Derivation and validation of a novel clinical decision aid to distinguish between uncomplicated and complicated appendicitis in children.

2020 ◽  
Author(s):  
Stavros P. Loukogeorgakis ◽  
Christina Major ◽  
Ceri E Jones ◽  
Harriet J. Corbett ◽  
Semiu Eniola Folaranmi ◽  
...  
Keyword(s):  
Prediction Model ◽  
Operative Treatment ◽  
Scoring System ◽  
Multiple Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Complicated Appendicitis ◽  
Histopathological Analysis ◽  
Characteristic Analysis ◽  
Independent Cohort

Abstract Aim of Study:Non-operative treatment of acute uncomplicated appendicitis (UA) in children might be equally effective to surgery but requires accurate discrimination from those with complicated appendicitis (CA) to ensure safety and maximise efficacy. We aimed to identify specific clinical and laboratory parameters that would aid distinction between UA and CA in children.Methods:Retrospective review of consecutive children with a clinical +/- radiological diagnosis of acute appendicitis that underwent appendicectomy in three specialist paediatric surgical centres between March 2017 and February 2018. Demographic, clinical and laboratory data were retrieved and analysed in relation to intra-operative and histopathological findings. CA was defined as gangrene and/or perforation seen intra-operatively and/or in histopathological analysis. Multiple logistic regression analysis was used to derive a novel prediction model that could accurately distinguish UA and CA. A priori we set analytical parameters so as to ensure the score had a positive predictive value (PPV) for UA of >95%. The resulting scoring system was validated in an independent cohort of children.Main Results: The prediction model was derived from 130 children (UA: 71; CA: 59) with median age (range) 10 (2-15) years. Initial univariate analysis identified six factors significantly associated (p<0.01) with CA (duration of abdominal pain, presence of rebound tenderness, temperature, , white cell count, , neutrophil count and C-reactive protein [CRP]). These variables were entered in the regression model, and points awarded based on the adjusted odds ratios. Receiver operating characteristic analysis demonstrated a threshold of ≥4 points for prediction of CA. The scoring system was validated in an independent cohort of 112 children (UA: 51; CA: 61); it was found to have a sensitivity of 98% and specificity 78%. A score of <4 points had a PPV for UA of 98%.Conclusions: Our novel scoring system can discriminate between UA and CA in children with high accuracy. Children with a score <4 could be eligible for non-operative treatment.

scholarly journals Scoring System for Differentiation of Complicated Appendicitis in Pediatric Patients: Appendicitis Scoring System in Children

2021 ◽  
Vol 8 ◽  
pp. 2333794X2110222
Author(s):  
Yujin Lee ◽  
Hyunjin Cho ◽  
Geumhee Gwak ◽  
Byungnoe Bae ◽  
Keunho Yang
Keyword(s):  
Body Temperature ◽  
Acute Appendicitis ◽  
Scoring System ◽  
Multiple Logistic Regression Analysis ◽  
Laboratory Data ◽  
Area Under The Curve ◽  
Perforated Appendicitis ◽  
Scoring Systems ◽  
Complicated Appendicitis ◽  
Free Fluid

Although several scoring systems have been used to differentiate simple acute appendicitis from perforated appendicitis, no particular system has been widely accepted. Therefore, this study aimed to investigate preoperative factors associated with complicated appendicitis and to develop a scoring system that distinguishes complicated appendicitis in children aged <10 years. Patients aged <10 years who underwent surgical treatment for acute appendicitis between 2011 and 2019 were included in this study, after excluding those with insufficient medical records, with other diseases that affect the length of hospitalization, or without formal reports of abdominal computed tomography (CT) or ultrasonography (US). Complicated appendicitis was defined as hospitalization for ≥5 days postoperatively or readmission within 30 days postoperatively. Patient characteristics, symptoms, physical examination, laboratory data, and radiographic results were collected to determine predictors of complicated appendicitis. The mean age of 279 patients was 7.3 years. Among them, 57 patients had complicated appendicitis. A scoring system was developed based on the following 5 independent risk factors derived from multiple logistic regression analysis: body temperature, anorexia, diarrhea, C-reactive protein (CRP) level, and presence of periappendiceal free fluid on CT or US. The scoring system resulted in an area under the curve of .898 ( P < .001). For patients aged <10 years, a new model that includes objective factors, such as body temperature, CRP levels, and radiography results, might help predict complicated appendicitis and determine treatment plans.

