P6531Evidence-practice gap in the preprocedural risk assessment for contrast-induced acute kidney injury

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
S Shoji ◽  
M Sawano ◽  
Y Shiraishi ◽  
N Ikemura ◽  
S Noma ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Acute Kidney Injury ◽  
Risk Score ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Acute Kidney Injury Network ◽  
Risk Scores ◽  
Risk Patients ◽  
Practice Gap ◽  
The Impact

Abstract Background Contrast-induced acute kidney injury (CI-AKI) is one of the frequently encountered and costly complications after percutaneous coronary intervention (PCI). Clinical practice guidelines strongly recommend that PCI patients should universally undergo preprocedural assessment for the risk of CI-AKI, and the contrast volume (CV) should be minimized to an achievable level, particularly among the high AKI risk patients. However, data on the CV use based on the comprehensive preprocedural risk assessment is still lacking. Purpose Our study aimed to 1) assess the impact of CV increase with the incidence of AKI among high AKI risk patients, and 2) retrospectively evaluate the used CV based on the preprocedural comprehensive risk assessment for patients undergoing PCI within multicenter longitudinal registry. Methods Between 2009 and 2018, 22,373 patients underwent PCI in 14 participating facilities, and consecutive patient data was registered. AKI was defined as a >0.3mg/dl absolute or >1.5-fold relative increase in post-PCI creatinine or new initiation of dialysis, based on the Acute Kidney Injury Network criteria. The post-procedural creatinine was defined as the highest value within 30 days after the indexed procedure. Congruent with the National Cardiovascular Data Registry (NCDR) definition, if more than 1 post-procedural creatinine level was measured, the highest value was used for determining AKI. We divided the patients into four groups according to quartile of NCDR AKI risk scores. Results Mean age of the patients were 68.7±11.1 years, and 79.1% were male. Mean CV use was 161.4±74.8ml. The incidence of CI-AKI was 8.9%, and was particularly high among high AKI risk patients (21.1%); CV (per 1ml linear increase) was directly associated with the occurrence of AKI (OR: 1.002 per unit in CV; 95% CI: 1.001–1.003; P<0.001) in these patients. CV during PCI decreased with the progression of chronic kidney disease (CKD), but it did not alter by the overall NCDR AKI risk score (Figure). After multivariable adjustment, CV was predicted by stage of CKD (−13.68ml; 95% CI: −12.05 to −15.30ml; P<0.001), but not by the value of pre-procedure prediction score (NCDR AKI risk score, P=0.575). CV according to CKD/NCDR AKI risk score Conclusions Higher CV was directly associated with the occurrence of AKI among higher AKI risk patients. However, CV use was largely influenced by the stage of renal disease, and not with overall patient risk presented by contemporary risk scores. Our results have identified an important evidence-practice gap and emphasizes the importance of total preprocedural assessment to minimize CV and prevent subsequent AKI. Acknowledgement/Funding KAKENHI (16KK0186, 16H05215, 25460630, 25460777), Bayer, Daiichi Sankyo, Bristol-Myers Squibb, Teikoku Seiyaku, Sumitomo Dainippon, AstraZeneka, Pfizer

scholarly journals Evidence‐to‐Practice Gap for Preventing Procedure‐Related Acute Kidney Injury in Patients Undergoing Percutaneous Coronary Intervention

2021 ◽  
Author(s):  
Satoshi Shoji ◽  
Mitsuaki Sawano ◽  
Alexander T. Sandhu ◽  
Paul A. Heidenreich ◽  
Yasuyuki Shiraishi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Chronic Kidney Disease ◽  
Acute Kidney Injury ◽  
Percutaneous Coronary Intervention ◽  
Risk Score ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Contrast Volume ◽  
Percutaneous Coronary ◽  
Baseline Renal Function

