Additional file 1: Table S1. of Clinico-pathological characteristics and outcomes of patients with biopsy-proven hypertensive nephrosclerosis: a retrospective cohort study

Correlations between pathology variables. (DOC 45 kb

A Non-Invasive Laboratory Panel as a Diagnostic and Prognostic Biomarker for Thrombotic Microangiopathy: Development and Application in a Chinese Cohort Study

<div><p>Background</p><p>Thrombotic microangiopathy (TMA) in the kidney is a histopathologic lesion that occurs in a number of clinical settings and is often associated with poor renal prognosis. The standard test for the diagnosis of TMA is the renal biopsy; noninvasive parameters such as potential biomarkers have not been developed.</p><p>Methods</p><p>We analyzed routine parameters in a cohort of 220 patients with suspected TMA and developed a diagnostic laboratory panel by logistic regression. The levels of candidate markers were validated using an independent cohort (n = 46), a cohort of systemic lupus erythematosus (SLE) (n = 157) and an expanded cohort (n = 113), as well as 9 patients with repeat biopsies.</p><p>Results</p><p>Of the 220 patients in the derivation cohort, 51 patients with biopsy-proven TMA presented with a worse renal prognosis than those with no TMA (P = 0.002). Platelet and L-lactate dehydrogenase (LDH) levels showed an acceptable diagnostic value of TMA (AUC = 0.739 and 0.756, respectively). A panel of 4 variables - creatinine, platelets, ADAMTS13 (a disintegrin and metalloprotease with thrombospondin type 1 repeats 13) activity and LDH - can effectively discriminate patients with TMA (AUC = 0.800). In the validation cohort, the platelet and LDH levels and the 4-variable panel signature robustly distinguished patients with TMA. The discrimination effects of these three markers were confirmed in patients with SLE. Moreover, LDH levels and the 4-variable panel signature also showed discrimination values in an expanded set. Among patients undergoing repeat biopsy, increased LDH levels and panel signatures were associated with TMA status when paired evaluations were performed. Importantly, only the 4-variable panel was an independent prognostic marker for renal outcome (hazard ratio = 3.549; P<0.001).</p><p>Conclusions</p><p>The noninvasive laboratory diagnostic panel is better for the early detection and prognosis of TMA compared with a single parameter, and may provide a promising biomarker for clinical application.</p></div

Association of LDH levels and 4-variable panel with renal survival.

<p>(A) Using the cutoff value of 0.248, suspected patients were divided into two groups by more or less than the value and the renal survival of two groups followed up 12 months was significantly different (P<0.001). (B) The pattern of increased LDH concentrations (more than the cutoff point of 289 u/L) associated statistically poorer renal outcome was not observed (P = 0.183).</p

Comparison of renal outcome in suspected patients.

<p>After 12 months of follow-up, the patients with TMA had a worse outcome of renal survival than those without TMA (Log rank: P = 0.002).</p

Receiver operating characteristic curves and calibration curve for a diagnostic panel.

<p>(A) The diagnostic panel was developed in the derivation group of 220 suspected patients, with AUC 0.800, P<0.001. (B) This marker was validated in 46 independent patients, with AUC 0.815, P<0.001. (C) Bootstrap validation shows the calibration curve of the diagnostic panel. Cross-validated estimates of the AUC, calibration-curve intercept and slope were 0.777, 0.07 and 0.64, respectively. The loess-smoothed estimates of the cross-validated and unadjusted calibration curves are overlaid on a diagonal reference line representing good model calibration.</p

Receiver operating characteristic curves of laboratory parameters.

<p>(A) The fraction of true positive results (sensitivity) and the fraction of false positive results (1-specificity) for LDH, HGB, SCr, PLT, THBD and ADAMTS13 activity were developed in 220 patients (all P≤0.001), and the levels of platelet and LDH showed acceptable discrimination, with AUC 0.739 and 0.756, respectively. (B) The levels of platelet and LDH could discriminate patients with TMA from those with no TMA in the validation cohort (n = 46), with AUC 0.747 and 0.741, respectively.</p

Clinical laboratory data for suspected patients in derivation cohort (n = 220).

<p>Values are expressed as medians (range), means ± standard deviation or percentages. <i>P</i> values were calculated by Mann-Whitney U test, Fisher’s exact test or chi-square test as appropriate. HUS: hemolytic uremic syndrome; TTP: thrombotic thrombocytopenic purpura; SLE: systemic lupus erythematosus; C3: Complement component 3; C4: Complement component 4; ADAMTS13: A Disintegrin and Metalloprotease with ThromboSpondin type 1 repeats 13; NEC: normal endothelial cells; VCAM: vascular cell adhesion molecule; vWF: von Willebrand factor.</p><p>Clinical laboratory data for suspected patients in derivation cohort (n = 220).</p

Additional file 1 of Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy

Additional file 1. Supplementary Materia

Advancing the application of the analytical renal pathology system in allograft IgA nephropathy patients

The analytical renal pathology system (ARPS) based on convolutional neural networks has been used successfully in native IgA nephropathy (IgAN) patients. Considering the similarity of pathologic features, we aim to evaluate the performance of the ARPS in allograft IgAN patients and broaden its implementation. Biopsy-proven allograft IgAN patients from two different centers were enrolled for internal and external validation. We implemented the ARPS to identify glomerular lesions and intrinsic glomerular cells, and then evaluated its performance. Consistency between the ARPS and pathologists was assessed using intraclass correlation coefficients. The association of digital pathological features with clinical and pathological data was measured. Kaplan-Meier survival curve and cox proportional hazards model were applied to investigate prognosis prediction. A total of 56 biopsy-proven allograft IgAN patients from the internal center and 17 biopsy-proven allograft IgAN patients from the external center were enrolled in this study. The ARPS was successfully applied to identify the glomerular lesions (F1-score, 0.696–0.959) and quantify intrinsic glomerular cells (F1-score, 0.888–0.968) in allograft IgAN patients rapidly and precisely. Furthermore, the mesangial hypercellularity score was positively correlated with all mesangial metrics provided by ARPS [Spearman’s correlation coefficient (r), 0.439–0.472, and all p values We propose that the ARPS could be implemented in future clinical practice with outstanding capability.</p

MOESM1 of Urinary miR-196a predicts disease progression in patients with chronic kidney disease

Additional file 1. Additional methods, figures and tables