scholarly journals The Prevalence of Disseminated Tuberculosis Among Tuberculosis Patients in Uganda

2021 ◽  
Author(s):  
Eddy Kyagulanyi ◽  
Joy Mirembe ◽  
Brandy Nantaayi ◽  
Sonita Nalukenge ◽  
David Mukasa ◽  
...  
Keyword(s):  
Retrospective Chart Review ◽  
Treatment Center ◽  
Cure Rate ◽  
Disseminated Tuberculosis ◽  
Tb Treatment ◽  
X Ray Imaging ◽  
Mulago National Referral Hospital ◽  
National Tuberculosis ◽  
Chest X Ray ◽  
Epidemiological Characteristics

Abstract Background: The incidence of disseminated tuberculosis (DTB) is increasing worldwide yet its epidemiological characteristics in Uganda are not known. The purpose of this study was to determine the prevalence, associated factors, and treatment outcomes of DTB among patients at a national tuberculosis (TB) treatment center in Uganda.Methodology: The study took place at the TB unit of Mulago National Referral Hospital in Kampala, Uganda. We conducted a retrospective chart review of TB patients who were enrolled in care between January 2015 and December 2019. Eligible charts were for patients with pulmonary bacteriologically confirmed TB enrolled into care in the period under study. DTB was defined as TB at two or more non-contiguous sites.Results: Overall, 400 patient charts were eligible, of whom 240(60.0%) were aged 15 – 34 years and 205 (51.3%) were female. The prevalence of DTB was 8.5% (34/400) (95% CI: 6.0% – 11.7%). Patients with DTB were more likely to be casual laborers (44.1% vs 21.3%, p = 0.023), from Bantu ethnic group (67.7% vs. 40.5%, p = 0.0021), and had at least one comorbidity (82.4% vs 37.2%, p <0.001), of which HIV was the most frequent. Further, patients with DTB (n = 20) were more likely to have empyema (15% vs 2.6%, p = 028) but less likely to have bronchopneumonic opacification (0.0% vs 15.3%, p = 0.043) on chest x-ray imaging. Patients with DTB had higher mortality (26.5% vs 6.37%) and a lower cure rate (41.2% vs 64.8%), p = 0.002.Conclusion: Our findings highlight the need for early detection of TB before dissemination and greater use of TB preventive therapies in HIV-infected individuals to counter the observed high mortality of DTB.

scholarly journals 1692. Retrospective Review on the Safety and Efficacy of Nitrofurantoin for the Treatment of Cystitis in the Veteran Population With or Without Renal Insufficiency

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S829-S830
Author(s):  
Elwyn W Welch ◽  
Shaila Sheth ◽  
Chester Ashong ◽  
Caroline Pham
Keyword(s):  
Renal Function ◽  
Renal Dysfunction ◽  
Clinical Cure ◽  
Clinical Cure Rate ◽  
Retrospective Chart Review ◽  
Outpatient Setting ◽  
Secondary Outcome ◽  
Cure Rate ◽  
Acute Cystitis ◽  
Significant Difference

