This retrospective cohort study examined the roles of inflammation in acute kidney injury (AKI). Serum albumin and C-reactive protein (CRP) were used as markers of inflammation. Adults who underwent non–cardiac surgery from 2007 to 2011 were included. Exclusion criteria were urological surgery, obstetric surgery, missing data, and pre-operative dialysis. Subjects were followed until the end of 2015 or loss to follow-up. Associations between pre–operative albumin or CRP and post-operative AKI or association between AKI and mortality were examined by logistic or Cox regression, respectively. Mediation analyses were performed using albumin and CRP as mediators. Among 4,538 subjects, 272 developed AKI. Pre-operative albumin was independently associated with AKI (odds ratio [95% confidence interval (CI)]: 0.63 [0.48–0.83]). During a median follow-up of 4.5 years, 649 died. AKI was significantly associated with mortality (hazard ratio [HR] [95% CI]: 1.58 [1.22–2.04]). Further adjustment for pre-operative albumin and CRP attenuated the association (HR [95% CI]: 1.28 [0.99–1.67]). The proportions explained by mediating effects of lnCRP and albumin were 29.3% and 39.2% and mediation effects were statistically significant. In conclusion, inflammation is a predictor of AKI and a mediator of mortality after AKI. Interventions targeting inflammation might improve outcomes of AKI.

Background Little is known about the association between pre-operative proteinuria and post-operative acute kidney injury (AKI) in noncardiac surgery. Methods This is a retrospective cohort study. Adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011 at Nara Medical University Hospital were included. Those with obstetric or urological surgery, missing data for analyses or pre-operative dialysis were excluded. Exposure of interest was pre-operative proteinuria, defined as (+) or more by dipstick test. The outcome variable was post-operative AKI, defined by Kidney Disease: Improving Global Outcomes criteria, within 1 week after surgery. Multivariable logistic regression analyses were performed. Results Among 5168 subjects, 309 (6.0%) developed AKI. Pre-operative proteinuria was independently associated with post-operative AKI, with an odds ratio (OR) [95% confidence interval (CI)] of 1.80 (1.30–2.51). A sensitivity analysis restricted to elective surgery yielded a similar result. As proteinuria increased, the association with AKI became stronger [OR (95% CI) 1.14 (0.75–1.73), 1.24 (0.79–1.95), 2.75 (1.74–4.35) and 3.95 (1.62–9.62) for urinary protein (+/−), (+), (2+) and (3+), respectively]. Subgroup analyses showed proteinuria was especially associated with post-operative AKI among subjects with renin–angiotensin system inhibitors, other anti-hypertensives, hypoalbuminemia or impaired renal function (P for interaction = 0.05, 0.003, 0.09 or 0.02, respectively). Conclusions In noncardiac surgery, pre-operative proteinuria was independently associated with post-operative AKI. Subjects with proteinuria should be managed with caution to avoid AKI peri-operatively.

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This longitudinal cohort study aimed to create a novel prediction model for cardiovascular death with lifestyle factors. Subjects aged 40–74 years in the Japanese nationwide Specific Health Checkup Database in 2008 were included. Subjects were randomly assigned to the derivation and validation cohorts by a 2:1 ratio. Points for the prediction model were determined using regression coefficients that were derived from the Cox proportional hazards model in the derivation cohort. Models 1 and 2 were developed using known risk factors and known factors with lifestyle factors, respectively. The models were validated by comparing Kaplan-Meier curves between the derivation and validation cohorts, and by calibration plots in the validation cohort. Among 295,297 subjects, data for 120,823 were available. There were 310 cardiovascular deaths during a mean follow-up of 3.6 years. Model 1 included known risk factors. In model 2, weight gain, exercise habit, gait speed, and drinking alcohol were additionally included as protective factors. Kaplan-Meier curves matched better between the derivation and validation cohorts in model 2, and model 2 was better calibrated. In conclusion, our prediction model with lifestyle factors improved the predictive ability for cardiovascular death.

Aims Diabetic nephropathy, a pathologically diagnosed microvascular complication of diabetes, is a strong risk factor for cardiovascular events, which mainly involve arteries larger than those affected in diabetic nephropathy. However, the association between diabetic nephropathy pathological findings and cardiovascular events has not been well studied. We aimed to investigate whether the pathological findings in diabetic nephropathy are closely associated with cardiovascular event development. Methods This retrospective cohort study analysed 377 people with type 2 diabetes and biopsy-proven diabetic nephropathy, with a median follow-up of 5.9 years (interquartile range 2.0 to 13.5). We investigated how cardiovascular events were impacted by two vascular diabetic nephropathy lesions, namely arteriolar hyalinosis and arterial intimal thickening, and by glomerular and interstitial lesions. Results Of the 377 people with diabetic nephropathy, 331 (88%) and 295 (78%) had arteriolar hyalinosis and arterial intimal thickening, respectively. During the entire follow-up period, those with arteriolar hyalinosis had higher cardiovascular event rates in the crude Kaplan-Meier analysis than those without these lesions (P = 0.005, log-rank test). When fully adjusted for clinically relevant confounders, arteriolar hyalinosis independently predicted cardiovascular events [hazard ratio (HR) 1.99; 95% confidence interval (CI) 1.12, 3.86], but we did not find any relationship between arterial intimal thickening and cardiovascular events (HR 0.89; 95% CI 0.60, 1.37). Additionally, neither glomerular nor interstitial lesions were independently associated with cardiovascular events in the fully adjusted model. Conclusions Arteriolar hyalinosis, but not intimal thickening of large arteries, was strongly associated with cardiovascular events in people with diabetic nephropathy.

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IMPORTANCEThe Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed. OBJECTIVE To externally validate the SPARK index. DESIGN, SETTING, AND PARTICIPANTS This single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m 2 , preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021. EXPOSURES Risk factors for AKI included in SPARK index. MAIN OUTCOMES AND MEASURES PO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively. RESULTS Among 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m 2 vs 78.2 [65.6-92.2] mL/min/1.73 m 2 ), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28; R 2 = 0.86; critical AKI: y = 0.20x + 2.08; R 2 = 0.51).Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort.