Literature DB >> 10661477

Prognostic value of a new scoring system for hospital mortality in acute renal failure.

R L Lins1, M Elseviers, R Daelemans, P Zachée, P Zachée, E Gheuens, S Lens, M E De Broe.   

Abstract

AIM AND METHODS: In order to define a prognostic scoring system for hospital mortality of individual patients with acute renal failure (ARF), data were collected prospectively in a single centre study (Stuivenberg General Hospital, Antwerp, Belgium) on 197 adult patients consecutively admitted to the intensive care unit (ICU) during one year. Mean age was 69.8 (+/- 14.7), male/female ratio was 118/79.
RESULTS: Hospital mortality was 53%, 26% of the patients who were treated with renal replacement therapy. For developing the model all parameters showing a significant difference between survivors and non-survivors were entered in the multivariate analysis. Two SHARF scores (= Stuivenberg Hospital Acute Renal Failure scores) were developed, one at the time of diagnosis of ARF (T0) and the other 48 hours later (T48): SHARF T0 (7 x age) + (6 x alb0) + (3 x PTT0) + (39 x vent0) + (9 x heartf0) + 52 SHARF T48 (7 x age) + (6 x alb0) + (3 x PTT0) + (43 x vent48) + (16 x heartf48) + 52 age, albumin (alb0) and prothrombine time (PTT0) at T0 are expressed as categories, respiratory support (vent) and heart failure (heartf) at T0 and T48 are presented as absent (0) or present (1). In the linear regression model, r2 was, respectively, 0.36 and 0.43. The area under the receiver operator characteristic (ROC) curves, judging the discrimination ability between survivors and non-survivors, for T0 and T48 were, respectively, 0.87 and 0.90. The Hosmer-Lemeshow goodness-of-fit C statistic for T0 was C = 8.47; df8; p = 0.3 89 and for T48 C = 11.05; df = 8; p = 0.199.
CONCLUSION: We conclude that this scoring system, developed for all types of ARF, compares favorably with published scores and can become useful as a bedside tool for predicting hospital mortality in individual patients. A second measuring point increased the predictive value of the model. The results have to be confirmed in an ongoing prospective multicentre study.

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Year:  2000        PMID: 10661477

Source DB:  PubMed          Journal:  Clin Nephrol        ISSN: 0301-0430            Impact factor:   0.975


  15 in total

1.  Outcome of acute kidney injury with different treatment options: long-term follow-up.

Authors:  An M Van Berendoncks; Monique M Elseviers; Robert L Lins
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2.  Prognosis for children with acute kidney injury in the intensive care unit.

Authors:  Nilzete Bresolin; Carlos Silva; Ana Halllal; Julio Toporovski; Vera Fernandes; Jose Góes; Francisca Ligia Carvalho
Journal:  Pediatr Nephrol       Date:  2008-12-03       Impact factor: 3.714

3.  Prognostic indicators of patients with acute kidney injury in intensive care unit.

Authors:  Hai-Peng Shi; Dao-Miao Xu; Guo-En Wang
Journal:  World J Emerg Med       Date:  2010

4.  Pathological factors related to lymph node metastasis of submucosally invasive gastric cancer: criteria for additional gastrectomy after endoscopic resection.

Authors:  Mototsugu Fujii; Yutaro Egashira; Hiroshi Akutagawa; Tsukasa Nishida; Toshikatsu Nitta; Go Edagawa; Yoshitaka Kurisu; Yuro Shibayama
Journal:  Gastric Cancer       Date:  2012-11-23       Impact factor: 7.370

5.  Renal replacement therapy is an independent risk factor for mortality in critically ill patients with acute kidney injury.

Authors:  Monique M Elseviers; Robert L Lins; Patricia Van der Niepen; Eric Hoste; Manu L Malbrain; Pierre Damas; Jacques Devriendt
Journal:  Crit Care       Date:  2010-12-01       Impact factor: 9.097

6.  Predicting one-year mortality of critically ill patients with early acute kidney injury: data from the prospective multicenter FINNAKI study.

Authors:  Meri Poukkanen; Suvi T Vaara; Matti Reinikainen; Tuomas Selander; Sara Nisula; Sari Karlsson; Ilkka Parviainen; Juha Koskenkari; Ville Pettilä
Journal:  Crit Care       Date:  2015-03-27       Impact factor: 9.097

Review 7.  Utilizing electronic health records to predict acute kidney injury risk and outcomes: workgroup statements from the 15(th) ADQI Consensus Conference.

Authors:  Scott M Sutherland; Lakhmir S Chawla; Sandra L Kane-Gill; Raymond K Hsu; Andrew A Kramer; Stuart L Goldstein; John A Kellum; Claudio Ronco; Sean M Bagshaw
Journal:  Can J Kidney Health Dis       Date:  2016-02-26

8.  Case mix, outcome and activity for patients with severe acute kidney injury during the first 24 hours after admission to an adult, general critical care unit: application of predictive models from a secondary analysis of the ICNARC Case Mix Programme database.

Authors:  Nitin V Kolhe; Paul E Stevens; Alex V Crowe; Graham W Lipkin; David A Harrison
Journal:  Crit Care       Date:  2008-10-13       Impact factor: 9.097

9.  Incidence, clinical predictors and outcome of acute renal failure among North Indian trauma patients.

Authors:  Arulselvi Subramanian; Ravindra Mohan Pandey; Chhavi Sawhney; Ashish Dutt Upadhayay; Venencia Albert
Journal:  J Emerg Trauma Shock       Date:  2013-01

Review 10.  Acute Kidney Injury Recognition and Management: A Review of the Literature and Current Evidence.

Authors:  Syed Raza Shah; Sameer Altaf Tunio; Mohammad Hussham Arshad; Zorays Moazzam; Komal Noorani; Anushe Mohsin Feroze; Maham Shafquat; Huma Syed Hussain; Syed Ali Hyder Jeoffrey
Journal:  Glob J Health Sci       Date:  2015-09-18
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