Ercole, Ari and de Grooth, Harm-Jan and Thoral, Patrick and Rado\v{c}aj, Tomislav and Elbers, Paul}, year = {2023}, pages = {7}, DOI = {10.1016/j.jcrc.2023.154276}, chapter = {154276}, keywords = {Acute kidney injuryEarly detectionGlomerular filtration rateKinetic eGFR}, journal = {Journal of Critical Care}, doi = {10.1016/j.jcrc.2023.154276}, volume = {75}, issn = {0883-9441}, title = {Diagnosing acute kidney injury ahead of time in critically ill septic patients using kinetic estimated glomerular filtration rate}, keyword = {Acute kidney injuryEarly detectionGlomerular filtration rateKinetic eGFR}, chapternumber = {154276} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font