scholarly journals The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study

2020 ◽  
Vol 58 (7) ◽  
pp. 1106-1115 ◽  
Author(s):  
Yufen Zheng ◽  
Ying Zhang ◽  
Hongbo Chi ◽  
Shiyong Chen ◽  
Minfei Peng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Platelet Count ◽  
Disease Progression ◽  
Neutrophil Count ◽  
Calibration Curve ◽  
Lymphocyte Count ◽  
Severe Disease ◽  
Clinical Impact ◽  
Predictive Tool ◽  
Potential Biomarker

AbstractObjectivesIn December 2019, there was an outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, and since then, the disease has been increasingly spread throughout the world. Unfortunately, the information about early prediction factors for disease progression is relatively limited. Therefore, there is an urgent need to investigate the risk factors of developing severe disease. The objective of the study was to reveal the risk factors of developing severe disease by comparing the differences in the hemocyte count and dynamic profiles in patients with severe and non-severe COVID-19.MethodsIn this retrospectively analyzed cohort, 141 confirmed COVID-19 patients were enrolled in Taizhou Public Health Medical Center, Taizhou Hospital, Zhejiang Province, China, from January 17, 2020 to February 26, 2020. Clinical characteristics and hemocyte counts of severe and non-severe COVID patients were collected. The differences in the hemocyte counts and dynamic profiles in patients with severe and non-severe COVID-19 were compared. Multivariate Cox regression analysis was performed to identify potential biomarkers for predicting disease progression. A concordance index (C-index), calibration curve, decision curve and the clinical impact curve were calculated to assess the predictive accuracy.ResultsThe data showed that the white blood cell count, neutrophil count and platelet count were normal on the day of hospital admission in most COVID-19 patients (87.9%, 85.1% and 88.7%, respectively). A total of 82.8% of severe patients had lymphopenia after the onset of symptoms, and as the disease progressed, there was marked lymphopenia. Multivariate Cox analysis showed that the neutrophil count (hazard ratio [HR] = 4.441, 95% CI = 1.954–10.090, p = 0.000), lymphocyte count (HR = 0.255, 95% CI = 0.097–0.669, p = 0.006) and platelet count (HR = 0.244, 95% CI = 0.111–0.537, p = 0.000) were independent risk factors for disease progression. The C-index (0.821 [95% CI, 0.746–0.896]), calibration curve, decision curve and the clinical impact curve showed that the nomogram can be used to predict the disease progression in COVID-19 patients accurately. In addition, the data involving the neutrophil count, lymphocyte count and platelet count (NLP score) have something to do with improving risk stratification and management of COVID-19 patients.ConclusionsWe designed a clinically predictive tool which is easy to use for assessing the progression risk of COVID-19, and the NLP score could be used to facilitate patient stratification management.

PATTERNS OF COMPLETE BLOOD COUNTS (CBC) IN PATIENTS WITH COVID19 INFECTION

2021 ◽  
pp. 51-53
Author(s):  
Chhavi Gupta ◽  
Subhash Bhardwaj
Keyword(s):  
Platelet Count ◽  
Absolute Neutrophil Count ◽  
Neutrophil Count ◽  
Eosinophil Count ◽  
Lymphocyte Count ◽  
Severe Disease ◽  
Clinical Status ◽  
Clinical Severity ◽  
Monocyte Count ◽  
Wbc Count

