DOZ047.79: Bronchoscopic treatment of plastic bronchitis in children

2019 ◽  
Vol 32 (Supplement_1) ◽  
Author(s):  
M Y Erdas ◽  
N Valiyev ◽  
K K Cerit ◽  
Y Gokdemir ◽  
G Kiyan

Abstract Purpose Plastic bronchitis or cast bronchitis is a rare condition characterized by the formation of large gelatinous or rigid airway casts. Classification of plastic bronchitis is done by disease association and cast histology. This rare condition can cause airway obstruction and there is no standardized treatment. Here are presented two cases with plastic bronchitis treated by bronchoscopic removal of casts in our clinic. Patients Case 1: A 9-year-old boy presented with wheezing, cough, and respiratory distress. He expectorated the cast spontaneously and the cast was misdiagnosed as germinative membrane of a hydatid cyst at the previous center. Total collapse of the left hemithorax was seen on chest X-ray. Any underlying disease was not detected. The plastic-like solid structure was detected and easily extracted from the bronchial tree. Pathology results of the casts were eosinophilic mucoid casts. The patient experienced three bronchoscopic removals and had no recurrence thereafter for two years. Case 2: A 7-year-old girl presented with persistent cough and respiratory distress. The patient was referred to our center with the diagnosis of foreign body aspiration. Total collapse of the right middle and lower segment and partial collapse of the upper segment were seen on chest X-ray. Previously, she was diagnosed with reactive airway disease. The plastic-like semisolid structure was detected during bronchoscopy its extraction from the bronchial tree was not easy but was possible. Pathology results were eosinophilic mucoid and fibrinotic casts. This patient still needs bronchoscopy for cast removal after 12 bronchoscopic removals but her symptoms and bronchoscopy findings have regressed with time. Conclusion Bronchoscopic extraction of casts provides fast improvement of patients’ symptoms and postoperative chest X-rays, but recurrence of cast formation is common. Nevertheless, it is the mostly chosen therapy in the literature. Further researches in this area are required.

2021 ◽  
Vol 35 (2) ◽  
pp. 93-94
Author(s):  
Jyotsna Bhushan ◽  
Shagufta Iqbal ◽  
Abhishek Chopra

A clinical case report of spontaneous pneumomediastinum in a late-preterm neonate, chest x-ray showing classical “spinnaker sail sign,” which was managed conservatively and had excellent prognosis on conservative management. Respiratory distress in a preterm neonate is a common clinical finding. Common causes include respiratory distress syndrome, transient tachypnea of the newborn, pneumonia, and pneumothorax. Pneumomediastinum is not very common cause of respiratory distress and more so spontaneous pneumomediastinum. We report here a preterm neonate with spontaneous pneumomediastinum who had excellent clinical recovery with conservative management. A male baby was delivered to G3P1A1 mother at 34 + 6 weeks through caesarean section done due to abruptio placenta. Apgar scores were 8 and 9. Maternal antenatal history was uneventful and there were no risk factors for early onset sepsis. Baby had respiratory distress soon after birth with Silverman score being 2/10. Baby was started on oxygen (O2) by nasal prongs through blender 0.5 l/min, FiO2 25%, and intravenous fluids. Blood gas done was normal. Possibility of transient tachypnea of newborn or mild hyaline membrane disease was kept. Respiratory distress increased at 20 h of life (Silverman score: 5), urgent chest x-ray done revealed “spinnaker sign” suggestive of pneumomediastinum, so baby was shifted to O2 by hood with FiO2 being 70%. Blood gas repeated was normal. Baby was managed conservatively on intravenous fluids and O2 by hood. Baby was gradually weaned off from O2 over next 5 days. As respiratory distress decreased, baby was started on orogastric feed, which baby tolerated well and then was switched to oral feeds. Serial x-rays showed resolution of pneumomediastinum. Baby was discharged on day 7 of life in stable condition on breast feeds and room air.


