Life-threatening presentation of a parahiatal hernia after esophagectomy: a case report and review of the literature

2021 ◽  
Vol 14 (6) ◽  
pp. e242158
Author(s):  
Camille Plourde ◽  
Émilie Comeau

A woman presented to our hospital with acute abdominal pain 7 months following an oesophagectomy. A chest X-ray revealed a new elevation of the left diaphragm. CT demonstrated a large left diaphragmatic hernia incarcerated with non-enhancing transverse colon and loops of small bowel. She deteriorated rapidly into obstructive shock and was urgently brought to the operating room for a laparotomy. The diaphragmatic orifice was identified in a left parahiatal position, consistent with a parahiatal hernia. Incarcerated necrotic transverse colon and ischaemic loops of small bowel were resected, and the diaphragmatic defect was closed primarily. Because of haemodynamic instability, the abdomen was temporarily closed, and a second look was performed 24 hours later, allowing anastomosis and definitive closure. Parahiatal hernias are rare complications following surgical procedures and can lead to devastating life-threatening complications, such as an obstructive shock. Expeditious diagnosis and management are required in the acute setting.

2020 ◽  
Vol 2020 (7) ◽  
Author(s):  
Narendra Pandit ◽  
Abhijeet Kumar ◽  
Tek Narayan Yadav ◽  
Qamar Alam Irfan ◽  
Sujan Gautam ◽  
...  

Abstract Gastric volvulus is a rare abnormal rotation of the stomach along its axis. It is a surgical emergency, hence requires prompt diagnosis and treatment to prevent life-threatening gangrenous changes. Hence, a high index of suspicion is required in any patients presenting with an acute abdomen in emergency. The entity can present acutely with pain abdomen and vomiting, or as chronic with non-specific symptoms. Chest X-ray findings to diagnose it may be overlooked in patients with acute abdomen. Here, we report three patients with gastric volvulus, where the diagnosis was based on the chest X-ray findings, confirmed with computed tomography, and managed successfully with surgery.


2010 ◽  
Vol 92 (5) ◽  
pp. e53-e54 ◽  
Author(s):  
Somprakas Basu ◽  
Shilpi Bhadani ◽  
Vijay K Shukla

Bilothorax is a rare complication of biliary peritonitis and, if not treated promptly, can be life-threatening. We report a case of a middle-aged woman who had undergone a bilio-enteric bypass and subsequently a biliary leak developed, which finally led to intra-abdominal biliary collection and spontaneous bilothorax. The clinical course was rapid and mimicked venous thromboembolism, myocardial infarction and pulmonary oedema, which led to a delay in diagnosis and management and finally death. We high-light the fact that bilothorax, although a rare complication of biliary surgery, should always be considered as a probable cause of massive effusion and sudden-onset respiratory and cardiovascular collapse in the postoperative period. A chest X-ray and a diagnostic pleural tap can confirm the diagnosis. Once detected, an aggressive management should be instituted to prevent organ failure and death.


1982 ◽  
Vol 17 (4) ◽  
pp. 65-70
Author(s):  
Lawrence Kaplan ◽  
Michael Young ◽  
Leonard Krilov

2020 ◽  
Vol 20 (S14) ◽  
Author(s):  
Qingfeng Wang ◽  
Qiyu Liu ◽  
Guoting Luo ◽  
Zhiqin Liu ◽  
Jun Huang ◽  
...  

