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Importance: Contrast-associated acute kidney injury (AKI) is a common complication of coronary angiography and percutaneous coronary intervention (PCI) that has been associated with high costs and adverse long-term outcomes.Objective: To determine whether a multifaceted intervention is effective for the prevention of AKI after coronary angiography or PCI.Design, Setting, and Participants: A stepped-wedge, cluster randomized clinical trial was conducted in Alberta, Canada, that included all invasive cardiologists at 3 cardiac catheterization laboratories who were randomized to various start dates for the intervention between January 2018 and September 2019. Eligible patients were aged 18 years or older who underwent nonemergency coronary angiography, PCI, or both; who were not undergoing dialysis; and who had a predicted AKI risk of greater than 5%. Thirty-four physicians performed 7820 procedures among 7106 patients who met the inclusion criteria. Participant follow-up ended in November 2020.Interventions: During the intervention period, cardiologists received educational outreach, computerized clinical decision support on contrast volume and hemodynamic-guided intravenous fluid targets, and audit and feedback. During the control (preintervention) period, cardiologists provided usual care and did not receive the intervention.Main Outcomes and Measures: The primary outcome was AKI. There were 12 secondary outcomes, including contrast volume, intravenous fluid administration, and major adverse cardiovascular and kidney events. The analyses were conducted using time-adjusted models.Results: Of the 34 participating cardiologists who were divided into 8 clusters by practice group and center, the intervention group included 31 who performed 4327 procedures among 4032 patients (mean age, 70.3 [SD, 10.7] years; 1384 were women [32.0%]) and the control group included 34 who performed 3493 procedures among 3251 patients (mean age, 70.2 [SD, 10.8] years; 1151 were women [33.0%]). The incidence of AKI was 7.2% (310 events after 4327 procedures) during the intervention period and 8.6% (299 events after 3493 procedures) during the control period (between-group difference, -2.3% [95% CI, -0.6% to -4.1%]; odds ratio [OR], 0.72 [95% CI, 0.56 to 0.93]; P = .01). Of 12 prespecified secondary outcomes, 8 showed no significant difference. The proportion of procedures in which excessive contrast volumes were used was reduced to 38.1% during the intervention period from 51.7% during the control period (between-group difference, -12.0% [95% CI, -14.4% to -9.4%]; OR, 0.77 [95% CI, 0.65 to 0.90]; P = .002). The proportion of procedures in eligible patients in whom insufficient intravenous fluid was given was reduced to 60.8% during the intervention period from 75.1% during the control period (between-group difference, -15.8% [95% CI, -19.7% to -12.0%]; OR, 0.68 [95% CI, 0.53 to 0.87]; P = .002). There were no significant between-group differences in major adverse cardiovascular events or major adverse kidney events.Conclusions and Relevance: Among cardiologists randomized to an intervention including clinical decision support with audit and feedback, patients undergoing coronary procedures during the intervention period were less likely to develop AKI compared with those treated during the control period, with a time-adjusted absolute risk reduction of 2.3%. Whether this intervention would show efficacy outside this study setting requires further investigation.Trial Registration: ClinicalTrials.gov Identifier: NCT03453996. [ABSTRACT FROM AUTHOR]

A study was conducted to evaluate whether or not there was an increase in nephrology visits and health care resource use before and after reporting on estimated glomerular filtration rate (GFR). Results indicated that there was an increase in such visits following GFR reporting.

A study was conducted to evaluate the relationship between reduced kidney function, proteinuria, and adverse clinical outcomes. Results indicated that patients with heavy proteinuria were found to have more adverse outcomes as compared to those with a given level of kidney function.

Importance: Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up.Objective: To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease.Design, Setting, and Participants: Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013).Exposures: Demographic, laboratory, and comorbidity variables measured prior to discharge.Main Outcomes and Measures: Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year.Results: The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%).Conclusions and Relevance: A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research. [ABSTRACT FROM AUTHOR]

The article focuses on a study to determine the association of age with the likelihood of treatment of kidney failure. A community-based cohort study of adults in Alberta, Canada, who had outpatient estimated glomerular filtration rate measured between May 1, 2002 and March 31, 2008 and who did not require renal replacement therapy at baseline, was conducted. Main outcomes included adjusted rates of treated kidney failure, untreated kidney failure and death. The study concluded that in Alberta, Canada, rates of untreated kidney failure are significantly higher in older compared with younger individuals.

Importance: Clinical experience suggests that there are substantial differences in patient complexity across medical specialties, but empirical data are lacking., Objective: To compare the complexity of patients seen by different types of physician in a universal health care system., Design, Setting, and Participants: Population-based retrospective cohort study of 2 597 127 residents of the Canadian province of Alberta aged 18 years and older with at least 1 physician visit between April 1, 2014 and March 31, 2015. Data were analyzed in September 2018., Exposures: Type of physician seeing each patient (family physician, general internist, or 11 types of medical subspecialist) assessed as non-mutually exclusive categories., Main Outcomes and Measures: Nine markers of patient complexity (number of comorbidities, presence of mental illness, number of types of physicians involved in each patient's care, number of physicians involved in each patient's care, number of prescribed medications, number of emergency department visits, rate of death, rate of hospitalization, rate of placement in a long-term care facility)., Results: Among the 2 597 127 participants, the median (interquartile range) age was 46 (32-59) years and 54.1% were female. Over 1 year of follow-up, 21 792 patients (0.8%) died, the median (range) number of days spent in the hospital was 0 (0-365), 8.1% of patients had at least 1 hospitalization, and the median (interquartile range) number of prescribed medications was 3 (1-7). When the complexity markers were considered individually, patients seen by nephrologists had the highest mean number of comorbidities (4.2; 95% CI, 4.2-4.3 vs [lowest] 1.1; 95% CI, 1.0-1.1), highest mean number of prescribed medications (14.2; 95% CI, 14.2-14.3 vs [lowest] 4.9; 95% CI, 4.9-4.9), highest rate of death (6.6%; 95% CI, 6.3%-6.9% vs [lowest] 0.1%; 95% CI, <0.1%-0.2%), and highest rate of placement in a long-term care facility (2.0%; 95% CI, 1.8%-2.2% vs [lowest] <0.1%; 95% CI, <0.1%-0.1%). Patients seen by infectious disease specialists had the highest complexity as assessed by the other 5 markers: rate of a mental health condition (29%; 95% CI, 28%-29% vs [lowest] 14%; 95% CI, 14%-14%), mean number of physician types (5.5; 95% CI, 5.5-5.6 vs [lowest] 2.1; 95% CI, 2.1-2.1), mean number of physicians (13.0; 95% CI, 12.9-13.1 vs [lowest] 3.8; 95% CI, 3.8-3.8), mean days in hospital (15.0; 95% CI, 14.9-15.0 vs [lowest] 0.4; 95% CI, 0.4-0.4), and mean emergency department visits (2.6; 95% CI, 2.6-2.6 vs [lowest] 0.5; 95% CI, 0.5-0.5). When types of physician were ranked according to patient complexity across all 9 markers, the order from most to least complex was nephrologist, infectious disease specialist, neurologist, respirologist, hematologist, rheumatologist, gastroenterologist, cardiologist, general internist, endocrinologist, allergist/immunologist, dermatologist, and family physician., Conclusion and Relevance: Substantial differences were found in 9 different markers of patient complexity across different types of physician, including medical subspecialists, general internists, and family physicians. These findings have implications for medical education and health policy.