Background: COVID-19 is an ongoing pandemic caused by virus SARS-CoV-2. Many studies worldwide have documented hematological alterations in COVID-19. The present study also aimed to assess the CBC parameters in COVID-19 patients. Material And Methods: It was an observational study conducted in the Department of Pathology, Govt. Medical College, Jammu. COVID-19 patients admitted in the hospital were included in the study. Demographic details and clinical status were noted. EDTA anticoagulated blood samples received were processed on automated 5-part hematology analyzer for CBC. Various parameters obtained were evaluated and also compared with clinical severity of the patients. Results were tabulated and analysed statistically. Results: The study included 304 hospitalized COVID-19 patients. Males were 219 (72%) and females were 85 (28%). Median 6 age of patients was 55 years. Mean hemoglobin concentration was 12.05 g/dl (SD-1.93), mean RBC count was 4.21x10 /µL (SD3 3 0.69). Mean WBC count was 9.66x10 /µL (SD-4.80), mean absolute neutrophil count was 7.87x10 /µL (SD-4.63), mean absolute 3 3 lymphocyte count was 1.22x10 /µL (SD-0.77), mean absolute monocyte count was 0.52x10 /µL (SD-0.29), mean absolute 3 eosinophil count was 0.04 x10 /µL(SD-0.10). Mean NLR was 10.03 (SD-12.27), mean LMR was 2.84 (SD-2.02), mean PLR was 3 220.16 (SD-208.46). Mean platelet count was 187x10 /µL (SD-97.78). Patients with severe disease show signicantly raised WBC count and absolute neutrophil count, signicantly decreased absolute lymphocyte count, signicantly higher eosinophil count, NLR, PLR and signicantly decreased LMR with no signicant difference in absolute monocyte count and platelet count. Conclusion: Routine monitoring of CBC parameters in COVID – 19 patients during the course of illness is a simple, rapid means to assess disease severity and progression in these patients.

scholarly journals Correlation Analysis between the Viral Load and the Progression of COVID-19

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Wenyu Chen ◽  
Qinfeng Xiao ◽  
Zhixian Fang ◽  
Xiaodong Lv ◽  
Ming Yao ◽  
...  
Keyword(s):  
Viral Load ◽  
Nucleic Acid ◽  
Disease Progression ◽  
Neutrophil Count ◽  
Lymphocyte Count ◽  
Dynamic Change ◽  
Severe Disease ◽  
N Gene ◽  
Ct Value ◽  
Novel Coronavirus

Objectives. This study is aimed at exploring the relationship of the viral load of coronavirus disease 2019 (COVID-19) with lymphocyte count, neutrophil count, and C-reactive protein (CRP) and investigating the dynamic change of patients’ viral load during the conversion from mild COVID-19 to severe COVID-19, so as to clarify the correlation between the viral load and progression of COVID-19. Methods. This paper included 38 COVID-19 patients admitted to the First Hospital of Jiaxing from January 28, 2020, to March 6, 2020, and they were clinically classified according to the Guidelines on the Novel Coronavirus-Infected Pneumonia Diagnosis and Treatment. According to the instructions of the Nucleic Acid Detection Kit for the 2019 novel coronavirus (SARS-CoV-2), respiratory tract specimens (throat swabs) were collected from patients for nucleic acid testing. Patients’ lymphocyte count and neutrophil count were determined by blood routine examination, and CRP was measured by biochemical test. Results. The results of our study suggested that the cycle threshold (Ct) value of Nucleocapsid protein (N) gene examined by nucleic acid test was markedly positively correlated with lymphocyte count ( p = 0.0445 , R 2 = 0.1203 ), but negatively correlated with neutrophil count ( p = 0.0446 , R 2 = 0.1167 ) and CRP ( p = 0.0393 , R 2 = 0.1261 ), which indicated that patients with a higher viral load tended to have lower lymphocyte count but higher neutrophil count and CRP. Additionally, we detected the dynamic change of Ct value in patients who developed into a severe case, finding that viral load of 3 patients increased before disease progression, whereas this phenomenon was not found in 2 patients with underlying diseases. Conclusion. The results of this study demonstrated that viral load of SARS-CoV-2 is significantly negatively correlated with lymphocyte count, but markedly positively correlated with neutrophil count and CRP. The rise of viral load is very likely to be the key factor leading to the overloading of the body’s immune response and resulting in the disease progression into severe disease.

scholarly journals Nomogram to identify severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics: a multi-center study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yixing Yu ◽  
Ximing Wang ◽  
Min Li ◽  
Lan Gu ◽  
Zongyu Xie ◽  
...  
Keyword(s):  
Risk Factors ◽  
Calibration Curve ◽  
Severity Score ◽  
Early Stage ◽  
Area Under The Curve ◽  
Clinical Impact ◽  
Imaging Data ◽  
Net Benefit ◽  
Training Cohort ◽  
Independent Risk Factors