Abstract Background Nitrofurantoin has been used to treat cystitis in women; however, data supporting its use in men is lacking. In addition, recent retrospective studies have challenged the manufacturer’s recommendation to avoid nitrofurantoin with creatinine clearances (CrCl) less than 60 mL/min. The purpose of this study is to compare the efficacy and safety of nitrofurantoin for the treatment of acute cystitis in male and female veterans with variable degrees of renal dysfunction. Methods A retrospective chart review was conducted in adult patients who received nitrofurantoin for acute cystitis in the outpatient setting between May 1, 2018 and May 1, 2019. The primary outcomes were rates of clinical cure as compared between males and females, and across various renal function groups (CrCl greater than 60 mL/min, 30 to 60 mL/min, and less than 30 mL/min) following treatment with nitrofurantoin. The secondary outcome was adverse event rates. Results A total of 446 patients were included with 278 females and 168 males. Overall clinical cure rate was 86.5% (n=386). Clinical cure rate did not vary between genders (p=0.0851) or CrCl ranges (p=1.0) as shown in the tables. Benign prostatic hyperplasia (BPH) was associated with decreased odds of clinical cure (OR 0.50 [95% CI 0.26-0.97], p=0.0404) in addition to cirrhosis (OR 0.22 [95% CI 0.06-0.91], p=0.0357). Adverse events occurred in 2% of patients and did not vary based on gender or renal function. RATES OF CLINICAL CURE Conclusion There was no statistically significant difference in clinical cure with nitrofurantoin between genders and various renal impairments. However, history of BPH and cirrhosis were associated with decreased efficacy. Subgroup analysis also revealed lower efficacy in males with CrCl greater than 60 mL/min versus females with similar renal function. This study adds to the growing body of literature suggesting that renal dysfunction with CrCl of 30 to 60 mL/min may not carry the risk of treatment failure and adverse effects previously associated with nitrofurantoin, but large randomized trials are needed to confirm these results. Disclosures All Authors: No reported disclosures

scholarly journals The Impact of Geography in Hepatocellular Carcinoma: A Retrospective Population Based Study

2021 ◽  
Vol 28 (1) ◽  
pp. 396-404
Author(s):  
Irene S. Yu ◽  
Shiru L. Liu ◽  
Valeriya Zaborska ◽  
Tyler Raycraft ◽  
Sharlene Gill ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Retrospective Chart Review ◽  
Population Based ◽  
Tumor Board ◽  
Treatment Center ◽  
Population Based Study ◽  
Therapeutic Modalities ◽  
Quaternary Center ◽  
Statistics Canada ◽  
The Impact

Background: The treatment of hepatocellular carcinoma (HCC) includes different therapeutic modalities and multidisciplinary tumor board reviews. The impact of geography and treatment center type (quaternary vs. non-quaternary) on access to care is unclear. Methods: A retrospective chart review was performed on HCC patients who received sorafenib in British Columbia from 2008 to 2016. Patients were grouped by Statistics Canada population center (PC) size criteria: large PC (LPC), medium PC (MPC), and small PC (SPC). Access to specialists, receipt of liver-directed therapies, and survival outcomes were compared between the groups. Results: Of 286 patients, the geographical distribution was: LPC: 75%; MPC: 16%; and SPC: 9%. A higher proportion of Asians (51% vs. 9% vs. 4%; p < 0.001), Child–Pugh A (94% vs. 83% vs. 80%; p = 0.022), and hepatitis B (37% vs. 15% vs. 4%; p < 0.001) was observed in LPC vs. MPC vs. SPC, respectively. LPC patients were more likely referred to a hepatologist (62% vs. 48% vs. 40%; p = 0.031) and undergo transarterial chemoembolization (TACE) (43% vs. 24% vs. 24%; p = 0.018). Sixty percent were treated at a quaternary center, and the median overall survival (OS) was higher for patients treated at a quaternary vs. non-quaternary center (28.0 vs. 14.6 months, respectively; p < 0.001) but similar when compared by PC size. Treatment at a quaternary center predicted an improved survival on multivariate analysis (hazard ratio (HR): 0.652; 95% confidence interval (CI): 0.503–0.844; p = 0.001). Conclusions: Geography did not appear to impact OS but patients from LPC were more likely to be referred to hepatology and undergo TACE. Treatment at a quaternary center was associated with an improved survival.

scholarly journals COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader

2021 ◽  
Vol 29 (1) ◽  
pp. 19-36
Author(s):  
Çağín Polat ◽  
Onur Karaman ◽  
Ceren Karaman ◽  
Güney Korkmaz ◽  
Mehmet Can Balcı ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Critical Time ◽  
Image Data ◽  
Mapping Method ◽  
Fine Tuning ◽  
Learning Stage ◽  
X Ray ◽  
Testing Dataset ◽  
X Ray Imaging ◽  
Chest X Ray