scholarly journals Role of Blood Stasis Syndrome of Kampo Medicine in the Early Pathogenic Stage of Atherosclerosis: A Retrospective Cross-Sectional Study

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Akira Morita ◽  
Takao Namiki ◽  
Toshiya Nakaguchi ◽  
Kazunari Murai ◽  
Yuki Watanabe ◽  
...  
Keyword(s):  
Glucose Tolerance ◽  
Characteristic Curve ◽  
Multiple Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Blood Stasis ◽  
Area Under The Curve ◽  
Kampo Medicine ◽  
Blood Stasis Syndrome ◽  
History Of

In Kampo medicine, blood stasis (BS) syndrome is strongly associated with microangiopathy and can lead to atherosclerosis. Vascular endothelial dysfunction (VED), evaluated through flow-mediated dilation (FMD), plays an important role in the early stages of atherosclerosis. However, the association of BS syndrome with VED, as determined using FMD, has not been reported. This study investigated the association between BS syndrome and VED using FMD. Forty-one patients with normal glucose tolerance or impaired glucose tolerance (IGT) and without macrovascular complications were evaluated using FMD from May 2017 to August 2017. Based on the BS score, the patients were divided into the non-BS (n = 19) and BS syndrome (n = 22) groups. Physical and background characteristics, physiological function test results, and laboratory data were compared. Univariate analysis revealed that FMD and a history of dyslipidemia/IGT were significantly different between the two groups ( p < 0.05 ). Multiple logistic regression analysis showed that BS syndrome was significantly associated with FMD (odds ratio: 6.26; p = 0.03 ) after adjusting for the history of dyslipidemia/IGT. The receiver operating characteristic curve showed that the area under the curve for BS syndrome (0.74; p < 0.001 ) and history of IGT ( p < 0.007 ) provided good diagnostic accuracy for FMD. The area under the curve for “BS syndrome + IGT” showed very good accuracy (0.80; p < 0.0001 ) and was higher than that for BS syndrome or IGT alone. In conclusion, the results of this study suggest that the BS score in Kampo medicine could be a useful tool for detecting the early pathogenic stages of atherosclerosis.

scholarly journals A Novel Scoring System for Early Assessment of the Risk of the COVID-19-associated Mortality in Hospitalized Patients: COVID-19 BURDEN

2022 ◽  
Author(s):  
Fatemeh Amirzadehfard ◽  
Mohammad Hossein Imanieh ◽  
Sina Zoghi ◽  
Faezeh sehatpour ◽  
Peyman Jafari ◽  
...  
Keyword(s):  
Risk Score ◽  
Scoring System ◽  
Virus Disease ◽  
Multiple Logistic Regression Analysis ◽  
Laboratory Data ◽  
Area Under The Curve ◽  
Diagnostic Efficiency ◽  
Early Assessment ◽  
Severity Of The Disease ◽  
Care Costs

Background: Corona Virus Disease 2019 (COVID-19) presentation resembles common flu or can be more severe; it can result in hospitalization with significant morbidity and/or mortality. We made an attempt to develop a predictive model and a scoring system to improve the diagnostic efficiency for COVID-19 mortality via analysis of clinical features and laboratory data on admission. Methods: We retrospectively enrolled 480 consecutive adult patients, aged 21-95, who were admitted to Faghihi Teaching Hospital. Clinical and laboratory features were extracted from the medical records and analyzed using multiple logistic regression analysis. Results: A novel mortality risk score (COVID-19 BURDEN) was calculated, incorporating risk factors from this cohort. CRP (> 73.1 mg/L), O2 saturation variation (greater than 90%, 84-90%, and less than 84%), increased PT (>16.2s), diastolic blood pressure (≤75 mmHg), BUN (>23 mg/dL), and raised LDH (>731 U/L) are the features comprising the scoring system. The patients are triaged to the groups of low- (score <4) and high-risk (score ≥ 4) groups. The area under the curve, sensitivity, and specificity for predicting non-response to medical therapy with scores of ≥ 4 were 0.831, 78.12%, and 70.95%, respectively. Conclusion: Using this scoring system in COVID-19 patients, the severity of the disease will be determined in the early stages of the disease, which will help to reduce hospital care costs and improve its quality and outcome.