1998 ◽  
Vol 5 (3) ◽  
pp. 219-221 ◽  
Author(s):  
EZ Phillipos ◽  
K Libsekal

This paper describes the case of a 3 kg neonate who had congenital lobar emphysema of the left upper lobe (LUL). He was in severe respiratory distress with a fraction of inspired oxygen of 0.8. Chest x-ray showed hyperlucent expanded left hemithorax and marked mediastinal shift. Following flexible bronchoscopy and introduction of ultrathin bronchoscope into the LUL bronchus, symptoms and chest x-ray improved markedly. Flexible bronchoscopy resulted in emergency relief of his initial respiratory distress, and left upper lobe lobectomy was performed electively three days later.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Makoto Nishimori ◽  
Kunihiko Kiuchi ◽  
Kunihiro Nishimura ◽  
Kengo Kusano ◽  
Akihiro Yoshida ◽  
...  

AbstractCardiac accessory pathways (APs) in Wolff–Parkinson–White (WPW) syndrome are conventionally diagnosed with decision tree algorithms; however, there are problems with clinical usage. We assessed the efficacy of the artificial intelligence model using electrocardiography (ECG) and chest X-rays to identify the location of APs. We retrospectively used ECG and chest X-rays to analyse 206 patients with WPW syndrome. Each AP location was defined by an electrophysiological study and divided into four classifications. We developed a deep learning model to classify AP locations and compared the accuracy with that of conventional algorithms. Moreover, 1519 chest X-ray samples from other datasets were used for prior learning, and the combined chest X-ray image and ECG data were put into the previous model to evaluate whether the accuracy improved. The convolutional neural network (CNN) model using ECG data was significantly more accurate than the conventional tree algorithm. In the multimodal model, which implemented input from the combined ECG and chest X-ray data, the accuracy was significantly improved. Deep learning with a combination of ECG and chest X-ray data could effectively identify the AP location, which may be a novel deep learning model for a multimodal model.


2011 ◽  
Vol 2011 ◽  
pp. 1-6
Author(s):  
Aristida Georgescu ◽  
Crinu Nuta ◽  
Simona Bondari

Unilateral primary pulmonary hypoplasia is rare in adulthood (UPHA); it is characterized by a decreased number of bronchial segmentation and decreased/absent alveolar air space. Classical chest X-ray may be confusing, and the biological tests are unspecific. We present a case of UPHA in a 60-year-old female, smoker, with 3 term normal deliveries, who presented with late recurrent pneumonias and bronchiectasis-type symptomathology, arterial hypertension, and obesity. Chest X-rays revealed opacity in the left lower pulmonary zone, an apparent hypoaerated upper left lobe and left deviation of the mediastinum. Preoperatory multidetector computer tomography (MDCT) presented a small retrocardiac left lung with 5-6 bronchial segmentation range and cystic appearance. After pneumonectomy the gross specimen showed a small lung with multiple bronchiectasis and small cysts, lined by hyperplasic epithelium, surrounded by stromal fibrosclerosis. We concluded that this UPHA occurred in the 4–7 embryonic weeks, and the 3D MDCT reconstructions offered the best noninvasive diagnosis.


2016 ◽  
Vol 15 (1) ◽  
pp. 30-32
Author(s):  
Legate Philip ◽  
◽  
Neil Andrews ◽  

Acute mitral regurgitation (acute MR) is a rare cause of acute respiratory distress, which can present diagnostic challenges. We present the case of a 57 year old man who developed acute shortness of breath subsequently associated with fever, raised white cells and elevated CRP. Chest x-ray revealed unilateral shadowing and he was treated for pneumonia, despite the finding of severe mitral regurgitation on echo. Failure to respond to antibiotic treatment following 3 weeks on ITU led to the consideration of acute MR as the cause of his symptoms and he responded well to diuretics. He subsequently underwent mitral valve repair. The causes and clinical presentations of this condition are discussed.


