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Diagnostic presentations of different pleural effusion patients to a tertiary care centre

A descriptive cross-sectional study

Bibliographic Data

ID15799053
AuthorsSasmita Meher (0009-0002-0666-533X, corresponding author), Bhanjan Kumar Meher, Sujeet Kumar Brahma, Pravin G Dhone, Neeta Rai (Vishwakarma University)
Year2022
Pages5315-5323
Publication date2022-07-20
Open AccessYes
TypeARTICLE
VenueInternational Journal of Health Sciences (JOURNAL)
Journal identifiersISSN: 2550-696X • E-ISSN: 2550-6978
PublisherUniversidad Tecnica de Manabi (PUBLISHER • EC)
DOI10.53730/ijhs.v6ns6.10832
OpenAlexW4290975165
LanguageEN

BACKGROUND-Pleural effusion is defined as collection of fluid between the two pleural covering. OBJECTIVE-To evaluate the different etiologies of pleural effusion according to laboratory report. METHODOLOGY-Data was collected in a nonprobability convenience technique with descriptive cross- sectional study in indoor patient of pulmonary medicine department of Balangir Bhima Bhoi medical college from 2017 nov to 2020 nov,202 patients included in this technique.Diagnosis was confirmed by chest -x-Ray, and USG Chest in some cases, .Pleural fluid is aspirated from all and analysed with necessary investigation carried out ,like pleural fluid cytology, Biochemical and culture .computed tomography ,echocardiography and connective tissue profile for evaluating the underlying cause of pleural effusion. RESULT- Out of 202 patients 145 (73%) were male and 57(26)% were female Mean age was 44.8years with 19,832 SD .Among patients of pleural effusion most common cause was tuberculosis (65.3%). followed by Para pneumonic effusion/empyema (11.4%), malignancy both metastatic and primary accounted for (15%), heart failure also showed its presence in 5% of cases. Connective tissue disorder was found to be the cause in only one case (0.5%). In one case (0.5%) pleural effusion remained undiagnosed

Effusion · Empyema · Etiology · Malignancy · Parapneumonic effusion · Pathology · Pleural effusion · Pleural fluid · Radiology · Tuberculosis · COVID-19 diagnosis using AI · Medicine · Pleural and Pulmonary Diseases · Ultrasound in Clinical Applications · Internal Medicine · Surgery

Highly citedNo

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