Abstract WP434: The SAH score: An Outcome prediction model

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Neeraj S Naval ◽  
Robert Kowalski ◽  
Tiffany Chang ◽  
Filissa Caserta ◽  
Juan R Carhuapoma ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Prediction Model ◽  
Outcome Prediction ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Multiple Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Risk Of Mortality ◽  
Relationship Of ◽  
Admission Variables

Objective: To create a reliable model for predicting mortality following aneurysmal subarachnoid hemorrhage (aSAH) based on admission variables. Background: Hunt & Hess grade is commonly used as a grading scale to predict mortality following aSAH. The scale relies only on clinical presentation and does not incorporate other admission factors making it suboptimal for outcome prediction. Methods: Prospectively collected data of aSAH patients admitted to our institution between 1991-2009 were reviewed. We analyzed factors that impacted in-hospital SAH mortality following multiple logistic regression analysis. Scores were ‘weighted’ based on relative risk of mortality following stratification of each of these variables. Hunt & Hess grade was subdivided into grades I/II, III, IV and V; age was split into 4 subgroups: 18-49, 50-69, 70-79 and >80. Medical co-morbidities were subdivided into none, 1 or >/=2 based on co-morbidities derived either from Charlson index or other factors (hypertension, cocaine) historically known to impact SAH outcomes, only if they were associated with increased mortality on univariate analysis. Results: 1134 patients were included; all-cause SAH hospital mortality was 18.3%. Hunt & Hess Grade, age and medical co-morbidities significantly impacted mortality following multivariate analysis (P< 0.05). Association with mortality based on Hunt & Hess Grade was 7%(I/II; score 0), 16%(III; score 1), 31%(IV; score 2) and 65%(V; score 4). Mortality based on age was 13%(18-49; score 0), 18%(50-69; score 1), 34% (70-79; score 2) and 46% (>80; score 3). Relationship of co-morbidities and mortality was 9%(none; score 0), 17%(one; score 1) and 32%(two/more; score 2). Summated Scores ranged from 0-9 with progressively increasing mortality at higher scores (0=1%/ 1=4%/ 2=9%/ 3=13%/ 4=22%/ 5=52%/ 6=77%/ 7=88%/ 8=100%/ 9=100%). PPV for scores in the range 7-9 was 90%; 6-9 was 83%. NPV for range 0-3 was 93% and 0-4 was 91%. The area under the curve (AUC) was 0.825 (good accuracy), which was superior to Hunt & Hess Grade (AUC 0.775, fair accuracy). Conclusions: The SAH score is a more accurate prediction model than the Hunt & Hess grade in estimating likelihood of hospital mortality following SAH.

scholarly journals CD8+ T cells predicted the conversion of common covid-19 to severe

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Li Liu ◽  
Zhiyong Chen ◽  
Yingrong Du ◽  
Jianpeng Gao ◽  
Junyi Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
T Cells ◽  
Logistic Regression ◽  
Prediction Model ◽  
Roc Curve ◽  
Multiple Logistic Regression Analysis ◽  
Laboratory Data ◽  
Training Set ◽  
Area Under Roc Curve ◽  
Validation Set

AbstractTo evaluate the predictive effect of T-lymphoid subsets on the conversion of common covid-19 to severe. The laboratory data were collected retrospectively from common covid-19 patients in the First People's Hospital of Zaoyang, Hubei Province, China and the Third People's Hospital of Kunming, Yunnan Province, China, between January 20, 2020 and March 15, 2020 and divided into training set and validation set. Univariate and multivariate logistic regression was performed to investigate the risk factors for the conversion of common covid-19 to severe in the training set, the prediction model was established and verified externally in the validation set. 60 (14.71%) of 408 patients with common covid-19 became severe in 6–10 days after diagnosis. Univariate and multiple logistic regression analysis revealed that lactate (P = 0.042, OR = 1097.983, 95% CI 1.303, 924,798.262) and CD8+ T cells (P = 0.010, OR = 0.903, 95% CI 0.835, 0.975) were independent risk factors for general type patients to turn to severe type. The area under ROC curve of lactate and CD8+ T cells was 0.754 (0.581, 0.928) and 0.842 (0.713, 0.970), respectively. The actual observation value was highly consistent with the prediction model value in curve fitting. The established prediction model was verified in 78 COVID-19 patients in the verification set, the area under the ROC curve was 0.906 (0.861, 0.981), and the calibration curve was consistent. CD8+ T cells, as an independent risk factor, could predict the transition from common covid-19 to severe.