2021 ◽  
pp. 31-32
Author(s):  
Sheeba Rana ◽  
Vicky Bakshi ◽  
Yavini Rawat ◽  
Zaid Bin Afroz

INTRODUCTION: Various chest X-ray scoring systems have been discovered and are employed to correlate with clinical severity, outcome and progression of diseases. With, the coronavirus outbreak, few chest radiograph classication were formulated, like the BSTI classication and the Brixia chest X-ray score. Brixia CXR scoring is used for assessing the clinical severity and outcome of COVID-19. This study aims to compare the Brixia CXR score with clinical severity of COVID-19 patients. MATERIAL& METHODS:This was a retrospective study in which medical records of patients aged 18 years or above, who tested for RTPCR or st st Rapid Antigen Test (RAT) for COVID positive from 1 February 2021 to 31 July 2021 (6 months) were taken. These subjects were stratied into mild, moderate and severe patients according to the ICMR guidelines. Chest X Rays were obtained and lesions were classied according to Brixia scoring system. RESULTS: Out of these 375 patients, 123 (32.8%) were female and 252 (67.2%) were male subjects. The average brixia score was 11.12. Average Brixia CXR score for mild, moderate and severe diseased subjects were 5.23, 11.20, and 14.43 respectively. DISCUSSION:The extent of chest x-ray involvement is proportional to the clinical severity of the patient. Although, a perplexing nding was that the average Brixia score of the female subjects were slightly higher than their male counterparts in the same clinical groups. CONCLUSION: Brixia CXR score correlates well with the clinical severity of the COVID-19.


2013 ◽  
Vol 53 (1) ◽  
pp. 6
Author(s):  
Indah Nurhayati ◽  
Muhammad Supriatna ◽  
Kamilah Budhi Raharjani ◽  
Eddy Sudijanto

Background Most infants and children admitted to the pediatricintensive care unit (PICU) have respiratory distress and pulmonarydisease as underlying conditions. Mechanical ventilation may beused to limit morbidity and mortality in children with respiratoryfailure.Objective To assess a correlation between chest x-ray findingsand outcomes of patients with mechanical ventilation.Methods This retrospective study was held in Dr. KariadiHospital, Semarang, Indonesia. Data was collected from themedical records of children admitted to the PICU from Januaryto December 2010, who suffered from respiratory distress andused mechanical ventilation. We compared chest x-ray findings tothe outcomes of patients. Radiological expertise was provided byradiologists on duty at the time. Chi-square and logistic regressiontests were used for statistical analysis.Results There were 63 subjects in our study, consisting of 28 malesand 35 females. Patient outcomes were defined as survived or died,43 subjects ( 68%) and 20 subjects (3 2%), respectively. Chest x-rayfindings revealed the following conditions: bronchopneumonia48% (P=0.298; 95%CI 0.22 to 1.88), pleural effusion 43%(P=0.280; 95%CI 0.539 to 4.837) , pulmonary edema 6%(P=0.622; 95%CI 0.14 to 14.62) and atelectasis 3% (P=0.538;95%CI 0.03 to 7 .62). None of the chest x-ray findings significantlycorrelated to patient outcomes.Conclusion Chest x-ray findings do not correlate to patientoutcomes in pediatric subjects with mechanical ventilation inthe PICU of Dr. Kariadi Hospital, Semarang, Indonesia.


2018 ◽  
Vol 35 (10) ◽  
pp. 1032-1038 ◽  
Author(s):  
Aaron S. Weinberg ◽  
William Chang ◽  
Grace Ih ◽  
Alan Waxman ◽  
Victor F. Tapson