Abstract Background To develop and validate a nomogram for early identification of severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics. Methods The initial clinical and CT imaging data of 217 patients with COVID-19 were analyzed retrospectively from January to March 2020. Two hundred seventeen patients with 146 mild cases and 71 severe cases were randomly divided into training and validation cohorts. Independent risk factors were selected to construct the nomogram for predicting severe COVID-19. Nomogram performance in terms of discrimination and calibration ability was evaluated using the area under the curve (AUC), calibration curve, decision curve, clinical impact curve and risk chart. Results In the training cohort, the severity score of lung in the severe group (7, interquartile range [IQR]:5–9) was significantly higher than that of the mild group (4, IQR,2–5) (P < 0.001). Age, density, mosaic perfusion sign and severity score of lung were independent risk factors for severe COVID-19. The nomogram had a AUC of 0.929 (95% CI, 0.889–0.969), sensitivity of 84.0% and specificity of 86.3%, in the training cohort, and a AUC of 0.936 (95% CI, 0.867–1.000), sensitivity of 90.5% and specificity of 88.6% in the validation cohort. The calibration curve, decision curve, clinical impact curve and risk chart showed that nomogram had high accuracy and superior net benefit in predicting severe COVID-19. Conclusion The nomogram incorporating initial clinical and CT characteristics may help to identify the severe patients with COVID-19 in the early stage.

Evaluation of prognostic role of inflammatory index in glioblastoma multiforme patients undergoing to concomitant radio-chemotherapy.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e13549-e13549
Author(s):  
Valentina Fausti ◽  
Flavia Foca ◽  
Nada Riva ◽  
Alberto Bongiovanni ◽  
Lorena Gurrieri ◽  
...  
Keyword(s):  
Platelet Count ◽  
Glioblastoma Multiforme ◽  
Neutrophil Count ◽  
Lymphocyte Count ◽  
Statistical Significance ◽  
Prognostic Role ◽  
P Values ◽  
Inflammatory Index ◽  
Radio Chemotherapy

e13549 Background: Hematologic markers of inflammation have been shown to be prognostic in different malignancies. Also in glioblastoma multiforme (GBM) a prognostic role has been demonstrated. The purpose of this study is to evaluate retrospectively the prognostic role of these markers in patients receiving a concomitant radio-chemotherapy after surgery. Methods: Sixty-five GBM patients have been treated with concomitant radio-chemotherapy after surgery at our institute from 2008 to 2017. Information on blood counts were carried out the day before starting therapy and after the day before the last cycle of chemotherapy. Neutrophil/lymphocyte ratio (NLR) and Platelet/lymphocyte ratio (PLR) were computed as the ratio of the absolute neutrophil count and absolute platelet count by the absolute lymphocyte count respectively. Systemic Inflammatory Index (SII) was calculated as platelet count × neutrophil count/lymphocyte count. The optimal cut-point was obtained using X-tile software version 3.6.1. Results: NLR and PLR baseline value didn’t show a statistic a statistically significant prognostic role in PFS or OS. Patients with baseline SII < 480 showed both better PFS and OS (OS: 22.1 VS 11.8 mo p-values 0.0516; PFS: 10.6 VS 5.7 mo p-values 0.0351). Patients aged < 60 years showed better PFS and OS. (PFS 10.3 VS 5.5 p-values 0.0501; OS: 20.6 VS 11.2 mo p-values 0.0124). Statistical significance for SII and age was maintained for both PFS and OS in multivariate analysis as shown in Table 1. Baseline values of NLR PLR and SII have also been correlated with the best response and ORR without showing statistical significance. Conclusions: This restorative study confirms the prognostic value of inflammatory indices in patients with GBM. Correlation analysis with the methylation status of MGMT is ongoing.[Table: see text][Table: see text]

scholarly journals Can We Improve the Predictive Value of Interim PET/CT Using a New Prognostic Model for Advanced Hodgkin Lymphoma?