scholarly journals 387. Markers for Mortality in COVID-19 Patients with Atrial Fibrillation or Flutter

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S262-S262
Author(s):  
Kok Hoe Chan ◽  
Bhavik Patel ◽  
Iyad Farouji ◽  
Addi Suleiman ◽  
Jihad Slim
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Prognostic Markers ◽  
Univariate Analysis ◽  
Laboratory Data ◽  
Significant Difference ◽  
New Onset

Abstract Background Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection can lead to many different cardiovascular complications, we were interested in studying prognostic markers in patients with atrial fibrillation/flutter (A. Fib/Flutter). Methods A retrospective cohort study of patients with confirmed COVID-19 and either with existing or new onset A. Fib/Flutter who were admitted to our hospital between March 15 and May 20, 2020. Demographic, outcome and laboratory data were extracted from the electronic medical record and compared between survivors and non-survivors. Univariate and multivariate logistic regression were employed to identify the prognostic markers associated with mortality in patients with A. Fib/Flutter Results The total number of confirmed COVID-19 patients during the study period was 350; 37 of them had existing or new onset A. Fib/Flutter. Twenty one (57%) expired, and 16 (43%) were discharged alive. The median age was 72 years old, ranged from 19 to 100 years old. Comorbidities were present in 33 (89%) patients, with hypertension (82%) being the most common, followed by diabetes (46%) and coronary artery disease (30%). New onset of atrial fibrillation was identified in 23 patients (70%), of whom 13 (57%) expired; 29 patients (78%) presented with atrial fibrillation with rapid ventricular response, and 2 patients (5%) with atrial flutter. Mechanical ventilation was required for 8 patients, of whom 6 expired. In univariate analysis, we found a significant difference in baseline ferritin (p=0.04), LDH (p=0.02), neutrophil-lymphocyte ratio (NLR) (p=0.05), neutrophil-monocyte ratio (NMR) (p=0.03) and platelet (p=0.015) between survivors and non-survivors. With multivariable logistic regression analysis, the only value that had an odds of survival was a low NLR (odds ratio 0.74; 95% confidence interval 0.53–0.93). Conclusion This retrospective cohort study of hospitalized patients with COVID-19 demonstrated an association of increase NLR as risk factors for death in COVID-19 patients with A. Fib/Flutter. A high NLR has been associated with increased incidence, severity and risk for stroke in atrial fibrillation patients but to our knowledge, we are first to demonstrate the utilization in mortality predictions in COVID-19 patients with A. Fib/Flutter. Disclosures Jihad Slim, MD, Abbvie (Speaker’s Bureau)Gilead (Speaker’s Bureau)Jansen (Speaker’s Bureau)Merck (Speaker’s Bureau)ViiV (Speaker’s Bureau)

scholarly journals Risk Scoring System of Mortality and Prediction Model of Hospital Stay for Critically Ill Patients Receiving Parenteral Nutrition

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 853
Author(s):  
Jee-Yun Kim ◽  
Jeong Yee ◽  
Tae-Im Park ◽  
So-Youn Shin ◽  
Man-Ho Ha ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Linear Regression ◽  
Parenteral Nutrition ◽  
Prediction Model ◽  
Scoring System ◽  
Prediction Equation ◽  
Icu Patients ◽  
Risk Scoring ◽  
Risk Scoring System

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.

scholarly journals PROGNOSTIC FACTORS OF RENAL TUMOR RECURRENCE AFTER RADICAL NEPHRECTOMY

