Predicting Severe Renal and Gastrointestinal Involvement in Childhood Immunoglobulin A Vasculitis with Routine Laboratory Parameters

Dermatology ◽  
2021 ◽  
pp. 1-8
Author(s):  
Zexing Song ◽  
Yingli Nie ◽  
Liu Yang ◽  
Juan Tao
Keyword(s):  
Prediction Model ◽  
Prediction Models ◽  
Renal Involvement ◽  
Immunoglobulin A ◽  
Prognostic Information ◽  
Cutaneous Manifestations ◽  
Laboratory Parameters ◽  
Wbc Count ◽  
Immunoglobulin A Vasculitis ◽  
D Dimer

<b><i>Background:</i></b> Immunoglobulin A vasculitis (IgAV) is the most common vasculitis in children. Although childhood IgAV is generally considered as a self-limited disease, progressive course and poor prognosis could occur in some cases which mostly result from severe renal involvement and gastrointestinal (GI) involvement. <b><i>Methods:</i></b> We performed a retrospective study of pediatric patients diagnosed as IgAV in our institution from 2016 to 2019. Patients were divided into groups based on the occurrence and severity of GI and renal involvement. Analysis of variance (ANOVA) and Kruskal-Wallis test were used to compare results of laboratory parameters among groups and prediction models were built by using logistic regression analysis. <b><i>Results:</i></b> A total of 286 patients were enrolled. GI involvement occurred in 148 (51.7%) patients, 30 (20.3%) of which were severe cases. Renal involvement developed in 120 (42.0%) patients, 22 (18.3%) of which were severe cases. Compared with patients with only cutaneous manifestations, white blood cell (WBC) count, neutrophil-to-lymphocyte ratio (NLR), and D-dimer levels were higher in those with GI involvement, and D-dimer level was found to be positively associated with severity. Increased NLR and lower complement 3 (C3) were found in patients with renal involvement, but only C3 was relevant in distinguishing moderate and severe cases. The prediction model for severe renal involvement was: Logit (P) = 6.820 + 0.270 (age) + 0.508 (NLR) − 16.130 (C3), with an AUC of 0.914. The prediction model for severe GI involvement was: Logit (P) = −5.459 + 0.005 (WBC) + 1.355 (D-dimer) – 0.020 (NLR), with an AUC of 0.849. <b><i>Conclusion:</i></b> Our data suggest C3 to be an exclusive predictor for severe renal involvement and D-dimer level to be positively associated with the severity of GI involvement. Prediction models consisting of the above parameters were built for obtaining prognostic information in the early phase of IgAV.

scholarly journals Epidemiological and clinical aspects of immunoglobulin A vasculitis in childhood: a retrospective cohort study

2021 ◽  
Vol 47 (1) ◽  
Author(s):  
Breda Luciana ◽  
Carbone Ilaria ◽  
Casciato Isabella ◽  
Cristina Gentile ◽  
Eleonora Agata Grasso ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Renal Involvement ◽  
Healthcare Delivery ◽  
Immunoglobulin A ◽  
Retrospective Chart Review ◽  
Paediatric Population ◽  
Clinical Aspects ◽  
Healthcare Delivery System ◽  
Laboratory Findings ◽  
Immunoglobulin A Vasculitis

Abstract Background A retrospective study was conducted in order to investigate and describe the characteristics of Immunoglobulin A vasculitis (IgAV), previously known as Henoch-Schӧnlein purpura, in the paediatric population of a community-based healthcare delivery system in the Italian region of Abruzzo. Methods This is a population-based retrospective chart review of the diagnosis of IgAV in children ages 0 to 18, admitted to the Department of Paediatrics of Chieti and Pescara between 1 January 2000 and 31 December 2016. All children enrolled presented with clinical symptoms and laboratory findings and met the EULAR/PRINTO/PRES 2008 criteria. Results Two-hundred-eight children met the criteria for IgAV, with the highest incidence reported among children below 7-years of age. A correlation with recent infections was found in 64% of the cohort; the onset was more frequently during the winter and fall. Purpura had a diffuse distribution in the majority of patients; joint impairment was the second most frequent symptom (43%), whereas the gastrointestinal tract was involved in 28% of patients. Conclusions Hereby, we confirm the relative benignity of IgAV in a cohort of Italian children; with regards to renal involvement, we report a better outcome compared to other studies. However, despite the low rate of renal disease, we observed a wide use of corticosteroids, especially for the treatment of persistent purpura.