BACKGROUND: Chest X-ray imaging has been proved as a powerful diagnostic method to detect and diagnose COVID-19 cases due to its easy accessibility, lower cost and rapid imaging time. OBJECTIVE: This study aims to improve efficacy of screening COVID-19 infected patients using chest X-ray images with the help of a developed deep convolutional neural network model (CNN) entitled nCoV-NET. METHODS: To train and to evaluate the performance of the developed model, three datasets were collected from resources of “ChestX-ray14”, “COVID-19 image data collection”, and “Chest X-ray collection from Indiana University,” respectively. Overall, 299 COVID-19 pneumonia cases and 1,522 non-COVID 19 cases are involved in this study. To overcome the probable bias due to the unbalanced cases in two classes of the datasets, ResNet, DenseNet, and VGG architectures were re-trained in the fine-tuning stage of the process to distinguish COVID-19 classes using a transfer learning method. Lastly, the optimized final nCoV-NET model was applied to the testing dataset to verify the performance of the proposed model. RESULTS: Although the performance parameters of all re-trained architectures were determined close to each other, the final nCOV-NET model optimized by using DenseNet-161 architecture in the transfer learning stage exhibits the highest performance for classification of COVID-19 cases with the accuracy of 97.1 %. The Activation Mapping method was used to create activation maps that highlights the crucial areas of the radiograph to improve causality and intelligibility. CONCLUSION: This study demonstrated that the proposed CNN model called nCoV-NET can be utilized for reliably detecting COVID-19 cases using chest X-ray images to accelerate the triaging and save critical time for disease control as well as assisting the radiologist to validate their initial diagnosis.

scholarly journals Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging

2021 ◽  
Vol 11 (2) ◽  
pp. 411-424 ◽  
Author(s):  
José Daniel López-Cabrera ◽  
Rubén Orozco-Morales ◽  
Jorge Armando Portal-Diaz ◽  
Orlando Lovelle-Enríquez ◽  
Marlén Pérez-Díaz
Keyword(s):  
Artificial Intelligence ◽  
X Ray ◽  
X Ray Imaging ◽  
Chest X Ray

scholarly journals Artificial Intelligence Framework for Efficient Detection and Classification of Pneumonia Using Chest Radiography Images

2021 ◽  
Author(s):  
Ali Mohammad Alqudah ◽  
Shoroq Qazan ◽  
Ihssan S. Masad
Keyword(s):  
Artificial Intelligence ◽  
Input Image ◽  
Image Size ◽  
X Ray ◽  
Softmax Classifier ◽  
Non Invasive ◽  
Efficient Detection ◽  
X Ray Imaging ◽  
Chest X Ray

Abstract BackgroundChest diseases are serious health problems that threaten the lives of people. The early and accurate diagnosis of such diseases is very crucial in the success of their treatment and cure. Pneumonia is one of the most widely occurred chest diseases responsible for a high percentage of deaths especially among children. So, detection and classification of pneumonia using the non-invasive chest x-ray imaging would have a great advantage of reducing the mortality rates.ResultsThe results showed that the best input image size in this framework was 64 64 based on comparison between different sizes. Using CNN as a deep features extractor and utilizing the 10-fold methodology the propose artificial intelligence framework achieved an accuracy of 94% for SVM and 93.9% for KNN, a sensitivity of 93.33% for SVM and 93.19% for KNN and a specificity of 96.68% for SVM and 96.60% for KNN.ConclusionsIn this study, an artificial intelligence framework has been proposed for the detection and classification of pneumonia based on chest x-ray imaging with different sizes of input images. The proposed methodology used CNN for features extraction that were fed to two different types of classifiers, namely, SVM and KNN; in addition to the SoftMax classifier which is the default CNN classifier. The proposed CNN has been trained, validated, and tested using a large dataset of chest x-ray images contains in total 5852 images.

scholarly journals Respiratory symptoms and lung function in patients treated for pulmonary tuberculosis in Malawi: a prospective cohort study