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3001-3001
Author(s):  
Eldad J. Dann ◽  
Osnat Bairey ◽  
Rachel Bar-Shalom ◽  
Tanya Mashiach ◽  
Elinor Barzilai ◽  
...  
Keyword(s):  
Risk Factors ◽  
Radiation Therapy ◽  
Disease Progression ◽  
Hodgkin Lymphoma ◽  
Lymphocyte Count ◽  
Prognostic Score ◽  
Univariate Analysis ◽  
Disease Stage ◽  
Interim Pet ◽  
Pet Ct

Abstract Introduction: The treatment of advanced Hodgkin lymphoma (HL) has undergone many changes in recent years. The original International Prognostic Score (IPS) introduced by Hasenclever et al (1998) was based on a cohort of 1618 patients (pts) mainly treated with MOPP-ABV or ABVD between the years 1983 and 1992. One third (33%) of those pts also underwent involved field radiation therapy (IFRT). Staging was based on CT. The 5-y freedom from progression (FFP) results ranged between 84% and 42%, depending on the presence of 0-≥5 risk factors. The IPS has been validated in a number of studies and settings. Currently, staging is based on baseline PET/CT, which upgrades the disease stage in 15% and downgrades it in 5% of pts compared to CT scan. Positive interim PET/CT (PET-2) is predictive of an inferior prognosis in pts with early and advanced HL. Based on these findings, several studies have used a positive PET-2 as an indication for therapy escalation. However, the majority of relapses still occur in pts with negative PET-2, highlighting the need for additional prognostic markers. We evaluated baseline factors and lab results in a prospectively collected database of pts enrolled in a multicenter clinical trial (NCT00392314) where treatment was modified based on PET-2 results. The current study aimed to develop a model for refined prediction of HL progression risk in advance-disease pts with negative PET-2, using baseline risk factors. Methods: Pts with advanced classic Hodgkin lymphoma (HL) were stratified according to their baseline IPS; treatment was modified according to PET-2 results. Pts with IPS 0-2 initially received 2 ABVD cycles and those with IPS ≥ 3 received 2 cycles of escalated BEACOPP (EB). In the former group, if PET-2 was positive without evidence of disease progression, therapy was escalated to EB with involved site radiation therapy (ISRT) given to residual masses. If PET-2 was negative in both IPS strata, 4 additional ABVD cycles were administered. We evaluated whether traditional IPS parameters continued to predict relapse when treatment was modified based on PET-2 results, and assessed the need for new cutoffs based on ROC curves using univariate and multivariate Cox proportional hazard models. Results: Of 185 enrolled pts, 33 (18%) experienced disease progression and 27 (15%) had a positive PET-2. The 5-y PFS for the whole group, PET-2 negative and PET-2 positive subgroups was 80%, 82% and 68%, respectively (p=0.07). Eight of 33 (28%) relapsed pts had a positive Deauville score (≥3). On univariate analysis of traditional IPS parameters, male gender, age >45, stage IV disease were not found to be associated with a significantly increased hazard ratio (HR) for progression. New cutoffs for lymphocyte count and albumin level predictive of relapse were determined. The following parameters were significantly (P<0.006) associated with lower PFS on univariate analysis: albumin <3.5gm/dL, hemoglobin <10.5 gm/dL, lymphocyte count <1400 or <11% of white blood cell (WBC) count. On multivariate analysis, albumin <3.5gm/dL, lymphocyte count <1400 or <11% of WBC remained significantly associated with relapse, with adjusted HRs of 2.2 (95% CI 1.1-4.5; P<0.03) and 2.6 (95% CI 1.1-6.2; P<0.025), respectively. Hence, a score was constructed using 0, 1 or 2 of these factors. Pts with 0-1 or 2 new risk factors and negative PET-2 had a relapse rate (RR) of 10% and 42%, respectively (HR=4.7; 95% CI 4.7-11), while in pts with positive PET-2 the RR was 30% (Table 1). However, one should bear in mind that pts with IPS 0-2 initiated therapy with ABVDx2 and those with IPS≥3 initiated therapy with EBx2. Conclusions: The current analysis, using data prospectively collected during a phase II study but analyzed retrospectively after pts had been stratified by IPS, suggests a scoring model that could refine the IPS-based identification of pts at a higher risk for disease progression, even if their PET-2 is negative. The findings imply that pts with 2 new risk factors (19% of pts) may need to initiate more intensive therapy than ABVD. However, given the retrospective nature of the analysis, its results should be interpreted with caution. The model needs to be verified in an independent cohort of pts with advanced HL using uniform treatment protocols. Table 1 Table 1. Disclosures Bairey: Janssen: Consultancy.