scholarly journals Low Back Pain and Swelling as an Atypical Presentation of IgA Vasculitis

2020 ◽  
Vol 4 (2) ◽  
pp. 241-243
Author(s):  
Clay Winkler ◽  
Raymond Dobson ◽  
Michael Tranovich
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Immunoglobulin A ◽  
Lumbar Pain ◽  
Low Back ◽  
Iga Vasculitis ◽  
Gastrointestinal Involvement ◽  
Cutaneous Manifestations ◽  
Schonlein Purpura ◽  
Immunoglobulin A Vasculitis

Introduction: Immunoglobulin A vasculitis (IgA vasculitis), formerly Henoch-Schonlein purpura, is the most common vasculitis in children. Case Report: A 6-year-old female presented with low back pain and swelling, difficulty ambulating, and rash two weeks after a respiratory infection. She was approached with a broad differential and ultimately diagnosed with IgA vasculitis. Discussion: Cutaneous manifestations, arthralgias, renal and gastrointestinal involvement are the most common presenting signs of IgA vasculitis. Only two cases of IgA vasculitis associated with lumbar pain and swelling were identified in the literature. Conclusion: While rash and joint pain are common presenting signs of IgA vasculitis, practitioners should be aware it can present atypically.

scholarly journals Tumor marker based survival analysis for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pseudomyxoma Peritonei ◽  
Roc Analysis ◽  
Prediction Models ◽  
Radical Surgery ◽  
Univariate Analysis ◽  
Barthel Index Score ◽  
Discrimination Ability ◽  
First Time ◽  
D Dimer

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to screen independent prediction indicators for PMP and establish prediction model for OS rates in PMP.Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for screening independent prediction indicators. Finally, the prediction models for OS in PMP will be established.Results Univariate analysis showed that Barthel Index Score, albumin, D-dimer, CEA, CA125, CA19-9, CA724, CA242, PCI, degree of radical surgery, histopathological grade were significant predictors for OS in PMP. At multivariate analysis, sex, D-dimer, CA125, CA19-9, and degree of radical surgery were independently associated with OS rate in PMP. ROC analysis was performed to calculate discrimination ability of prediction model and the area under curves (AUC) was 0.902 (95%CI: 0.823-0.954). Finally, nomogram was plotted by the independent predictive factors for PMP.Conclusions Several factors (sex, degree of radical surgery, D-dimer, preoperative CA125 and CA19-9) have independent prognostic value for survival in PMP, the tumor based prediction model has better prediction value, more researches are need to verify and improve the prediction model.

scholarly journals Case of Gut Necrosis in Adult-Onset Immunoglobulin A Vasculitis (Henoch-Schönlein Purpura)

2020 ◽  
Vol 8 ◽  
pp. 232470962092556 ◽  
Author(s):  
Amanda S. Weissman ◽  
Viral Sanjay Patel ◽  
Omar Mushfiq
Keyword(s):  
Abdominal Pain ◽  
Renal Disease ◽  
Renal Involvement ◽  
Immunoglobulin A ◽  
Glucocorticoid Therapy ◽  
Acute Glomerulonephritis ◽  
Henoch Schonlein Purpura ◽  
Schonlein Purpura ◽  
Immunoglobulin A Vasculitis ◽  
Henoch Schönlein Purpura

