Literature DB >> 30446014

Prediction of acute kidney injury in intensive care unit patients.

Rui-Juan Guo1, Fu-Shan Xue2, Liu-Jia-Zi Shao1.   

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Year:  2018        PMID: 30446014      PMCID: PMC6240211          DOI: 10.1186/s13054-018-2248-x

Source DB:  PubMed          Journal:  Crit Care        ISSN: 1364-8535            Impact factor:   9.097


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In their recent article assessing the predictive ability of urinary liver-type fatty-acid binding protein and serum N-terminal pro-B-type natriuretic peptide for acute kidney injury (AKI) in patients treated at a medical cardiac intensive care unit (ICU), Naruse et al. [1] did not provide any severity score, such as the APACHE II score or the SOFA score. The available evidence shows that patients’ severity of illness and level of organ failure upon admission to the ICU are independently associated with the occurrence of AKI [2, 3]. Furthermore, it was unclear whether the serum creatinine levels used for diagnosis of AKI had been corrected based on fluid balance. It has been shown that not adjusting serum creatinine levels for fluid balance can underestimate the incidence and severity of AKI in the ICU patients, as a positive fluid balance can dilute serum creatinine [4]. Finally, the discriminative ability of risk prediction models for AKI was assessed by c-statistic, but the calibration was not performed with the Hosmer-Lemeshow test. The calibration assesses the ability of a prediction model to match the number of actual events across deciles of risk-stratified subgroups. A P < 0.05 indicates poor calibration of the prediction model or a lack of fit between two models [5].
  5 in total

1.  Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

Authors:  Ryan P Merkow; Bruce L Hall; Mark E Cohen; Justin B Dimick; Edward Wang; Warren B Chow; Clifford Y Ko; Karl Y Bilimoria
Journal:  J Am Coll Surg       Date:  2012-03-21       Impact factor: 6.113

2.  Acute Kidney Injury in Elderly Patients in Thai-Surgical Intensive Care Units (THAI-SICU) Study.

Authors:  Konlawij Trongtrakul; Sujaree Poopipatpab; Chawika Pisitsak; Kaweesak Chittawatanarat; Sunthiti Morakul
Journal:  J Med Assoc Thai       Date:  2016-09

3.  Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients.

Authors:  Etienne Macedo; Josée Bouchard; Sharon H Soroko; Glenn M Chertow; Jonathan Himmelfarb; T Alp Ikizler; Emil P Paganini; Ravindra L Mehta
Journal:  Crit Care       Date:  2010-05-06       Impact factor: 9.097

4.  Epidemiological characteristics of and risk factors for patients with postoperative acute kidney injury: a multicenter prospective study in 30 Chinese intensive care units.

Authors:  Yu Zhang; Li Jiang; Baomin Wang; Xiuming Xi
Journal:  Int Urol Nephrol       Date:  2018-02-26       Impact factor: 2.370

5.  Predicting acute kidney injury using urinary liver-type fatty-acid binding protein and serum N-terminal pro-B-type natriuretic peptide levels in patients treated at medical cardiac intensive care units.

Authors:  Hiroyuki Naruse; Junnichi Ishii; Hiroshi Takahashi; Fumihiko Kitagawa; Hideto Nishimura; Hideki Kawai; Takashi Muramatsu; Masahide Harada; Akira Yamada; Sadako Motoyama; Shigeru Matsui; Mutsuharu Hayashi; Masayoshi Sarai; Eiichi Watanabe; Hideo Izawa; Yukio Ozaki
Journal:  Crit Care       Date:  2018-08-18       Impact factor: 9.097

  5 in total
  1 in total

1.  Authors' response to letter "Prediction of acute kidney injury in intensive care unit patients".

Authors:  Hiroyuki Naruse; Hiroshi Takahashi; Junnichi Ishii
Journal:  Crit Care       Date:  2019-02-19       Impact factor: 9.097

  1 in total

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