Gelatinous Pleural Effusion: A Diagnostic Challenge for Pleural Mesothelioma in an 80-Year-Old Man.

BACKGROUND Gelatinous pleural effusion, due to raised hyaluronic acid, can be associated with pleural infection and malignancies, such as tuberculosis, metastatic pleural disease, and mesothelioma. This report is of an 80-year-old man presenting with a gelatinous pleural effusion and diagnosis of pleural mesothelioma. CASE REPORT An 80-year-old man with diabetes mellitus, ischemic heart disease, metastatic prostate cancer, 30-pack-year smoking history, and 5-year history of asbestos exposure (during his 30s), presented with a 4-week history of breathlessness and was found to have right-sided pleural effusion. Thoracic computed tomography (CT) showed mild right-sided pleural thickening. Pleural tap revealed exudative fluid, with a pH of 7.4, and unremarkable cytology and microbiology analyses. The patient was treated for pneumonia and para-pneumonic effusion and discharged home. He came back 5 weeks later with worsening of symptoms and re-accumulation of pleural fluid. Repeated thorax CT showed extensive right-sided pleural lobular thickening. Pleural tap again yielded an exudative fluid, with a pH of 7.37. Cytology and microbiology did not reveal any positive signs for malignancy or infection. This time the pleural fluid appeared gelatinous in consistency. Pleural biopsy showed atypical epithelioid mesothelial cells arranged in trabeculae, with a tubulo-papillary configuration. Also, immunohistochemistry panel showed tumor cells expressed calretinin, EMA, WT1, and D2-40, with negative TTF1, CEA, and BerEp4. Final diagnosis was epithelioid mesothelioma. CONCLUSIONS This report has shown that a gelatinous pleural effusion can be associated with malignant and inflammatory pleural diseases. In this case, imaging and pleural biopsy with histopathology confirmed a diagnosis of pleural mesothelioma.

A dataset of COVID-19 x-ray chest images.

The distinction between normal chest x-ray (CXR) images and abnormal ones containing features of disease (e.g., opacities, consolidation, etc.) is important for accurate medical diagnosis. CXR images contain valuable information concerning the physiological and pathological state of the lungs and airways. In addition, they provide information about the heart, chest bones, and some arteries (e.g., Aorta and pulmonary arteries). Deep learning artificial intelligence has taken great strides in the development of sophisticated medical models in a wide range of applications. More specifically, it has been shown to provide highly accurate diagnosis and detection tools. The dataset presented in this article contains the chest x-ray images from the examination of confirmed COVID-19 subjects, who were admitted for a multiday stay at a local hospital in northern Jordan. To provide a diverse dataset, only one CXR image per subject was included in the data. The dataset can be used for the development of automated methods that detect COVID-19 from CXR images (COVID-19 vs. normal) and distinguish pneumonia caused by COVID-19 from other pulmonary diseases. ©202x The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Detection of developmental dysplasia of the hip in X-ray images using deep transfer learning.

BACKGROUND: Developmental dysplasia of the hip (DDH) is a relatively common disorder in newborns, with a reported prevalence of 1-5 per 1000 births. It can lead to developmental abnormalities in terms of mechanical difficulties and a displacement of the joint (i.e., subluxation or dysplasia). An early diagnosis in the first few months from birth can drastically improve healing, render surgical intervention unnecessary and reduce bracing time. A pelvic X-ray inspection represents the gold standard for DDH diagnosis. Recent advances in deep learning artificial intelligence have enabled the use of many image-based medical decision-making applications. The present study employs deep transfer learning in detecting DDH in pelvic X-ray images without the need for explicit measurements. METHODS: Pelvic anteroposterior X-ray images from 354 subjects (120 DDH and 234 normal) were collected locally at two hospitals in northern Jordan. A system that accepts these images as input and classifies them as DDH or normal was developed using thirteen deep transfer learning models. Various performance metrics were evaluated in addition to the overfitting/underfitting behavior and the training times. RESULTS: The highest mean DDH detection accuracy was 96.3% achieved using the DarkNet53 model, although other models achieved comparable results. A common theme across all the models was the extremely high sensitivity (i.e., recall) value at the expense of specificity. The F1 score, precision, recall and specificity for DarkNet53 were 95%, 90.6%, 100% and 94.3%, respectively. CONCLUSIONS: Our automated method appears to be a highly accurate DDH screening and diagnosis method. Moreover, the performance evaluation shows that it is possible to further improve the system by expanding the dataset to include more X-ray images.

Cancer pain management program: Patients' experiences-A qualitative study.

BACKGROUND: Cancer patients frequently experience unrelieved pain as a significant symptom. However, several studies have found that cancer-related pain is frequently undertreated. PURPOSE: This study aimed to understand the pain experiences of cancer patients who were newly engaged in a multidisciplinary pain management program (PMP) at King Hussein Cancer Centre and still receiving cancer treatments and cancer pain management. METHODS: A qualitative study design and semi-structured interviews were used to obtain data from 21 cancer patients who were purposefully selected. All patients had advanced cancer, including skeleton metastases. All female participants had breast cancer, and all male participants had prostate cancer. RESULTS: It was found that the patient-healthcare professional relationship and satisfaction with services emerged as two themes in healthcare professionals' pain management. CONCLUSION: The results from this study can offer a new understanding of the knowledge related to satisfaction of patients with cancer in terms of the quality of pain management. Additional qualitative studies are required to replicate the findings in populations from different backgrounds, ethnicities, and cultures experiencing cancer pain.

A 5-Year-Old Palestinian Bedouin Girl with Repeated Self-Induced Injuries to the Digits, a Diagnosis of Congenital Insensitivity to Pain, and Anhidrosis.

BACKGROUND Congenital insensitivity to pain with anhidrosis (CIPA), also referred to as hereditary sensory and autonomic neuropathy type IV, is a rare autosomal recessive disease caused by mutations in the NTRK1 gene. The inability to feel pain and temperature often leads to repeated severe and unintentional self-inflicted injuries; these can result in severe complications, as patients heal slowly from skin and bone injuries. This case report describes a 5-year-old Palestinian girl with self-inflicted injury to the digits, a dislocated distal inter-phalangeal joint of the left big toe, and a diagnosis of CIPA. CASE REPORT A 5-year-old girl, a daughter of related Palestinian Bedouin parents, presented with a chronic unhealed wound over the planter surface of the left foot. Painless repetitive minor traumata over the same area badly affected wound healing and this led to wound dehiscence and dislocation of the distal inter-phalangeal joint of the left big toe. Surgical fixation of the dislocated joint along with intravenous antibiotics and close follow-up resulted in eventual improvement and near complete wound healing despite the obviously slow healing process. The girl also displayed evidence of unintentional self-inflicted injury, which within the overall clinical context warranted a clinical suspicion of CIPA. This was confirmed by genetic testing for the presence of a homozygous frameshift mutation in the NTRK1 gene (c.1842_1843insT; p.Pro615Serfs*12). CONCLUSIONS This case report shows that a physician should have a low threshold of suspicion to investigate for CIPA when managing children with multiple unintentional self-inflicted injuries, anhidrosis, and pain insensitivity, mainly through genetic testing to detect mutations in the NTRK1 gene.

Detection of COVID-19 from Chest X-ray Images Using Deep Convolutional Neural Networks.

The COVID-19 global pandemic has wreaked havoc on every aspect of our lives. More specifically, healthcare systems were greatly stretched to their limits and beyond. Advances in artificial intelligence have enabled the implementation of sophisticated applications that can meet clinical accuracy requirements. In this study, customized and pre-trained deep learning models based on convolutional neural networks were used to detect pneumonia caused by COVID-19 respiratory complications. Chest X-ray images from 368 confirmed COVID-19 patients were collected locally. In addition, data from three publicly available datasets were used. The performance was evaluated in four ways. First, the public dataset was used for training and testing. Second, data from the local and public sources were combined and used to train and test the models. Third, the public dataset was used to train the model and the local data were used for testing only. This approach adds greater credibility to the detection models and tests their ability to generalize to new data without overfitting the model to specific samples. Fourth, the combined data were used for training and the local dataset was used for testing. The results show a high detection accuracy of 98.7% with the combined dataset, and most models handled new data with an insignificant drop in accuracy.

Determinants of the willingness of the general population to get vaccinated against COVID-19 in a developing country.

PURPOSE: Vaccination is a cost-efficient intervention to slow the spread of the coronavirus disease 2019 (COVID-19) pandemic. This study aims to assess the population's willingness to take the COVID-19 vaccine in Jordan and investigate potential determinants of their acceptance. MATERIALS AND METHODS: This study used an online survey distributed in November 2020, before introducing the vaccine, with items investigating socio-demographic characteristics, seasonal flu vaccination history, COVID-19 vaccine acceptance once available, and factors affecting their decision-making. Also, "COVID-19 risk perception" and beliefs toward COVID-19 vaccine benefits and barriers were assessed. RESULTS: A total of 2,208 participants completed the survey with a participation rate of 13.1%. The mean±standard deviation age was 33.2±13.5, and 55.7% were females. Study participants were almost equally distributed between willingness, unwillingness, and indecision to take the COVID-19 vaccine (30.4%, 36.4%, and 31.5%, respectively). Younger adults, males, and those who were not married, do not have children, have a bachelor or higher education, employees or being students, healthcare workers, and those who reported receiving flu vaccine had higher rates of COVID-19 vaccine acceptance compared to their counterparts (p<0.001 for each category). COVID-19 risk perception, and perceived vaccine benefits, and barriers were significant predictors of intention. Among those undecided or unwilling to take the COVID-19 vaccine, its safety and side effects were the most common concerns. CONCLUSION: The low rate of COVID-19 vaccine acceptance in a developing country is alarming, and a significant proportion are indecisive. Interventions to elevate vaccine acceptance by addressing its safety and efficacy and targeting vulnerable groups are recommended.