Immunoglobulin A vasculitis (IgAV), formerly known as Henoch-Schönlein purpura, is an immune-mediated small vessel vasculitis characterized by palpable purpura, arthralgia, abdominal pain, and renal disease. It is primarily a childhood disease and usually resolves spontaneously with supportive therapy. Treatment of IgAV in adults is controversial with no clearly established guidelines. We report a rare case of IgAV in an adult male who developed gut necrosis and perforation while receiving glucocorticoid therapy for treatment of acute glomerulonephritis. A 44-year-old male was admitted with joint pain, leg swelling, mild abdominal pain, and a diffuse rash. Laboratory values revealed acute kidney injury with significant proteinuria and hematuria. The patient was started on glucocorticoid therapy for suspected IgAV nephritis, which was confirmed by kidney biopsy. Several days later, he complained of worsening abdominal pain. Imaging demonstrated bowel ischemia and perforation requiring multiple abdominal surgeries. The patient was critically ill in the intensive care unit with worsening renal failure requiring dialysis. He was discharged a month later after gradual recovery with stable but moderately impaired kidney function. IgAV is less common in adults; however, the disease is more severe with a higher risk of long-term complications. Adult patients with renal involvement may benefit from glucocorticoid therapy in preventing progression to end-stage renal disease. However, glucocorticoids may mask the symptoms of abdominal complications like gut necrosis and perforation causing delay in diagnosis and treatment. Therefore, vigilance to detect early signs of gut ischemia is imperative when treating an adult case of IgAV nephritis with glucocorticoids.

scholarly journals IgA Vasculitis in Middle Aged Man Followed by Influenza Virus Infection: A Case Report

2018 ◽  
Vol 3 (3) ◽  
pp. 130
Author(s):  
Aqsa Iqbal ◽  
Nicole Stahl ◽  
Erin M Davis
Keyword(s):  
Case Report ◽  
Virus Infection ◽  
Group A Streptococcus ◽  
Severe Disease ◽  
Renal Involvement ◽  
Immunoglobulin A ◽  
Influenza Virus Infection ◽  
Infectious Agent ◽  
Gastrointestinal Lesions ◽  
Immunoglobulin A Vasculitis

Introduction: Immunoglobulin A vasculitis (formerly known as Henoch Schonlein Purpura) is the most common pediatric vasculitis, which occurs typically at the age of 3-15 years. Mononucleosis, group A Streptococcus, Campylobacter and Mycoplasma are some of the common infectious causes of immunoglobulin A vasculitis. Immunoglobulin A vasculitis is a clinically diagnosed disease. Most common clinical features include nonthrombocytopenic nonpruritic palpable purpura, gastrointestinal involvement, arthritis or arthralgia and renal involvement. Biopsy of skin and/or gastrointestinal lesions con rm the diagnosis, although this is not necessary. Immunoglobulin A vasculitis is a self-limiting disease, which resolves spontaneously. Steroids can be used for the treatment of moderate to severe disease and for the prevention of renal complications. Prognosis relies upon various factors among which involvement of kidneys dictates poor prognosis and requires close follow up. Case Presentation: We are presenting a case of immunoglobulin A vasculitis in a 39-year-old German male following in uenza virus infection. The infectious agent that cause immunoglobulin A vasculitis in our patient was In uenza A virus. Biopsy of the skin lesion con rmed the diagnosis of immunoglobulin A vasculitis in our patient. The patient responded to steroids and his skin and GI ndings resolved. Conclusion: Our case report adds to the literature of medicine by describing in uenza virus as a cause of immunoglobulin A vasculitis in young adult patients. Considering immunoglobulin A vasculitis after in uenza and outside of the typical age of 3-15 years, can help to make earlier diagnosis and prevent complications.

scholarly journals Development and external validation of a prognostic multivariable model on admission for hospitalized patients with COVID-19

2020 ◽  
Author(s):  
Jianfeng Xie ◽  
Daniel Hungerford ◽  
Hui Chen ◽  
Simon T Abrams ◽  
Shusheng Li ◽  
...  
Keyword(s):  
Lactate Dehydrogenase ◽  
Prediction Model ◽  
Lymphocyte Count ◽  
Prediction Models ◽  
External Validation ◽  
Model Development ◽  
Added Value ◽  
Clinical Prediction ◽  
Healthcare Resources ◽  
D Dimer

