Urinary calprotectin, NGAL, and KIM-1 in the differentiation of primarily inflammatory vs. non-inflammatory stable chronic kidney diseases.

INTRODUCTION: It has been demonstrated that urinary neutrophil gelatinase-associated lipocalin (NGAL) and calprotectin are helpful biomarkers in the differentiation of intrinsic and prerenal acute kidney injury. OBJECTIVE: The present cross-sectional study investigates, whether urinary biomarkers are able to differentiate primarily inflammatory from non-inflammatory entities in chronic kidney disease (CKD). METHODS: Urinary calprotectin, NGAL, and kidney injury molecule-1 (KIM-1) concentrations were assessed in a study population of 143 patients with stable CKD and 29 healthy controls. Stable renal function was defined as an eGFR fluctuation ≤5 ml/min/1.73 m2 in the past 12 months. Pyuria, metastatic carcinoma, and renal transplantation were regarded as exclusion criteria. Diabetic nephropathy, hypertensive nephropathy, and polycystic kidney disease were categorized as 'primarily non-inflammatory renal diseases' (NIRD), whereas glomerulonephritis and vasculitis were regarded as 'primarily inflammatory renal diseases' (IRD). RESULTS: Urinary calprotectin and NGAL concentrations significantly differed between CKD and healthy controls (p < 0.05 each), whereas KIM-1 concentrations did not (p = 0.84). The three biomarkers did neither show significant differences in-between the individual entities, nor the two categories of IRD vs. NIRD (calprotectin 155.7 vs. 96.99 ng/ml; NGAL 14 896 vs. 11 977 pg/ml; KIM-1 1388 vs. 1009 pg/ml; p > 0.05 each). Albumin exceeds the diagnostic power of the investigated biomarkers by far. CONCLUSIONS: The urinary biomarkers calprotectin, NGAL, and KIM-1 have no diagnostic value in the differentiation of primarily inflammatory vs. non-inflammatory etiologies of CKD.

Prognostic Value of Urinary Calprotectin, NGAL and KIM-1 in Chronic Kidney Disease.

BACKGROUND/AIMS: Urinary biomarkers like neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule-1 (KIM-1) do not only allow an early diagnosis of acute kidney injury, but also provide prognostic information in this setting. The present prospective study investigates, whether the urinary biomarkers NGAL, KIM-1 and calprotectin have prognostic information in chronic kidney disease (CKD) as well. METHODS: Urinary calprotectin, NGAL and KIM-1 concentrations were assessed in a study population of 143 patients with stable CKD comprising diabetic and hypertensive nephropathy, glomerulonephritis/vasculitis, and autosomal dominant polycystic kidney disease. An eGFR fluctuation > 5ml/min/1.73m2 in the past 12 months was defined as an exclusion criterion in order to exclude cases with acute on chronic kidney injury. Renal function was monitored for a median follow-up of 37 months. RESULTS: In the overall study population, all the three biomarkers failed to predict DeGFR and DACR from baseline to follow-up in linear regression analysis adjusted for age, gender, and baseline eGFR. Contrarily, baseline ACR was significantly associated with DeGFR (p< 0.001). In the subgroup of patients with vasculitis and glomerulonephritis, all the three biomarkers were significantly associated with DeGFR, with calprotectin having the highest regression coefficient. CONCLUSION: In contrast to the traditional biomarker "albuminuria", neither the inflammatory biomarker calprotectin, nor the tubular biomarkers NGAL and KIM-1, provide robust prognostic information on the loss or renal function in a heterogeneous CKD population. All of them, however, are candidate prognostic biomarkers in primarily inflammatory renal diseases.

Step Back in Order to Go Forward: Willful Enlargement and Sandwich Closure Technique for Spinal Dura Repair after Several Unsuccessful Closure Attempts.

A CSF leak is a common complication in spine surgery which is usually closed effectivly by suture and/or epidural patches. There is currently no algorithm to treat a recurrent CSF leak that fails to be closed initially. We describe the case of a recurrent cerebrospinal fluid leak that we have successfully treated using an inlay-onlay dural repair technique.

Deep learning algorithm in detecting intracranial hemorrhages on emergency computed tomographies.

BACKGROUND: Highly accurate detection of intracranial hemorrhages (ICH) on head computed tomography (HCT) scans can prove challenging at high-volume centers. This study aimed to determine the number of additional ICHs detected by an artificial intelligence (AI) algorithm and to evaluate reasons for erroneous results at a level I trauma center with teleradiology services. METHODS: In a retrospective multi-center cohort study, consecutive emergency non-contrast HCT scans were analyzed by a commercially available ICH detection software (AIDOC, Tel Aviv, Israel). Discrepancies between AI analysis and initial radiology report (RR) were reviewed by a blinded neuroradiologist to determine the number of additional ICHs detected and evaluate reasons leading to errors. RESULTS: 4946 HCT (05/2020-09/2020) from 18 hospitals were included in the analysis. 205 reports (4.1%) were classified as hemorrhages by both radiology report and AI. Out of a total of 162 (3.3%) discrepant reports, 62 were confirmed as hemorrhages by the reference neuroradiologist. 33 ICHs were identified exclusively via RRs. The AI algorithm detected an additional 29 instances of ICH, missed 12.4% of ICH and overcalled 1.9%; RRs missed 10.9% of ICHs and overcalled 0.2%. Many of the ICHs missed by the AI algorithm were located in the subarachnoid space (42.4%) and under the calvaria (48.5%). 85% of ICHs missed by RRs occurred outside of regular working-hours. Calcifications (39.3%), beam-hardening artifacts (18%), tumors (15.7%), and blood vessels (7.9%) were the most common reasons for AI overcalls. ICH size, image quality, and primary examiner experience were not found to be significantly associated with likelihood of incorrect AI results. CONCLUSION: Complementing human expertise with AI resulted in a 12.2% increase in ICH detection. The AI algorithm overcalled 1.9% HCT. TRIAL REGISTRATION: German Clinical Trials Register (DRKS-ID: DRKS00023593).