Background Acute kidney injury (AKI) is a common complication of percutaneous coronary intervention. This risk can be minimized with reduction of contrast volume via preprocedural risk assessment. We aimed to identify quality gaps for implementing the available risk scores introduced to facilitate more judicious use of contrast volume. Methods and Results We grouped 14 702 patients who underwent percutaneous coronary intervention according to the calculated NCDR (National Cardiovascular Data Registry) AKI risk score quartiles (Q1 [lowest]–Q4 [highest]). We compared the used contrast volume by the baseline renal function and NCDR AKI risk score quartiles. Factors associated with increased contrast volume usage were determined using multivariable linear regression analysis. The overall incidence of AKI was 8.9%. The used contrast volume decreased in relation to the stages of chronic kidney disease (168 mL [SD, 73.8 mL], 161 mL [SD, 75.0 mL], 140 mL [SD, 70.0 mL], and 120 mL [SD, 73.7 mL] for no, mild, moderate, and severe chronic kidney disease, respectively; P <0.001), albeit no significant correlation was observed with the calculated NCDR AKI risk quartiles. Of the variables included in the NCDR AKI risk score, anemia (7.31 mL [1.76–12.9 mL], P =0.01), heart failure on admission (10.2 mL [6.05–14.3 mL], P <0.001), acute coronary syndrome presentation (10.3 mL [7.87–12.7 mL], P <0.001), and use of an intra‐aortic balloon pump (17.7 mL [3.9–31.5 mL], P =0.012) were associated with increased contrast volume. Conclusions The contrast volume was largely determined according to the baseline renal function, not the patients' overall AKI risk. These findings highlight the importance of comprehensive risk assessment to minimize the contrast volume used in susceptible patients.

The Impact of Hemodynamic Transesophageal Echocardiography on Acute Kidney Injury Management and Use of Continuous Renal Replacement Therapy in Trauma

2020 ◽  
Vol 86 (3) ◽  
pp. 190-194
Author(s):  
Alex Sapp ◽  
Andrew Drahos ◽  
Madison Lashley ◽  
Amy Christie ◽  
D. Benjamin Christie
Keyword(s):  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Continuous Renal Replacement Therapy ◽  
Transesophageal Echocardiography ◽  
Replacement Therapy ◽  
Hospital Costs ◽  
Kidney Injury ◽  
Acute Kidney Injury Network ◽  
Trauma Patients ◽  
The Impact

Resuscitation of critically ill trauma patients can be precarious, and errors can cause acute kidney injuries. If renal failure develops, continuous renal replacement therapy (CRRT) may be necessary, but adds expense. Hemodynamic transesophageal echocardiography (hTEE) provides objective data to guide resuscitation. We hypothesized that hTEE use improved acute kidney injury (AKI) management, reserved CRRT use for more severe AKIs, and decreased cost and resource utilization. We retrospectively reviewed 2413 trauma patients admitted to a Level I trauma center's ICU between 2009 and 2015. Twenty-three patients required CRRT before standard hTEE use and 11 required CRRTafter; these are the “CRRT” and “CRRT/hTEE” groups, respectively. The hTEE group comprised 83 patients evaluated with hTEE, with AKI managed without CRRT. We compared the average creatinine, change in creatinine, and Acute Kidney Injury Network (AKIN) of “CRRT” with “CRRT/hTEE” and “hTEE.” We also analyzed several quality measures including ICU length of stay and cost. “CRRT” had a lower AKIN score (1.6) than “CRRT/hTEE” (2.9) ( P = 0.0003). “hTEE” had an AKIN score of 2.1 ( P = 0.0387). “CRRT” also had increased ICU days (25.1) compared with “CRRT/hTEE” (20.2) ( P = 0.014) and “hTEE” (16.8) ( P = 0.003). “CRRT” accrued on average $198,695.81 per patient compared with “CRRT/ hTEE” ($167,534.19) and “hTEE” ($53,929.01). hTEE provides valuable information to tailor resuscitation. At our institution, hTEE utilization reserved CRRT for worse AKIs and decreased hospital costs.