SummaryBackgroundCOVID-19 pandemic has developed rapidly and the ability to stratify the most vulnerable patients is vital. However, routinely used severity scoring systems are often low on diagnosis, even in non-survivors. Therefore, clinical prediction models for mortality are urgently required.MethodsWe developed and internally validated a multivariable logistic regression model to predict inpatient mortality in COVID-19 positive patients using data collected retrospectively from Tongji Hospital, Wuhan (299 patients). External validation was conducted using a retrospective cohort from Jinyintan Hospital, Wuhan (145 patients). Nine variables commonly measured in these acute settings were considered for model development, including age, biomarkers and comorbidities. Backwards stepwise selection and bootstrap resampling were used for model development and internal validation. We assessed discrimination via the C statistic, and calibration using calibration-in-the-large, calibration slopes and plots.FindingsThe final model included age, lymphocyte count, lactate dehydrogenase and SpO2 as independent predictors of mortality. Discrimination of the model was excellent in both internal (c=0·89) and external (c=0·98) validation. Internal calibration was excellent (calibration slope=1). External validation showed some over-prediction of risk in low-risk individuals and under-prediction of risk in high-risk individuals prior to recalibration. Recalibration of the intercept and slope led to excellent performance of the model in independent data.InterpretationCOVID-19 is a new disease and behaves differently from common critical illnesses. This study provides a new prediction model to identify patients with lethal COVID-19. Its practical reliance on commonly available parameters should improve usage of limited healthcare resources and patient survival rate.FundingThis study was supported by following funding: Key Research and Development Plan of Jiangsu Province (BE2018743 and BE2019749), National Institute for Health Research (NIHR) (PDF-2018-11-ST2-006), British Heart Foundation (BHF) (PG/16/65/32313) and Liverpool University Hospitals NHS Foundation Trust in UK.Research in contextEvidence before this studySince the outbreak of COVID-19, there has been a pressing need for development of a prognostic tool that is easy for clinicians to use. Recently, a Lancet publication showed that in a cohort of 191 patients with COVID-19, age, SOFA score and D-dimer measurements were associated with mortality. No other publication involving prognostic factors or models has been identified to date.Added value of this studyIn our cohorts of 444 patients from two hospitals, SOFA scores were low in the majority of patients on admission. The relevance of D-dimer could not be verified, as it is not included in routine laboratory tests. In this study, we have established a multivariable clinical prediction model using a development cohort of 299 patients from one hospital. After backwards selection, four variables, including age, lymphocyte count, lactate dehydrogenase and SpO2 remained in the model to predict mortality. This has been validated internally and externally with a cohort of 145 patients from a different hospital. Discrimination of the model was excellent in both internal (c=0·89) and external (c=0·98) validation. Calibration plots showed excellent agreement between predicted and observed probabilities of mortality after recalibration of the model to account for underlying differences in the risk profile of the datasets. This demonstrated that the model is able to make reliable predictions in patients from different hospitals. In addition, these variables agree with pathological mechanisms and the model is easy to use in all types of clinical settings.Implication of all the available evidenceAfter further external validation in different countries the model will enable better risk stratification and more targeted management of patients with COVID-19. With the nomogram, this model that is based on readily available parameters can help clinicians to stratify COVID-19 patients on diagnosis to use limited healthcare resources effectively and improve patient outcome.

scholarly journals Tumor marker based survival analysis for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pseudomyxoma Peritonei ◽  
Prediction Models ◽  
Radical Surgery ◽  
Cox Model ◽  
Univariate Analysis ◽  
Rank Test ◽  
Internal Validation ◽  
Discrimination Ability ◽  
D Dimer

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to screen independent prediction indicators and establish a nomogram for PMP. Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for screening independent prediction indicators. Finally, the nomogram prediction models will be established. Results Univariate analysis showed that Barthel Index Score, Albumin, D-Dimer, CEA, CA125, CA19-9, CA724, CA242, PCI, degree of radical surgery, histopathological grade were significant predictors for OS in PMP. At multivariate analysis, Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery were independently associated with OS rate in PMP. A nomogram was plotted based on the independent predictive factors for PMP and undergone internal validation, ROC analysis was performed to calculate discrimination ability of prediction model, the area under curves (AUC) was 0.880 (95% CI : 0.806- 0.933). Conclusions Several factors (Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery) have independent prognostic value for survival in PMP, the tumor based prediction model has a better prediction value, more researches are need to verify and improve the prediction model.

scholarly journals Correlation of the severity of HRCT findings with the other hematologic parameters & viral load in patients with confirmed COVID – 19 Infection

2021 ◽  
Vol 12 (9) ◽  
pp. 4-10
Author(s):  
Anjali Goyal ◽  
Misha Antani ◽  
Suhani Agarwal ◽  
Chandni Gadara ◽  
Milap Shah ◽  
...  
Keyword(s):  
Respiratory Tract ◽  
Hospital Stay ◽  
Tertiary Care ◽  
Viral Clearance ◽  
Care Hospital ◽  
Laboratory Parameters ◽  
Duration Of Hospital Stay ◽  
Severity Scores ◽  
Wbc Count ◽  
D Dimer