Viral Clearance Course of COVID-19 Outbreaks.

BACKGROUND: Coronavirus disease 2019 (COVID-19) viral course and behavior remain unpredictable. This study describes incubation time and viral clearance of COVID-19 hospitalized cases in Northern Jordan. METHODS: All COVID-19 confirmed cases hospitalized from March 15 to June 09, 2020, were included. Nasopharyngeal swabs were collected, and COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) was performed every two days in all cases. The viral cure was defined when two negative RT-PCR tests were obtained ≥ 24 hours apart. Viral clearance time (VCT) reflects the time from the first positive nasopharyngeal swab to the first of two consecutive negative tests. RESULTS: In this cohort, a total of 157 patients were included. Most cases resulted from two major outbreaks. The median incubation period was 6 days (IQR, 3-10) and ranged from 1 to 17 days. The median VCT was 13 days (IQR, 7-2) and ranged from 1 to 40 days. Symptomatic presentation and abnormal chest radiograph were predictors for a prolonged VCT (p=0.015 and p=0.014, respectively). The median time of resolution of symptoms was 7 days (IQR, 3-10 days). Most symptomatic cases (91.7%) remained RT-PCR positive for up to 20 days after symptoms resolution, with a median of 13.5 days. VCT significantly correlated with the incubation period (p=0.013). CONCLUSION: Viral cure lagged for as long as 20 days after resolution of symptoms. Continuing with social-distancing, frequent hand hygiene, and wearing facial mask remains essential and is recommended even after clinical resolution of symptoms.

A dataset of lung sounds recorded from the chest wall using an electronic stethoscope.

The advancement of stethoscope technology has enabled high quality recording of patient sounds. We used an electronic stethoscope to record lung sounds from healthy and unhealthy subjects. The dataset includes sounds from seven ailments (i.e., asthma, heart failure, pneumonia, bronchitis, pleural effusion, lung fibrosis, and chronic obstructive pulmonary disease (COPD)) as well as normal breathing sounds. The dataset presented in this article contains the audio recordings from the examination of the chest wall at various vantage points. The stethoscope placement on the subject was determined by the specialist physician performing the diagnosis. Each recording was replicated three times corresponding to various frequency filters that emphasize certain bodily sounds. The dataset can be used for the development of automated methods that detect pulmonary diseases from lung sounds or identify the correct type of lung sound. The same methods can also be applied to the study of heart sounds.

COVID-19 outbreak in Jordan: Epidemiological features, clinical characteristics, and laboratory findings.

BACKGROUND: In March 2020, an outbreak of coronavirus 19 (COVID-19) was detected in the North of Jordan. This retrospective study is the first from Jordan to report the epidemiologic, clinical, laboratory, and radiologic characteristics of COVID-19 infected patients. METHODS: All patients with laboratory-confirmed COVID-19 infection by RT-PCR in the North of Jordan admitted between March 15 and April 2, 2020 were included. The clinical features, radiological, and laboratory findings were reviewed. RESULTS: Of 81 patients affected, 79 (97.5%) shared a common exposure to four recent travelers from endemic areas. The mean age was 40 years. Although about half (44 [54.3%]) were females, symptomatic patients were mostly females (75%). The most common presenting symptoms were nasal congestion, sore throat and dry cough. Less than one-third (31%) had chronic diseases. Although 84% of patients reported receiving Bacille Calmette-Guérin (BCG) vaccination, more asymptomatic patients had BCG than symptomatic (p = 0.017). Almost all patients (97.5%) had an elevated D-dimer level. Erythrocyte sedimentation rate (ESR) and c-reactive protein were elevated in 50% and 42.7% of patients, respectively. High ESR found to be the predictor of abnormal chest radiograph observed in 13 (16%) patients with OR of 14.26 (95% CI 1.37-147.97, p = 0.026). CONCLUSIONS: An outbreak of COVID-19 infection in northern Jordan affected more females and relatively young individuals and caused mainly mild illnesses. The strict outbreak response measures applied at early stages probably contributed to the lenient nature of this outbreak, but the contribution of other factors to such variability in COVID-19 presentation is yet to be explained.

Screening for obstructive sleep apnea among patients undergoing coronary catheterization in Jordan.