2021 ◽  
Vol 108 (Supplement_3) ◽  
Author(s):  
G Martínez Izquierdo ◽  
A R Arnaiz Pérez ◽  
E Escolano Fernández ◽  
M Merayo Álvarez ◽  
B Carrasco Aguilera ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Radical Nephrectomy ◽  
Univariate Analysis ◽  
Malignant Neoplasms ◽  
Histopathological Analysis ◽  
Chi Square ◽  
Renal Sinus ◽  
Chi Square Test

Abstract INTRODUCTION Renal cell carcinoma (RCC) represents 3% of overall malignant neoplasms in adults. However, its aetiology has not been clearly established. Although surgery represents the cornerstone in treatment, recurrence postoperative rates are around 20-30%, what implies prognostic factors search must be mandatory in order to help to plan de follow-up and the different adjuvant therapy possibilities available in case they were necessary. MATERIAL AND METHODS A retrospective observational study was carried out in 110 patients who underwent radical nephrectomy between 2004 and 2018, with the aim of identifying possible prognostic factors of recurrence of RCC after these surgeries. Preoperative data (epidemiological, comorbidities and laboratory tests), surgical, pathological and variables related to follow-up were taken into account. A univariate and multivariate analysis were performed, using chi-square test and logistic regression, respectively. RESULTS The median follow-up time was 53.5 months (SD = 35.8), time in which 19 patients had a recurrence of RCC after radical nephrectomy (17.2%). Histopathological items such as the surgical piece size, the nodal and microvascular invasion, the renal sinus invasion and the presence of necrosis in the surgical piece were associated with RCC recurrence in the univariate analysis, while only the presence of necrosis in the surgical piece showed a significant result in the multivariate analysis (p = 0.004). CONCLUSIONS Histopathological analysis, highlighting the presence of necrosis in the histological sample, was proved to be the main risk factor of RCC recurrence.

scholarly journals Derivation and validation of a lipid-covered prognostic model for mature T-cell lymphomas

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Tiange Lu ◽  
Lei Shi ◽  
Guanggang Shi ◽  
Yiqing Cai ◽  
Shunfeng Hu ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
T Cell ◽  
Scoring System ◽  
Serum Lipid ◽  
Prognostic Model ◽  
Validation Cohort ◽  
Univariate Analysis ◽  
Prognostic Significance ◽  
Cox Regression Analysis ◽  
T Cell Lymphomas

Abstract Background Mature T-cell lymphomas (MTCLs), a group of diseases with high aggressiveness and vulnerable prognosis, lack for the accurate prognostic stratification systems at present. Novel prognostic markers and models are urgently demanded. Aberrant lipid metabolism is closely related to the tumor progression but its prognostic significance in MTCLs remains unexplored. This study aims to investigate the relationship between dysregulated lipid metabolism and survival prognosis of MTCLs and establish a novel and well-performed prognostic scoring system for MTCL patients. Methods A total of 173 treatment-naive patients were enrolled in this study. Univariate and multivariate Cox regression analysis were performed to assess the prognostic significance of serum lipid profiles and screen out independent prognostic factors, which constituted a novel prognostic model for MTCLs. The performance of the novel model was assessed in the training and validation cohort, respectively, by examining its calibration, discrimination and clinical utility. Results Among the 173 included patients, 115 patients (01/2006–12/2016) constituted the training cohort and 58 patients (01/2017–06/2020) formed the validation cohort. Univariate analysis revealed declined total cholesterol (TC, P = 0.000), high-density lipoprotein cholesterol (HDL-C, P = 0.000) and increased triglycerides (TG, P = 0.000) correlated to inferior survival outcomes. Multivariate analysis revealed extranodal involved sites ≥ 2 (hazard ratio [HR]: 2.439; P = 0.036), β2-MG ≥ 3 mg/L (HR: 4.165; P = 0.003) and TC < 3.58 mmol/L (HR: 3.338; P = 0.000) were independent predictors. Subsequently, a novel prognostic model, EnBC score, was constructed with these three factors. Harrell’s C-index of the model in the training and validation cohort was 0.840 (95% CI 0.810–0.870) and 0.882 (95% CI 0.822–0.942), respectively, with well-fitted calibration curves. The model divided patients into four risk groups with distinct OS [median OS: not available (NA) vs. NA vs. 14.0 vs. 4.0 months, P < 0.0001] and PFS (median PFS: 84.0 vs. 19.0 vs. 8.0 vs. 1.5 months, P < 0.0001). Time-dependent receiver operating characteristic curve and decision curve analysis  further revealed that EnBC score provided higher diagnostic capacity and clinical benefit, compared with International Prognostic Index (IPI). Conclusion Firstly, abnormal serum lipid metabolism was demonstrated significantly related to the survival of MTCL patients. Furthermore, a lipid-covered prognostic scoring system was established and performed well in stratifying patients with MTCLs.

