Risk prediction to inform surveillance of chronic kidney disease in the US Healthcare Safety Net: a cohort study

Xie, Yi; Maziarz, Marlena; Tuot, Delphine S.; Chertow, Glenn M.; Himmelfarb, Jonathan; Hall, Yoshio N.

doi:10.1186/s12882-016-0272-0

Cited by 9 publications

(8 citation statements)

References 37 publications

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“…These are available from the authors upon request. c The study by Xie [ 27 ] and Maziarz [ 29 ] includes the same patient population. Part of this population is included in Maziarz et al .…”

Section: Resultsmentioning

confidence: 99%

Towards the best kidney failure prediction tool: a systematic review and selection aid

Ramspek

Jong

Dekker

et al. 2019

Nephrology Dialysis Transplantation

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Background Prediction tools that identify chronic kidney disease (CKD) patients at a high risk of developing kidney failure have the potential for great clinical value, but limited uptake. The aim of the current study is to systematically review all available models predicting kidney failure in CKD patients, organize empirical evidence on their validity and ultimately provide guidance in the interpretation and uptake of these tools. Methods PubMed and EMBASE were searched for relevant articles. Titles, abstracts and full-text articles were sequentially screened for inclusion by two independent researchers. Data on study design, model development and performance were extracted. The risk of bias and clinical usefulness were assessed and combined in order to provide recommendations on which models to use. Results Of 2183 screened studies, a total of 42 studies were included in the current review. Most studies showed high discriminatory capacity and the included predictors had large overlap. Overall, the risk of bias was high. Slightly less than half the studies (48%) presented enough detail for the use of their prediction tool in practice and few models were externally validated. Conclusions The current systematic review may be used as a tool to select the most appropriate and robust prognostic model for various settings. Although some models showed great potential, many lacked clinical relevance due to being developed in a prevalent patient population with a wide range of disease severity. Future research efforts should focus on external validation and impact assessment in clinically relevant patient populations.

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Section: Resultsmentioning

confidence: 99%

Towards the best kidney failure prediction tool: a systematic review and selection aid

Ramspek

Jong

Dekker

et al. 2019

Nephrology Dialysis Transplantation

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“…It was generally observed that regardless of the model used, the predicted outcome included measurement of risk towards ESKD which were defined as [ 41 , 43 , 44 , 48 – 50 , 53 , 56 – 60 , 64 , 69 , 70 , 72 ]:…”

Section: Resultsmentioning

confidence: 99%

“…There were very few studies that had predicted outcomes such as progression from an earlier stage to a more severe stage of CKD, for example from stage 1 to stages 3 or 4 [ 54 , 56 ], and other predicted endpoints of stated percentage decline in eGFR levels [ 9 , 41 ]. Depending on the quality of the available dataset [ 59 , 60 ], the predicted outcome could also be combined with other variables such death, comorbidities, the type of dialysis and the time of diagnosis [ 46 , 59 , 68 ]. Some examples of outcomes that integrated these additional variables include, predicting the chances of future KRT at the time of CKD diagnosis [ 70 ]; a ≥ 50% decline in the eGFR from baseline [ 50 ] or an eGFR decline ≥30% from baseline [ 41 ]; the 5-year risk of KRT in CKD stage 3 and 4 [ 56 ]; the mortality and progression to ESKD over five years [ 65 ].…”

Section: Resultsmentioning

confidence: 99%

“…The eGFR formula was also not consistent across studies, 13 studies used the CKD Epidemiology Collaboration (CKD-EPI) equation [ 9 , 41 , 42 , 44 , 46 , 51 , 54 – 56 , 58 , 63 , 65 , 66 ] and 9 studies used the Modification of Diet in Renal Disease (MDRD) equation [ 43 , 45 , 47 , 49 , 53 , 60 , 62 , 64 , 71 ]. Two studies used unique equations customised for their specific cohort [ 48 , 69 ].…”

Section: Resultsmentioning

confidence: 99%

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Prediction models used in the progression of chronic kidney disease: A scoping review

et al. 2022

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Objective To provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD). Design Scoping review. Data sources Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022. Study selection All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression. Data extraction Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications. Results From 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models. Conclusions Researchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression.

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“…In cardiac surgical settings, CKD-patients are reported to have short life expectancy with renal dysfunction severity and are often associated with other medical problems compared to those without CKD [3,4]. Cardiac, pulmonary, metabolic, and hematological complications have a major effect on outcome after cardiac surgery [5,6] Our main aim was to investigate the association between stratum of renal impairment with the outcome of morbidity and mortality during peri-operative period of isolated mitral valve replacement; and to identify further the degree of renal failure at time of prosthetic mitral valve replacement going to affect the outcomes of surgery.…”

Section: Introductionmentioning

confidence: 99%

Outcome stratification of patients with impaired renal functions after isolated prosthetic mitral valve replacement

Hassan¹,

Elbadawi²,

Elsayed³

et al. 2021

GSC Adv. Res. Rev.

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Objectives: Patients with impaired renal functions have a variable risk of morbidity and mortality in cardiovascular surgery. Poor outcome was reported among patients who underwent valve surgery. Current study is presumed to compare the early outcomes of patients having different degrees of impaired renal functions and undergoing mitral valve replacement surgery. Methods: 135 patients were admitted into the three highly specialized centers in Cairo and Ismailia–Egypt between Dec.2018 and Jan.2020 Preoperative, intraoperative and early post-operative data were recorded. Impairment may present as one of these strata: early reversible (G1-2 included strata 1 & 2 kidney disease patients), moderate G3-4 included strata 3 & 4 kidney disease patients) or advanced irreversible renal damage. (The 5th stratum or G5-KD included end stage renal disease patients undergoing 4-hour hemodialysis sessions, three times a week, with bicarbonate dialysate). We correlated outcome among each stratum with cardiac and renal functions in that stratum. Results: The more is the impairment of renal functions at any peri- operative stage, the longer is the need for prolonged mechanical ventilation and the longer is the hospital stay. We found that levels of serum creatinine were significantly increased postoperatively Also, the more is the reversibility of the renal impairment, even by renal dialysis, the much better is the outcome (P=.0019). We also found insignificant difference between different strata of irreversible renal impairment in the early outcome of the prosthetic mitral valve replacement surgery. The early reversible damage can be repaired peri-operatively. Conclusions: Prosthetic mitral valve replacement among patients with different degrees of impaired renal functions is not only feasible but also it does not seem to add any more deterioration into renal function. Prolonged mechanical ventilation and hospital stay are the only drawbacks of irreversibly impaired renal damage by dialysis or renal transplant.

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Risk prediction to inform surveillance of chronic kidney disease in the US Healthcare Safety Net: a cohort study

Cited by 9 publications

References 37 publications

Towards the best kidney failure prediction tool: a systematic review and selection aid

Towards the best kidney failure prediction tool: a systematic review and selection aid

Prediction models used in the progression of chronic kidney disease: A scoping review

Outcome stratification of patients with impaired renal functions after isolated prosthetic mitral valve replacement

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