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2021-217190
Author(s):  
Rebecca Nightingale ◽  
Beatrice Chinoko ◽  
Maia Lesosky ◽  
Sarah J Rylance ◽  
Bright Mnesa ◽  
...  
Keyword(s):  
Lung Function ◽  
Pulmonary Tuberculosis ◽  
Respiratory Symptoms ◽  
Treatment Completion ◽  
First Year ◽  
Tb Treatment ◽  
Effective Interventions ◽  
Hiv Coinfection ◽  
History Of ◽  
Chest X Ray

RationalePulmonary tuberculosis (PTB) can cause post-TB lung disease (PTLD) associated with respiratory symptoms, spirometric and radiological abnormalities. Understanding of the predictors and natural history of PTLD is limited.ObjectivesTo describe the symptoms and lung function of Malawian adults up to 3 years following PTB-treatment completion, and to determine the evolution of PTLD over this period.MethodsAdults successfully completing PTB treatment in Blantyre, Malawi were followed up for 3 years and assessed using questionnaires, post-bronchodilator spirometry, 6 min walk tests, chest X-ray and high-resolution CT. Predictors of lung function at 3 years were identified by mixed effects regression modelling.Measurement and main resultsWe recruited 405 participants of whom 301 completed 3 years follow-up (mean (SD) age 35 years (10.2); 66.6% males; 60.4% HIV-positive). At 3 years, 59/301 (19.6%) reported respiratory symptoms and 76/272 (27.9%) had abnormal spirometry. The proportions with low FVC fell from 57/285 (20.0%) at TB treatment completion to 33/272 (12.1%), while obstruction increased from and 41/285 (14.4%) to 43/272 (15.8%) at 3 years. Absolute FEV1 and FVC increased by mean 0.03 L and 0.1 L over this period, but FEV1 decline of more than 0.1 L was seen in 73/246 (29.7%). Higher spirometry values at 3 years were associated with higher body mass index and HIV coinfection at TB-treatment completion.ConclusionSpirometric measures improved over the 3 years following treatment, mostly in the first year. However, a third of PTB survivors experienced ongoing respiratory symptoms and abnormal spirometry (with accelerated FEV1 decline). Effective interventions are needed to improve the care of this group of patients.

scholarly journals Factors that influence the recovery of TB patients using Cox proportional hazard regression

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
ZURNILA MARLI KESUMA ◽  
HIZIR SOFYAN ◽  
LATIFAH RAHAYU ◽  
WARDATUL JANNAH
Keyword(s):  
Control Program ◽  
Proportional Hazard ◽  
Cure Rate ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
National Tuberculosis Control Program ◽  
Record Data ◽  
National Tuberculosis ◽  
The Government ◽  
Cox Proportional Hazard Regression

Tuberculosis (TB) is an infectious disease which is one of the biggest health problems in the world, including Indonesia. The government, through the National Tuberculosis Control program, has made various efforts to control tuberculosis. However, this problem was exacerbated by the dramatic increase in the incidence of tuberculosis. This study aimed to determine the Cox proportional hazard regression model and the factors that affect the cure rate of TB patients. We used medical record data for inpatient TB patients for the period July-December 2017 at dr. Zainoel Abidin Hospital. The results showed that with α = 0.1, the factors that influenced the recovery of TB patients were the type of cough, the symptoms of bloody cough and symptoms of sweating at night.  There were 33.93% of patients who did not work. This category included students, domestic helpers, and those who did not work until they suffered from tuberculosis and were treated at dr. Zainoel Abidin Hospital. The hazard ratio (failure ratio) showed that the tendency or cure rate for TB patients who did not experience cough symptoms was 70% greater than patients who experienced phlegm cough symptoms. The cure rate for TB patients who experienced coughing up blood symptoms was 53% greater than patients without these symptoms. The cure rate for TB patients who experienced  symptoms of sweating at night was 54% greater than patients who did not sweat at night.

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