Poor-Risk Acute Leukemia Patients with An EBMT Low-Risk Score and An 8/8 Matched Unrelated Donor Show Excellent Survival After Hematopoietic Stem Cell Transplantation.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 1196-1196
Author(s):  
Tom Lodewyck ◽  
Machteld Oudshoorn ◽  
Bronno van der Holt ◽  
Eefke Petersen ◽  
Eric Spierings ◽  
...  
Keyword(s):  
High Resolution ◽  
Acute Leukemia ◽  
Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Unrelated Donor ◽  
Hematopoietic Stem ◽  
Poor Risk ◽  
Risk Patients ◽  
The Impact

Abstract Abstract 1196 Poster Board I-218 Introduction: Allogeneic hematopoietic stem cell transplantation (alloSCT) from volunteer unrelated donors (URD) may be associated with a higher non-relapse mortality (NRM) and worse outcome as compared to alloSCT using HLA-identical sibling donors. However, many parameters next to donor type define NRM. The impact on outcome of allele-matching for HLA-A, -B, -C and -DRB1 between donor and recipient has clearly been demonstrated. The prognostic impact of the EBMT risk score, that takes into account age, stage of disease, time from diagnosis to transplantation, donor type and donor-recipient gender combination, has recently been validated in a variety of hematological malignancies including acute leukemia and myelodysplastic syndrome (MDS). We evaluated the relative prognostic value of high-resolution HLA matching and the EBMT risk score for patients with poor-risk acute leukemia and MDS who received an URD transplant. Patients and methods: Between 1987 and 2006, 327 patients (≥16y) with poor-risk acute leukemia and MDS underwent URD alloSCT in the Netherlands. Patients were in 1st complete remission (CR1, n=129), 2nd CR (CR2, n=91), beyond CR2 or not in remission (n=107). The leukemia-risk was considered to be poor if patients had adverse cytogenetics or were not in CR1. The majority of the grafts was T-cell depleted (94%). High-resolution typing of HLA-A, -B, -C, and -DRB1 alleles was available for analysis in 270 donor-recipient pairs and had in part been performed retrospectively. Results: We evaluated the impact of high-resolution matching for HLA-A, -B, -C and -DRB1 on progression free survival (PFS) and overall survival (OS). Patients who were fully matched (8/8) with their donors (n=170) hadsignificantly superior PFS (40+/-4% vs 26+/-5%, hazard ratio (HR)=0.68; 95%CI 0.50–0.92, p=0.01) and OS (39+/-4% vs 29+/-5%, HR=0.70; 95%CI 0.51-0.96, p=0.03), compared to patients with mismatched (≤7/8) donors (n=100). Superior OS in the 8/8 group appeared to be due to a lower NRM (24+/-4% vs 39+/-5%, HR=0.54; 95%CI 0.35-0.85, p=0.008), while the relapse mortality rate was identical in both groups (37+/-4% vs 32+/-5%). Patients with EBMT risk scores of 1-2 (n=71), 3 (n=77), 4 (n=76) and 5-7 (n=103) had a predicted 5 year OS of 52%, 41% (HR=1.57; 95%CI 0.98-2.52), 29% (HR=2.07; 95%CI 1.32-3.26) and 19% (HR=2.69; 95%CI 1.76-4.11), respectively (p<0.001). Relapse mortality rate and NRM increased with increasing EBMT risk score. As shown in the table, the impact of allele-matching on OS was most evident in the EBMT low-risk group. EBMT low-risk (1-2) patients with 8/8 donors showed excellent 5 year OS compared to EBMT low-risk patients with ≤7/8 donors (73+/-8% vs 35+/-12%). The favorable impact of a fully matched donor was absent in patients with higher EBMT risk scores. Conclusions: Both the EBMT risk score and the degree of allele-matching independently predicted outcome after URD alloSCT. The predictive value of allele-matching was especially evident in EBMT low-risk patients, while patients with the highest EBMT risk scores (>4) had a dismal outcome, despite allele-matching. These results emphasize the importance of incorporating age, disease stage, donor-recipient gender combination and time interval from diagnosis to transplantation (EBMT risk score parameters) as well as high-resolution HLA-typing in the risk assessment prior to URD alloSCT. As excellent OS was noted in well matched EBMT low-risk patients, our data underscore the importance of an immediate search for an unrelated donor in poor-risk leukemia patients in CR1 below the age of 40, who should then receive their alloSCT as early consolidation therapy following induction chemotherapy. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Development and external validation of an acute kidney injury risk score for use in the general population