Myelodysplasia Following Therapy with Tumour Necrosis Factor-alpha (TNF α) Inhibitors - An Uncommon Occurence.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 4844-4844
Author(s):  
Anil V. Kamat ◽  
Raphael Ezekwesili ◽  
Yasser El-Miedany
Keyword(s):  
Bone Marrow ◽  
Platelet Count ◽  
Tumour Necrosis Factor ◽  
Neutrophil Count ◽  
Lymphocyte Count ◽  
Tumour Necrosis ◽  
Blood Count ◽  
Full Blood Count ◽  
Tnf Α ◽  
Necrosis Factor

Abstract Introduction-Tumour necrosis factor- alpha (TNF α) inhibitors such as infliximab & etanercept have various applications such as severe rheumatoid arthritis, seronegative spondyloarthritis, vasculitis, crohn’s disease & psoriasis. There have been few reports of haematological complications arising in patients treated with anti-TNF a therapies. There has been only one reported case of development of acute myeloid leukaemia after initiation of etanercept therapy. Case report-A 57year old gentleman with HLA B27 negative ankylosing spondylitis presented with chest infection. His full blood count showed Hb 5.9 g/l WBC 3.8 × 10^9/L Neutrophil count 2.7 × 10^9/L Lymphocyte count 0.7 × 10^9/L Platelet count 89 × 10^9/L & Reticulocyte count 21 × 10^9/L. Occasional myeloblasts were seen on the blood film. He had been on biological therapy for ankylosing spondylitis with infliximab 5mg/kg infusion on 8 weekly basis for 18 months which was stopped due to lack of efficacy. Subsequently he had been treated with etanercept 50 mg subcutaneous once weekly for the past 16 weeks prior to this presentation. His full blood count prior to initiation of infliximab & etanercept was Hb 11.6 g/l WBC 16 × 10^9/L Neutrophil count 12.8 × 10^9/L Lymphocyte count 2.1 × 10^9/L Platelet count 655 × 10^9/L and Hb 11.0 g/l WBC 8.2 × 10^9/L Neutrophil count 4.9 × 10^9/L Lymphocyte count 2.4 × 10^9/L Platelet count 591 × 10^9/L, respectively. He underwent bone marrow investigations. Bone marrow aspirate was aparticulate with dyshaemopoeisis. Dyserythropoeisis in form of irregular nuclei, occasional binucleated cells & delayed nucleo-cytoplasmic maturation was seen along with dysmyelopoeisis in form of binucleated cells & pelger forms. Blasts amounted to 14% of nucleated cells. Overall, impression was in keeping with refractory anemia with excess of blasts (RAEB-2). Trephine biopsy showed mildly hypocellular bone marrow with markedly disordered haemopoeisis. There was trilineage dysplasia with abundant micromegakaryocytes with immunocytochemistry for CD117 showing increased number of progenitors (10–20%). The appearances were in keeping with myelodysplasia with excess of CD117 positive progenitors. Cytogenetic study failed. The sepsis responded to broad spectrum antibiotics but he continues on red cell & platelet support on a weekly basis. Conclusion The chronology points to a TNF α inhibitor mediated effect in this patient. Despite the close temporal association between exposure to TNF α inhibitor therapy and the presentation of myelodysplasia in this patient, a causal relationship cannot be established with confidence. Tumour necrosis factor inhibitors find wide applications in inflammatory conditions with high TNF. Such treatment may be associated with uncommon complications. It is of interest to note there are ongoing trials using TNF α inhibitors in myelodysplastic syndrome. Checking a full blood count periodically, and immediately if the patient is unwell is recommended.

