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3 results on '"Birnie, Kate"'

2. Accuracy of cystatin C for the detection of abnormal renal function in children undergoing chemotherapy for malignancy: a systematic review using individual patient data.

Author

Whiting, Penny, Birnie, Kate, Sterne, Jonathan A. C., Jameson, Catherine, Skinner, Rod, Phillips, Bob, The Cystatin C In Childhood Cancer Collaboration Group, and Cystatin C In Childhood Cancer Collaboration Group

Subjects
*CYSTATINS, *META-analysis, *KIDNEY glomerulus, *PHYSIOLOGICAL effects of chemotherapy, *CREATININE, *CHILDHOOD cancer
Abstract

Purpose: We conducted a systematic review and individual patient data (IPD) meta-analysis to examine the utility of cystatin C for evaluation of glomerular function in children with cancer.Methods: Eligible studies evaluated the accuracy of cystatin C for detecting poor renal function in children undergoing chemotherapy. Study quality was assessed using QUADAS-2. Authors of four studies shared IPD. We calculated the correlation between log cystatin C and GFR stratified by study and measure of cystatin C. We dichotomized the reference standard at GFR 80 ml/min/1.73m2 and stratified cystatin C at 1 mg/l, to calculate sensitivity and specificity in each study and according to age group (0-4, 5-12, and ≥ 13 years). In sensitivity analyses, we investigated different GFR and cystatin C cut points. We used logistic regression to estimate the association of impaired renal function with log cystatin C and quantified diagnostic accuracy using the area under the ROC curve (AUC).Results: Six studies, which used different test and reference standard thresholds, suggested that cystatin C has the potential to monitor renal function in children undergoing chemotherapy for malignancy. IPD data (504 samples, 209 children) showed that cystatin C has poor sensitivity (63%) and moderate specificity (89%), although use of a GFR cut point of < 60 ml/min/1.73m2 (data only available from two of the studies) estimated sensitivity to be 92% and specificity 81.3%. The AUC for the combined data set was 0.890 (95% CI 0.826, 0.951). Diagnostic accuracy appeared to decrease with age.Conclusions: Cystatin C has better diagnostic accuracy than creatinine as a test for glomerular dysfunction in young people undergoing treatment for cancer. Diagnostic accuracy is not sufficient for it to replace current reference standards for predicting clinically relevant impairments that may alter dosing of important nephrotoxic agents. [ABSTRACT FROM AUTHOR]

Published
2018
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3. Predictive models for kidney disease: improving global outcomes (KDIGO) defined acute kidney injury in UK cardiac surgery

Author

Birnie, Kate, Verheyden, Veerle, Pagano, Domenico, Bhabra, Moninder, Tilling, Kate, Sterne, Jonathan A, and Murphy, Gavin J

Subjects
Male, Models, Statistical, Research, Acute Kidney Injury, Middle Aged, Prognosis, urologic and male genital diseases, Critical Care and Intensive Care Medicine, United Kingdom, ROC Curve, Risk Factors, Creatinine, Humans, Female, Postoperative Period, Cardiac Surgical Procedures, Aged, Retrospective Studies
Abstract

Introduction Acute kidney injury (AKI) risk prediction scores are an objective and transparent means to enable cohort enrichment in clinical trials or to risk stratify patients preoperatively. Existing scores are limited in that they have been designed to predict only severe, or non-consensus AKI definitions and not less severe stages of AKI, which also have prognostic significance. The aim of this study was to develop and validate novel risk scores that could identify all patients at risk of AKI. Methods Prospective routinely collected clinical data (n = 30,854) were obtained from 3 UK cardiac surgical centres (Bristol, Birmingham and Wolverhampton). AKI was defined as per the Kidney Disease: Improving Global Outcomes (KDIGO) Guidelines. The model was developed using the Bristol and Birmingham datasets, and externally validated using the Wolverhampton data. Model discrimination was estimated using the area under the ROC curve (AUC). Model calibration was assessed using the Hosmer–Lemeshow test and calibration plots. Diagnostic utility was also compared to existing scores. Results The risk prediction score for any stage AKI (AUC = 0.74 (95% confidence intervals (CI) 0.72, 0.76)) demonstrated better discrimination compared to the Euroscore and the Cleveland Clinic Score, and equivalent discrimination to the Mehta and Ng scores. The any stage AKI score demonstrated better calibration than the four comparison scores. A stage 3 AKI risk prediction score also demonstrated good discrimination (AUC = 0.78 (95% CI 0.75, 0.80)) as did the four comparison risk scores, but stage 3 AKI scores were less well calibrated. Conclusions This is the first risk score that accurately identifies patients at risk of any stage AKI. This score will be useful in the perioperative management of high risk patients as well as in clinical trial design.

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