Recurrent Acute Kidney Injury in Renal Transplant Patients: A Single-Center Study

Bardak, Simge; Turgutalp, Kenan; Türkegün, Merve; Demir, Serap; Kıykım, Ahmet

doi:10.1016/j.transproceed.2015.04.077

Cited by 8 publications

(8 citation statements)

References 13 publications

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“… 24 , 54 Third, despite the relatively small sample size (n = 315 patients), this is the largest study, that we are aware of, to examine AKI in the kidney transplant population defined by serum creatinine values rather than administrative codes. 16 , 17 , 55 Moreover, this was a high-risk population with a high event rate. Last, all of the variables included in our risk score are objective and readily available to clinicians.…”

Section: Discussionmentioning

confidence: 91%

Derivation of a Predictive Model for Graft Loss Following Acute Kidney Injury in Kidney Transplant Recipients

Molnar

Walraven

Fergusson

et al. 2017

Can J Kidney Health Dis

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Background:Acute kidney injury (AKI) is common in the kidney transplant population.Objective:To derive a multivariable survival model that predicts time to graft loss following AKI.Design:Retrospective cohort study using health care administrative and laboratory databases.Setting:Southwestern Ontario (1999-2013) and Ottawa, Ontario, Canada (1996-2013).Patients:We included first-time kidney only transplant recipients who had a hospitalization with AKI 6 months or greater following transplant.Measurements:AKI was defined using the Acute Kidney Injury Network criteria (stage 1 or greater). The first episode of AKI was included in the analysis. Graft loss was defined by return to dialysis or repeat kidney transplant.Methods:We performed a competing risk survival regression analysis using the Fine and Gray method and modified the model into a simple point system. Graft loss with death as a competing event was the primary outcome of interest.Results:A total of 315 kidney transplant recipients who had a hospitalization with AKI 6 months or greater following transplant were included. The median (interquartile range) follow-up time was 6.7 (3.3-10.3) years. Graft loss occurred in 27.6% of the cohort. The final model included 6 variables associated with an increased risk of graft loss: younger age, increased severity of AKI, failure to recover from AKI, lower baseline estimated glomerular filtration rate, increased time from kidney transplant to AKI admission, and receipt of a kidney from a deceased donor. The risk score had a concordance probability of 0.75 (95% confidence interval [CI], 0.69-0.82). The predicted 5-year risk of graft loss fell within the 95% CI of the observed risk more than 95% of the time.Limitations:The CIs of the estimates were wide, and model overfitting is possible due to the limited sample size; the risk score requires validation to determine its clinical utility.Conclusions:Our prognostic risk score uses commonly available information to predict the risk of graft loss in kidney transplant patients hospitalized with AKI. If validated, this predictive model will allow clinicians to identify high-risk patients who may benefit from closer follow-up or targeted enrollment in future intervention trials designed to improve outcomes.

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Section: Discussionmentioning

confidence: 91%

Derivation of a Predictive Model for Graft Loss Following Acute Kidney Injury in Kidney Transplant Recipients

Molnar

Walraven

Fergusson

et al. 2017

Can J Kidney Health Dis

View full text Add to dashboard Cite

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“…Alternatively, this may have been due to a lack of power given our relatively small sample size or the exclusion of certain very high-risk populations (e.g., those with advanced heart failure or liver failure) from the overall population. A similar study examined predictors of recurrent AKI after renal transplantation [ 15 ] and was unable to identify any risk factors, while other studies have mostly focused on predictors of a second hospitalization with AKI, rather than a second episode during a single hospitalization [ 16 ].…”