Objective: Computed tomography angiography is limited in the intensive care unit (ICU) due to renal insufficiency, hemodynamic instability, and difficulty transporting unstable patients. A portable ventilation/perfusion (V/Q) scan can be used. However, it is commonly believed that an abnormal chest radiograph can result in a nondiagnostic scan. In this retrospective study, we demonstrate that portable V/Q scans can be helpful in ruling in or out clinically significant pulmonary embolism (PE) despite an abnormal chest x-ray in the ICU. Design: Two physicians conducted chart reviews and original V/Q reports. A staff radiologist, with 40 years of experience, rated chest x-ray abnormalities using predetermined criteria. Setting: The study was conducted in the ICU. Patients: The first 100 consecutive patients with suspected PE who underwent a portable V/Q scan. Interventions: Those with a portable V/Q scan. Results: A normal baseline chest radiograph was found in only 6% of patients. Fifty-three percent had moderate, 24% had severe, and 10% had very-severe radiographic abnormalities. Despite the abnormal x-rays, 88% of the V/Q scans were low probability for a PE despite an average abnormal radiograph rating of moderate. A high-probability V/Q for PE was diagnosed in 3% of the population despite chest x-ray ratings of moderate to severe. Six patients had their empiric anticoagulation discontinued after obtaining the results of the V/Q scan, and no anticoagulation was started for PE after a low-probability V/Q scan. Conclusion: Despite the large percentage of moderate-to-severe x-ray abnormalities, PE can still be diagnosed (high-probability scan) in the ICU with a portable V/Q scan. Although low-probability scans do not rule out acute PE, it appeared less likely that any patient with a low-probability V/Q scan had severe hypoxemia or hemodynamic instability due to a significant PE, which was useful to clinicians and allowed them to either stop or not start anticoagulation.


2021 ◽  
Author(s):  
Hamzeh Asgharnezhad ◽  
Afshar Shamsi ◽  
Roohallah Alizadehsani ◽  
Abbas Khosravi ◽  
Saeid Nahavandi ◽  
...  

Abstract Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate where and when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems.


Author(s):  
Satyanand Sathi ◽  
Richa Tiwari ◽  
Savita Verma ◽  
Anil Kumar Garg ◽  
Virendra Singh Saini ◽  
...  

Recent literature has reported that radiological features of coronavirus disease (COVID-19) patients are influenced by computed tomography. This study aimed to assess the characteristic chest X-ray features of COVID-19 and correlate them with clinical outcomes of patients. This retrospective study included 120 COVID-19 patients. Baseline chest X-rays and serial chest X-rays were reviewed. A severity index in the form of maximum radiological assessment of lung edema (RALE) score was calculated for each lung, and scores of both the lungs were summed to obtain a final score. The mean ± standard deviation (SD) and frequency (%) were determined, and an unpaired t test, Spearman’s rank correlation coefficient, and logistic regression analyses were performed for statistical analyses. Among 120 COVID-19 patients, 74 (61.67%) and 46 (38.33%) were males and females, respectively; 64 patients (53.33%) had ground-glass opacities (GGO), 55 (45.83%) had consolidation, and 38 (31.67%) had reticular-nodular opacities, with lower zone distribution (50%) and peripheral distribution (41.67%). Baseline chest X-ray showed a sensitivity of 63.3% in diagnosing typical findings of SARS-CoV-2 pneumonia. The maximum RALE score was 2.13 ± 1.9 in hospitalized patients and 0.57 ± 0.77 in discharged patients ( p value <0.0001). Spearman’s rank correlation coefficient between maximum RALE score and clinical outcome parameters was as follows: age, 0.721 ( p value <0.00001); >10 days of hospital stay, 0.5478 ( p value <0.05); ≤10 days of hospital stay, 0.5384 ( p value <0.0001); discharged patients, 0.5433 ( p value <0.0001); and death, 0.6182 ( p value = 0.0568). The logistic regression analysis revealed that maximum RALE scores (0.0932 [0.024–0.367]), (10.730 [2.727–42.206]), (1.258 [0.990–1.598]), and (0.794 [0.625–1.009]) predicted discharge, death, >10 days of hospital stay, and ≤10 days of hospital stay, respectively. The study findings suggested that the RALE score can quantify the extent of COVID-19 and can predict the prognosis of patients.


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