Background: The latter half of 2019 saw the spread of a highly contagious and fatal respiratory tract disease originating in the Hubei province of Wuhan in China which was labelled as COVID 19. Although a multi organ disease, it is seen to spread through the respiratory tract with lung being the primary target. Aims and Objective: The study was conducted to correlate the severity of lung involvement as assessed by the HRCT severity, with the Viral Severity index, laboratory parameters, duration of hospital stay, viral clearance and resolution of lung symptoms. Materials and Methods: An observational retrospective study was carried out from the laboratory records of consecutive 208 patients admitted to the tertiary care hospital between March 2020 to May 2020. Results: Out of a total of 208 patients, 200(96%) recovered and 8(4%) expired. The expired patients showed a higher average age (50.79+/- 17.42; 62.25+/-12.37) years in the recovered & expired patients respectively (p=0.06). A longer duration of hospital stay was seen in the expired patients (15.05+/-9.55&18.62+/-10.22) days in the recovered & expired patients respectively. A low average (Hemoglobin) Hb values (12.17+/-2.01&10.9+/-2.31) g/dl in the recovered and expired patients respectively along with a higher total WBC count was seen in the expired patients (8.62+/-3.81& 16.86+/-12.79) k/U in the recovered and expired patients with a highly significant p value of < 0.001). Higher CT severity scores were seen in the expired patients (10.74+/-5.57&17.12+/-6.55) in the recovered and expired patients respectively (p=0.0018). None of the expired patients had a normal D Dimer level. HRCT values and the Rising D Dimer levels tend to show a positive correlation with the disease outcome and progression. The Higher Viral severity and HRCT score was associated with a longer duration of hospital stay reflecting a higher duration of viral clearance. Conclusion: The Chest CT scores along with the laboratory parameters like the total WBC count and the D Dimer levels can together act as important parameters to monitor the Covid 19 disease course.

scholarly journals Machine Learning Enables Prediction of Cardiac Amyloidosis by Routine Laboratory Parameters: A Proof-of-Concept Study

2020 ◽  
Vol 9 (5) ◽  
pp. 1334 ◽  
Author(s):  
Asan Agibetov ◽  
Benjamin Seirer ◽  
Theresa-Marie Dachs ◽  
Matthias Koschutnik ◽  
Daniel Dalos ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Sensitivity And Specificity ◽  
Cardiac Amyloidosis ◽  
Linear Prediction ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Proof Of Concept ◽  
Laboratory Parameters ◽  
Concept Study

(1) Background: Cardiac amyloidosis (CA) is a rare and complex condition with poor prognosis. While novel therapies improve outcomes, many affected individuals remain undiagnosed due to a lack of awareness among clinicians. This study was undertaken to develop an expert-independent machine learning (ML) prediction model for CA relying on routinely determined laboratory parameters. (2) Methods: In a first step, we developed baseline linear models based on logistic regression. In a second step, we used an ML algorithm based on gradient tree boosting to improve our linear prediction model, and to perform non-linear prediction. Then, we compared the performance of all diagnostic algorithms. All prediction models were developed on a training cohort, consisting of patients with proven CA (positive cases, n = 121) and amyloidosis-unrelated heart failure (HF) patients (negative cases, n = 415). Performances of all prediction models were evaluated on a separate prognostic validation cohort with 37 CA-positive and 124 CA-negative patients. (3) Results: Our best model, based on gradient-boosted ensembles of decision trees, achieved an area under the receiver operating characteristic curve (ROC AUC) score of 0.86, with sensitivity and specificity of 89.2% and 78.2%, respectively. The best linear model had an ROC AUC score of 0.75, with sensitivity and specificity of 84.6 and 71.7, respectively. (4) Conclusions: Our work demonstrates that ML makes it possible to utilize basic laboratory parameters to generate a distinct CA-related HF profile compared with CA-unrelated HF patients. This proof-of-concept study opens a potential new avenue in the diagnostic workup of CA and may assist physicians in clinical reasoning.

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