scholarly journals Risk factors of severe cases with COVID-19: a meta-analysis

2020 ◽  
Vol 148 ◽  
Author(s):  
Mingchun Ou ◽  
Jieyun Zhu ◽  
Pan Ji ◽  
Hongyuan Li ◽  
Zhimei Zhong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Platelet Count ◽  
Weighted Mean Difference ◽  
Meta Analysis ◽  
Severe Disease ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Electronic Search ◽  
Low Platelet Count ◽  
D Dimer

Abstract Our study aimed to systematically analyse the risk factors of coronavirus disease 2019 (COVID-19) patients with severe disease. An electronic search in eight databases to identify studies describing severe or critically ill COVID-19 patients from 1 January 2020 to 3 April 2020. In the end, we meta-analysed 40 studies involving 5872 COVID-19 patients. The average age was higher in severe COVID-19 patients (weighted mean difference; WMD = 10.69, 95%CI 7.83–13.54). Patients with severe disease showed significantly lower platelet count (WMD = −18.63, 95%CI −30.86 to −6.40) and lymphocyte count (WMD = −0.35, 95%CI −0.41 to −0.30) but higher C-reactive protein (CRP; WMD = 42.7, 95%CI 31.12–54.28), lactate dehydrogenase (LDH; WMD = 137.4, 95%CI 105.5–169.3), white blood cell count（WBC), procalcitonin（PCT）, D-dimer, alanine aminotransferase (ALT), aspartate aminotransferase (AST) and creatinine（Cr）. Similarly, patients who died showed significantly higher WBC, D-dimer, ALT, AST and Cr but similar platelet count and LDH as patients who survived. These results indicate that older age, low platelet count, lymphopenia, elevated levels of LDH, ALT, AST, PCT, Cr and D-dimer are associated with severity of COVID-19 and thus could be used as early identification or even prediction of disease progression.

scholarly journals Nomogram to identify severe Coronavirus Disease 2019 (COVID-19) based on initial clinical and CT characteristics: a multi-center study

2020 ◽  
Author(s):  
Yixing Yu ◽  
Ximing Wang ◽  
Min Li ◽  
Lan Gu ◽  
Zongyu Xie ◽  
...  
Keyword(s):  
Risk Factors ◽  
Calibration Curve ◽  
Severity Score ◽  
Early Stage ◽  
Area Under The Curve ◽  
Clinical Impact ◽  
Imaging Data ◽  
Net Benefit ◽  
Training Cohort ◽  
Independent Risk Factors

Abstract Background: To develop and validate a nomogram for early identification of severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics.Methods: The initial clinical and CT imaging data of 217 patients with COVID-19 were analyzed retrospectively from January to March 2020. 217 patients with 146 mild cases and 71 severe cases were randomly divided into training and validation cohorts. Independent risk factors were selected to construct the nomogram for predicting severe COVID-19. Nomogram performance in terms of discrimination and calibration ability was evaluated using the area under the curve (AUC), calibration curve, decision curve, clinical impact curve and risk chart.Results: In the training cohort, the severity score of lung in the severe group (7, interquartile range [IQR]:5-9) was significantly higher than that of the mild group (4, IQR:2-5) (P < 0.001). Age, density, mosaic perfusion sign and severity score of lung were independent risk factors for severe COVID-19. The nomogram had a AUC of 0.929 (95% CI, 0.889-0.969), sensitivity of 84.0% and specificity of 86.3%, in the training cohort, and a AUC of 0.936 (95% CI, 0.867-1.000), sensitivity of 90.5% and specificity of 88.6% in the validation cohort. The calibration curve, decision curve, clinical impact curve and risk chart showed that nomogram had high accuracy and superior net benefit in predicting severe COVID-19.Conclusion: The nomogram incorporating initial clinical and CT characteristics may help to identify the severe patients with COVID-19 in the early stage.

scholarly journals Histological Severity Risk Factors Identification in Juvenile-Onset Recurrent Respiratory Papillomatosis: How Immunohistochemistry and AI Algorithms Can Help?