scholarly journals POS0722 HISTOPATHOLOGICAL ANALYSIS OF LUPUS NEPHRITIS INCORPORATING BANFF CRITERIA EMPHASIZES THE IMPORTANCE OF TUBULOINTERSTITIAL CHANGES FOR CREATININE AND PROTEINURIA AT 12 MONTHS AFTER RENAL BIOPSY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 611.1-611
Author(s):  
M. Plüß ◽  
S. Hakroush ◽  
N. Niebusch ◽  
B. Tampe ◽  
P. Korsten
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Nephritis ◽  
Lupus Erythematosus ◽  
Interstitial Fibrosis ◽  
Laboratory Data ◽  
Histopathological Analysis ◽  
Systemic Lupus ◽  
Long Term Outcome ◽  
Banff Classification ◽  
Tubulointerstitial Inflammation

Background:Lupus nephritis (LN) occurs in about 30-60% of patients with systemic lupus erythematosus (SLE). LN is associated with increased mortality. Currently, the diagnosis relies on histopathologic characteristics according to the ISN/RPS classification (1). This classification relies heavily on glomerular changes and may not accurately reflect all changes occurring in LN. For the description of transplanted kidney, the BANFF classification has been established which, in addition to glomerular changes, also incorporates tubular pathologies (2).Objectives:With the present study, we aim to describe histopathologic changes according to the BANFF classification in a single-center cohort of LN patients.Methods:We retrospectively recorded epidemiological, clinical and laboratory data of 58 patients with LN over a ten-year period. Histopathologic diagnoses according to ISN/RPS classification or the former WHO classification were also documented. We then re-analyzed representative kidney samples according to the BANFF classification and performed Spearman rank correlation for BANFF findings and creatinine at biopsy and 12 months as well as proteinuria at biopsy and at 12 months.Results:We analyzed 58 patients with LN. 9 were male, 49 were female. Median age was 38 (15-78) years. According to ISN/RPS, 3 had class I LN, 6 had class II, 14 had class III, 16 had class IV, 6 had class V, and 0 had class VI. Median eGFR at biopsy was 60 ml/min/1.73m2 (13-137). According to the BANFF classification, tubulointerstitial inflammation (ti) was associated with creatinine at 12 months. Proteinuria at 12 months was associated with interstitial fibrosis (ci) (Figure 1).Conclusion:In LN, the current ISN/RPS classification puts emphasis on glomerular changes. Nevertheless, for the long-term outcome, tubulointerstitial changes (tubulointerstitial inflammation and interstitial fibrosis) may at least be as important as glomerular changes. These findings have to be corroborated in larger cohorts with prespecified renal endpoints.References:[1]Weening et al. The classification of glomerulonephritis in systemic lupus erythematosus revisited. JASN 2004.[2]Jeong HY. Diagnosis of renal transplant rejection: Banff classification and beyond. Kidney Res Clin Pract 2020.Disclosure of Interests:Marlene Plüß: None declared, Samy Hakroush: None declared, Noah Niebusch: None declared, Björn Tampe: None declared, PETER KORSTEN Speakers bureau: Abbvie, Pfizer, Chugai, Sanofi, Boehringer-Ingelheim, GSK, Novartis, Consultant of: Abbvie, Pfizer, Chugai, Sanofi, Boehringer-Ingelheim, GSK, Novartis, Lilly, Gilead, Grant/research support from: GSK

Sign in / Sign up

Export Citation Format

Share Document