Aims: This study aimed to utilize a validated sleep questionnaire as a screening tool for symptoms and risk of obstructive sleep apnea in patients undergoing coronary catheterization in Jordan. Materials and methods: A cross-sectional design was used to screen adult patients undergoing coronary catheterization for obstructive sleep apnea (OSA). The Berlin sleep questionnaire was used to record nocturnal and daytime symptoms of OSA and to stratify patients into "low-risk" or "high-risk" for OSA. Coronary artery disease was defined as ≥50% intraluminal stenosis in at least one coronary vessel. Results: A total of 398 patients were studied, mean age was 58.7 years (SD=10.70), ranging from 21-92 years, and 68.6% were males. Based on the Berlin sleep questionnaire's definition, 176 patients (44.2%) were at high-risk for obstructive sleep apnea. Snoring was reported by 61%; loud in 42.1%, and frequent in 62%. Daytime sleepiness was reported by 36%, and 18.9% had fallen asleep while driving. Witnessed apnea during sleep was less reported (7.8%). Prevalence of symptoms and risk of OSA were not different between patients with and without coronary artery disease, P>0.05. In addition, logistic regression indicated that there was no significant association between risk of OSA and coronary artery disease, adjusted (odds ratio=0.93, 95% Confidence Interval=0.60-1.44, P=0.752). Conclusions: Symptoms and risk of obstructive sleep apnea were common among adult Jordanians undergoing coronary catheterization. There was no association between risk of obstructive sleep apnea and coronary artery disease. Larger studies are needed to assess the role of screening for obstructive sleep apnea in this patient population.

Prevalence of undiagnosed COPD in male patients with coronary artery disease: a cross-sectional study in Jordan.

Purpose: COPD and coronary artery disease (CAD) are common chronic diseases with shared risk factors. COPD continues to be largely underdiagnosed and undertreated. We aimed to describe the prevalence and predictors of undiagnosed COPD in Jordanian men with CAD. Patients and methods: In a cross-sectional study conducted at a referral center in Jordan, male patients who underwent coronary angiography for suspected CAD and reported ≥10 pack-year of cigarette smoking were recruited. Pre- and post-bronchodilator spirometry was undertaken for all participants, and COPD was defined as post-bronchodilator FEV1/FVC <70%. The finding of ≥50% coronary luminal narrowing confirmed the presence of CAD. Results: Spirometry was undertaken for 376 men with mean age of 56.02±10.55 years, and 72.6% were active cigarettes smokers with a mean pack-year of 55.89±34.25. A CAD diagnosis was confirmed in 300 (79.8%) men. Spirometric criteria for COPD were met in 76 (15.7%) patients, of whom 91.5% were not previously diagnosed. COPD-related symptoms were common: chronic cough (44.4%), dyspnea (66.2%), and wheezes (27.9%). COPD was more common in patients with (18.0%) compared to patients without (6.6%) CAD (P=0.014). Multivariate logistic regression showed that the risk of COPD was higher in patients with CAD (OR 3.16, 95% CI, 1.10-9.09, P=0.033) and in those with chronic bronchitis (OR 13.07, 95% CI, 6.69-25.52, P<0.001). Conclusion: There was a high prevalence of COPD among male patients with CAD and most were underdiagnosed despite having respiratory symptoms. Male smokers with CAD and respiratory symptoms should be evaluated for airflow limitation and the presence of COPD.

The association of snoring and risk of obstructive sleep apnea with poor academic performance among university students.

STUDY OBJECTIVES: Subjects with obstructive sleep apnea (OSA) have neurocognitive dysfunction. The aim of this study was to estimate the prevalence of symptoms and risk of OSA among university students and the association with academic performance. METHODS: A cross-sectional study was conducted at Jordan University of Science and Technology. Students from faculties of engineering, medicine, nursing, pharmacy, and dentistry were asked to participate in this study. The Berlin Sleep Questionnaire was used to report symptoms and risk of OSA. Below average cumulative scores were considered poor academic performance. RESULTS: A total of 777 students (51% female; mean age, 20 years) completed the study questionnaire. According to the study definition, 42 students (5.4%) had high risk for OSA. Snoring was reported by 11% and daytime sleepiness and fatigue by 30%. Compared to female students, male students had more snoring (14.6 vs. 7.6%, p = 0.002) and higher risk for OSA (6.5 vs. 1.6%, p = 0.001). Both self-reported snoring and being at high risk for OSA were associated with poor academic performance (27.9 vs. 11.6% and 23.1 vs. 9.2%, respectively; p < 0.02). After adjusting for confounding factors, the odds ratio of having poor academic performance in students at high risk for OSA was 2.4 (CI 1.11-5.2, p = 0.027). CONCLUSIONS: Snoring and OSA were uncommon among university students. However, both were more common among male students and were associated with poor academic performance.