Section: Discussionmentioning

confidence: 99%

Duration of acute kidney injury in critically ill patients

Federspiel

Itenov

Mehta

et al. 2018

Ann. Intensive Care

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BackgroundDuration of acute kidney injury (AKI) has been recognized a risk factor for adverse outcomes following AKI. We sought to examine the relationship of AKI duration and recurrent AKI with short-term outcomes in critically ill patients who were mechanically ventilated and met criteria for the acute respiratory distress syndrome.MethodsParticipants in the NHLBI ARDS Network SAILS multicenter trial who developed AKI were included in this analysis and divided into groups based on AKI duration. Differences in outcomes were evaluated using t test and Chi-square test. Competing risks regression and Cox regression were used to evaluate factors associated with resolving AKI and recurrent AKI.ResultsIn total, 238 patients were included in the study. Seventy-seven patients had short duration AKI (1–2 days), 47 medium duration AKI (3–7 days), 87 persistent AKI (> 7 days) and 38 died during their AKI episode. Persistent AKI was associated with worse outcomes including increased ICU length of stay, time on the ventilator and days with cardiovascular failure. We found no clinical differences between patients with short and medium duration AKI, even when accounting for AKI severity and recurrent AKI. Patients with resolving AKI were less likely to have oliguria or moderate/severe ARDS on the day AKI criteria were met. Recurrent AKI was associated with poorer clinical outcomes. No baseline clinical factors were found to predict development of recurrent AKI.ConclusionsIn critically ill patients with sepsis-associated ARDS and AKI, the impact of short and medium duration AKI on clinical outcomes was modest. Persistent and recurrent AKI were both associated with worse clinical outcomes, emphasizing the importance of identifying these patients, who may benefit from novel interventions.Electronic supplementary materialThe online version of this article (10.1186/s13613-018-0374-x) contains supplementary material, which is available to authorized users.

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“…The code performed poorly when a code type of “main or most responsible diagnosis” was used. This could be due to the fact that AKI often occurs in the setting of another illness, such as an infection [ 9 , 19 ], which may be coded as the main diagnosis as opposed to AKI. The positive predictive value of the code was quite variable depending on the reference standard used.…”

Section: Discussionmentioning

confidence: 99%

Validation of Administrative Database Codes for Acute Kidney Injury in Kidney Transplant Recipients

Molnar

Walraven

McArthur

et al. 2016

Can J Kidney Health Dis

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BackgroundValidation studies of acute kidney injury (AKI) diagnostic codes performed in the general population have shown poor sensitivity, but the accuracy of such codes in the kidney transplant population remains unknown.ObjectiveThe objective of this study is to determine the accuracy of AKI diagnostic codes in kidney transplant recipients. We hypothesized that the sensitivity of diagnostic codes would be significantly greater in the kidney transplant population since these patients are closely followed by nephrologists and are more likely to have serum creatinine measured.DesignThe design is a population-based retrospective cohort study using healthcare administrative and laboratory databases.SettingThe setting is in Southwestern Ontario and Ottawa, Ontario, Canada, from 2003 to 2012.PatientsWe included first-time kidney transplant recipients admitted to hospital for whom serum creatinine was measured in hospital and within 6 months prior (n = 524).MethodsPatients meeting the Acute Kidney Injury Network (AKIN) classification serum creatinine change criteria were classified as having AKI. We determined the sensitivity, specificity, and negative and positive predictive values for the ICD-10-CA code for AKI when present as an admission diagnosis, most responsible diagnosis, or any diagnosis compared to a reference standard of AKI defined by the AKIN criteria (stage 1 or greater, stage 2 or greater, or stage 3).ResultsForty-five percent of included kidney transplant patients had a diagnosis of AKI. The most sensitive coding algorithm (reference standard AKIN stage 2 or greater, ICD-10 code present as any diagnosis) had a sensitivity of 42.1 % (95 % CI 31.7, 53.3), a specificity of 90.6 % (95 % CI 87.6, 93.0), and a positive likelihood ratio of 4.5. The median (IQR) rise in serum creatinine from baseline in patients with and without AKI codes was 104 (57 to 158) μmol/L and 16 (−3 to 41) μmol/L, respectively (Mann-Whitney test, p < 0.0001).LimitationsThe low sensitivity of the AKI code may be due to an alternative diagnosis of acute rejection being assigned in certain cases. The cause of AKI could not be determined.ConclusionsSimilar to the general population, the ICD-10 N17x code misses many kidney transplant patients with AKI during their hospitalization. This makes the code unusable for studying the incidence and consequences of AKI in hospitalized kidney transplant patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s40697-016-0108-7) contains supplementary material, which is available to authorized users.

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Recurrent Acute Kidney Injury in Renal Transplant Patients: A Single-Center Study

Cited by 8 publications

References 13 publications

Derivation of a Predictive Model for Graft Loss Following Acute Kidney Injury in Kidney Transplant Recipients

Derivation of a Predictive Model for Graft Loss Following Acute Kidney Injury in Kidney Transplant Recipients

Duration of acute kidney injury in critically ill patients

Validation of Administrative Database Codes for Acute Kidney Injury in Kidney Transplant Recipients

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