2020 ◽  
Vol 13 (3) ◽  
pp. 402-412
Author(s):  
Samira Bell ◽  
Matthew T James ◽  
Chris K T Farmer ◽  
Zhi Tan ◽  
Nicosha de Souza ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Risk Score ◽  
Validation Cohort ◽  
External Validation ◽  
Kidney Injury ◽  
Routinely Collected Data ◽  
C Statistic ◽  
Increased Risk ◽  
The Impact

Abstract Background Improving recognition of patients at increased risk of acute kidney injury (AKI) in the community may facilitate earlier detection and implementation of proactive prevention measures that mitigate the impact of AKI. The aim of this study was to develop and externally validate a practical risk score to predict the risk of AKI in either hospital or community settings using routinely collected data. Methods Routinely collected linked datasets from Tayside, Scotland, were used to develop the risk score and datasets from Kent in the UK and Alberta in Canada were used to externally validate it. AKI was defined using the Kidney Disease: Improving Global Outcomes serum creatinine–based criteria. Multivariable logistic regression analysis was performed with occurrence of AKI within 1 year as the dependent variable. Model performance was determined by assessing discrimination (C-statistic) and calibration. Results The risk score was developed in 273 450 patients from the Tayside region of Scotland and externally validated into two populations: 218 091 individuals from Kent, UK and 1 173 607 individuals from Alberta, Canada. Four variables were independent predictors for AKI by logistic regression: older age, lower baseline estimated glomerular filtration rate, diabetes and heart failure. A risk score including these four variables had good predictive performance, with a C-statistic of 0.80 [95% confidence interval (CI) 0.80–0.81] in the development cohort and 0.71 (95% CI 0.70–0.72) in the Kent, UK external validation cohort and 0.76 (95% CI 0.75–0.76) in the Canadian validation cohort. Conclusion We have devised and externally validated a simple risk score from routinely collected data that can aid both primary and secondary care physicians in identifying patients at high risk of AKI.

scholarly journals Development and internal validation of a prediction model for hospital-acquired acute kidney injury

2019 ◽  
Author(s):  
Catalina Martin-Cleary ◽  
Luis Miguel Molinero-Casares ◽  
Alberto Ortiz ◽  
Jose Miguel Arce-Obieta
Keyword(s):  
Acute Kidney Injury ◽  
Risk Score ◽  
Bayesian Model Averaging ◽  
Characteristic Curve ◽  
Tertiary Care ◽  
Kidney Injury ◽  
Risk Scores ◽  
Internal Validation ◽  
Clinical Records ◽  
Hospital Acquired

Abstract Background Predictive models and clinical risk scores for hospital-acquired acute kidney injury (AKI) are mainly focused on critical and surgical patients. We have used the electronic clinical records from a tertiary care general hospital to develop a risk score for new-onset AKI in general inpatients that can be estimated automatically from clinical records. Methods A total of 47 466 patients met inclusion criteria within a 2-year period. Of these, 2385 (5.0%) developed hospital-acquired AKI. Step-wise regression modelling and Bayesian model averaging were used to develop the Madrid Acute Kidney Injury Prediction Score (MAKIPS), which contains 23 variables, all obtainable automatically from electronic clinical records at admission. Bootstrap resampling was employed for internal validation. To optimize calibration, a penalized logistic regression model was estimated by the least absolute shrinkage and selection operator (lasso) method of coefficient shrinkage after estimation. Results The area under the curve of the receiver operating characteristic curve of the MAKIPS score to predict hospital-acquired AKI at admission was 0.811. Among individual variables, the highest odds ratios, all >2.5, for hospital-acquired AKI were conferred by abdominal, cardiovascular or urological surgery followed by congestive heart failure. An online tool (http://www.bioestadistica.net/MAKIPS.aspx) will facilitate validation in other hospital environments. Conclusions MAKIPS is a new risk score to predict the risk of hospital-acquired AKI, based on variables present at admission in the electronic clinical records. This may help to identify patients who require specific monitoring because of a high risk of AKI.

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