2021 ◽  
Vol 11 ◽  
Author(s):  
Charles Lépine ◽  
Paul Klein ◽  
Thibault Voron ◽  
Marion Mandavit ◽  
Dominique Berrebi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Image Analysis ◽  
Deep Learning ◽  
Severe Disease ◽  
Recurrent Respiratory Papillomatosis ◽  
Juvenile Onset ◽  
Strong Intensity ◽  
Potential Biomarker ◽  
Significant Difference

Juvenile-onset recurrent respiratory papillomatosis (JoRRP) is a condition characterized by the repeated growth of benign exophytic papilloma in the respiratory tract. The course of the disease remains unpredictable: some children experience minor symptoms, while others require multiple interventions due to florid growth. Our study aimed to identify histologic severity risk factors in patients with JoRRP. Forty-eight children from two French pediatric centers were included retrospectively. Criteria for a severe disease were: annual rate of surgical endoscopy ≥ 5, spread to the lung, carcinomatous transformation or death. We conducted a multi-stage study with image analysis. First, with Hematoxylin and eosin (HE) digital slides of papilloma, we searched for morphological patterns associated with a severe JoRRP using a deep-learning algorithm. Then, immunohistochemistry with antibody against p53 and p63 was performed on sections of FFPE samples of laryngeal papilloma obtained between 2008 and 2018. Immunostainings were quantified according to the staining intensity through two automated workflows: one using machine learning, the other using deep learning. Twenty-four patients had severe disease. For the HE analysis, no significative results were obtained with cross-validation. For immunostaining with anti-p63 antibody, we found similar results between the two image analysis methods. Using machine learning, we found 23.98% of stained nuclei for medium intensity for mild JoRRP vs. 36.1% for severe JoRRP (p = 0.041); and for medium and strong intensity together, 24.14% for mild JoRRP vs. 36.9% for severe JoRRP (p = 0.048). Using deep learning, we found 58.32% for mild JoRRP vs. 67.45% for severe JoRRP (p = 0.045) for medium and strong intensity together. Regarding p53, we did not find any significant difference in the number of nuclei stained between the two groups of patients. In conclusion, we highlighted that immunochemistry with the anti-p63 antibody is a potential biomarker to predict the severity of the JoRRP.

scholarly journals Risk factors for disease progression in Japanese patients with COVID-19 with no or mild symptoms on admission

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Toshifumi Ninomiya ◽  
Kohei Otsubo ◽  
Teppei Hoshino ◽  
Mototsugu Shimokawa ◽  
Megumi Nakazawa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Disease Progression ◽  
Old Age ◽  
Serum Ferritin ◽  
Severe Disease ◽  
Laboratory Data ◽  
Japanese Patients ◽  
High Serum ◽  
Disease Stage ◽  
The Mean

Abstract Background Although the risk factors for coronavirus disease 2019 (COVID-19) mortality have been identified, there is limited information about the risk factors for disease progression after hospitalization among Japanese patients with COVID-19 exhibiting no or mild symptoms. Methods All 302 consecutive patients who were admitted to our institutions and diagnosed with COVID-19 between March and December 2020 were retrospectively assessed. Ultimately, 210 adult patients exhibiting no or mild symptoms on admission were included in the analysis. They were categorized into the stable (no oxygen needed) and worsened (oxygen needed) groups, and their characteristics and laboratory data were compared. Results Among 210 patients, 49 progressed to a severe disease stage, whereas 161 did not. The mean patient age was 52.14 years, and 126 (60.0%) patients were male. The mean body mass index (BMI) was 23.0 kg/m2, and 71 patients were overweight (BMI ≥ 25 kg/m2). Multivariate logistic analysis showed that old age, overweight, diabetes mellitus (DM), and high serum ferritin levels were independent risk factors for disease progression. Conclusions Clinicians should closely observe patients with COVID-19, especially those with risk factors such as old age, overweight, DM, and high serum ferritin levels, regardless of whether they have no or mild symptoms.

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