Abstract Background Pneumothorax (PTX) may cause a life-threatening medical emergency with cardio-respiratory collapse that requires immediate intervention and rapid treatment. The screening and diagnosis of pneumothorax usually rely on chest radiographs. However, the pneumothoraces in chest X-rays may be very subtle with highly variable in shape and overlapped with the ribs or clavicles, which are often difficult to identify. Our objective was to create a large chest X-ray dataset for pneumothorax with pixel-level annotation and to train an automatic segmentation and diagnosis framework to assist radiologists to identify pneumothorax accurately and timely. Methods In this study, an end-to-end deep learning framework is proposed for the segmentation and diagnosis of pneumothorax on chest X-rays, which incorporates a fully convolutional DenseNet (FC-DenseNet) with multi-scale module and spatial and channel squeezes and excitation (scSE) modules. To further improve the precision of boundary segmentation, we propose a spatial weighted cross-entropy loss function to penalize the target, background and contour pixels with different weights. Results This retrospective study are conducted on a total of eligible 11,051 front-view chest X-ray images (5566 cases of PTX and 5485 cases of Non-PTX). The experimental results show that the proposed algorithm outperforms the five state-of-the-art segmentation algorithms in terms of mean pixel-wise accuracy (MPA) with $$0.93\pm 0.13$$ 0.93 ± 0.13 and dice similarity coefficient (DSC) with $$0.92\pm 0.14$$ 0.92 ± 0.14 , and achieves competitive performance on diagnostic accuracy with 93.45% and $$F_1$$ F 1 -score with 92.97%. Conclusion This framework provides substantial improvements for the automatic segmentation and diagnosis of pneumothorax and is expected to become a clinical application tool to help radiologists to identify pneumothorax on chest X-rays.


2014 ◽  
pp. 113-25
Author(s):  
Kemalasari Nas Darisan ◽  
Jamal Zaini ◽  
Yoga Yuniadi

Amiodarone is an antiarrhythmic agent commonly used to treat supraventricular and ventricular arrhythmias. The drug prevents the recurrence of life-threatening ventricular arrhythmias and produces a modest reduction of sudden deaths in high-risk patients. This drug is an iodine-containing compound that tends to accumulate in several organs, including the lungs. It has been associated with a variety of adverse events. Of these events, the most serious is amiodarone pulmonary toxicity. Although the incidence of this complication has decreased with the use of lower doses of amiodarone, it can occur with any dose. Because amiodarone is widely used, all clinicians should be vigilant of this possibility. Pulmonary toxicity usually manifests as an acute or subacute pneumonitis, typically with diffuse infiltrates on chest x-ray and high-resolution computed tomography. Other, more localized, forms of pulmonary toxicity may occur, including pleural disease, migratory infiltrates, and single or multiple nodules. With early detection, the prognosis is good. Most patients diagnosed promptly respond well to the withdrawal of amiodarone and the administration of corticosteroids, which are usually given for four to 12 months. It is important that physicians be familiar with amiodarone treatment guidelines and follow published recommendations for the monitoring of pulmonary as well as extrapulmonary adverse effects.


2011 ◽  
Vol 2011 ◽  
pp. 1-4 ◽  
Author(s):  
C. M. Steger

Despite their benign character, intrapericardial lipomas can cause life-threatening complications by rapid growth. This paper presents a case of an intrapericardial lipoma in an almost asymptomatic 41-year-old female patient only suffering from mild dyspnoea on exertion. The tumour was found incidentally by chest X-ray. Echocardiographic examination and a CT scan of the thorax revealed a 16 × 14 × 12 cm lipomatous tumour mass highly suspective of a lipoma. Histological examination of excised tumour specimens confirmed the diagnosis of a lipoma. The patient is currently asymptomatic and has not presented with evidence of recurrence at the 6-month followup.


2017 ◽  
Vol 4 (6) ◽  
pp. 1547 ◽  
Author(s):  
Rishi K. Sharma ◽  
Atul Luhadia ◽  
Shanti K. Luhadia ◽  
Yash Mathur ◽  
Harshil Pandya ◽  
...  

Background: Silicosis is an occupational lung disease caused by inhalation of dust containing crystalline silica particles of size 0.5-5 microns in diameter. It commonly occurs in workers involved in quarrying, mining, sandblasting, tunneling, foundry work and ceramics. Pneumothorax is one of the complications of silicosis. The occurrence of pneumothorax in a patient with silicosis is a rare event, but it may be fatal. The incidence of secondary spontaneous pneumothorax (SSP) in silicosis as such is not known. This study aims to report the cases of secondary spontaneous pneumothorax in patients of silicosis in Southern part of Rajasthan.Methods: 50 patients of silicosis established by historical, clinical evaluation and radiological evidence with increased dyspnoea were included in the study. In all patients Chest X ray was done immediately.Results: Among 50 patients of silicosis with increased dyspnoea, Chest X ray showed pneumothorax in 20 patients of which 4 had bilateral pneumothorax, 7 had right pneumothorax and 9 had left pneumothorax. The mean duration of exposure to silica particles was 10 years (5 to 15 years). All the patients had various degrees of dyspnoea and chest pain. Tube thoracostomy was performed in 15 patients while 5 patients were managed conservatively with oxygen and bronchodilators.Conclusions: Our study showed an increased incidence of secondary pneumothorax in silicosis patients. The occurrence of pneumothorax, though rare in silicosis is a potentially life-threatening complication and may cause serious morbidity and mortality. The patients of silicosis who develop sudden onset of dyspnoea should be promptly investigated for this complication.


2019 ◽  
Vol 2 (1) ◽  
pp. 57
Author(s):  
Alfian Nur Rosyid ◽  
M. Yamin ◽  
Arina Dery Puspitasari

Pulmonary embolism is a common condition and sometimes can be life-threatening. A proper diagnosis can reduce mortality. Some examinations are needed to diagnose pulmonary embolism, including assessing the risk factors, clinical examination, D-dimer tests, and imaging. Imaging is necessary when the previous assessment requires further investigation. There are more imaging that can be used to diagnose and assess the severity of pulmonary embolism. However, it is still controversial regarding imaging modalities for optimizing pulmonary embolism diagnose. Chest X-Ray cannot exclude pulmonary embolism, but it is needed to guide the next examinations and to find alternative diagnoses. Pulmonary Multi-Detector CT Angiography is the gold standard to diagnose pulmonary embolism.


2022 ◽  

Acute abdominal pain is one of the most common chief complaints in the acute setting all over the world. The definitive diagnoses of these patients vary depending on age, gender, geographical and sociodemographic characteristics etc. Apart from these, aging of the population, obesity, advanced diagnostic imaging modalities and changes in nutritional habits also have an impact on the rates of specific diagnoses. On the other hand, nonspecific abdominal pain constitutes almost half of all visits due to acute abdominal pain in the acute care setting. This phenomenon is the main differential diagnostic problem in the management of these patients because missing a life-threatening condition can cause enormous medicolegal problems for the caregivers. Certain diagnostic scoring systems have also been developed to facilitate recognition and management of these conditions. This article aims to review the entity and underline the challenges it can bring to the scene.


2020 ◽  
Author(s):  
Mohammad Helal Uddin ◽  
Mohammad Nahid Hossain ◽  
K. Thapa ◽  
S.-H Yang

BACKGROUND COVID-19 is a life-threatening infectious disease that has become a pandemic for the time being. The virus grows within the lower respiratory tract where early-stage symptoms(like- cough, fever, sore throat, etc.) develop and then it causes lung infection(pneumonia) OBJECTIVE This paper proposed a new methodology of artificial testing whether a patient has been infected by COVID-19 or not METHODS We have presented a prediction model based on, Convolutional Neural Networks(CNN) and our own developed mathematical equation based algorithm named SymptomNet. The CNN algorithm classifies the lung infection(pneumonia) from frontal chest X-ray images, while the symptoms analyzing algorithm(SymptomNet) predicts the possibility of COVID-19 infection from developed symptoms in a patient RESULTS The model has the accuracy of 96% while predicting COVID-19 patients. In this Model, the CNN classifier has the accuracy of around 96% and the SymptomNet algorithm has the accuracy of 97%. CONCLUSIONS This research work obtained a promising accuracy while predicting COVID-19 infected patients. The proposed model can be ubiquitously used at a low cost with high accuracy.


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