Literature DB >> 31509449

The Clinical Utility of Chest Radiography for Identifying Pneumonia: Accounting for Diagnostic Uncertainty in Radiology Reports.

Alexander Makhnevich1,2, Liron Sinvani1,2, Stuart L Cohen2,3, Kenneth H Feldhamer1, Meng Zhang2,4, Martin L Lesser4, Thomas G McGinn1,2.   

Abstract

OBJECTIVE. Currently, chest radiography is the first-line imaging test for identifying pneumonia; chest CT is considered the reference standard. The purpose of this study was to calculate the statistical measures of performance of chest radiography for identifying pneumonia when taking into account uncertain results of both chest radiography and CT examinations. MATERIALS AND METHODS. Statistical measures of performance of chest radiography, using CT as the reference standard, were calculated with 95% CIs by varying uncertain radiology report impressions of both chest radiography and CT to all negative or all positive. The resulting scenarios were as follows: scenario 1, uncertain chest radiography and CT impressions are considered positive for pneumonia; scenario 2, uncertain chest radiography impressions are positive but uncertain CT impressions are negative; scenario 3, uncertain chest radiography impressions are negative and uncertain CT impressions are positive; scenario 4, uncertain chest radiography and CT impressions are negative; and scenario 5, uncertain chest radiography and CT impressions are excluded. RESULTS. A retrospective analysis of 2411 patient visits revealed the prevalence of uncertain radiology report impressions to be 31.8% for chest radiography and 21.7% for CT. Scenario 1 yielded the following performance values: sensitivity, 51.9%; specificity, 71.3%; PPV, 59.4%; and NPV, 64.5%. Scenario 2 produced the following performance values: sensitivity, 59.6%; specificity, 67.1%; PPV, 59.6%; and NPV, 67.1%. Scenario 3 showed the following performance values: sensitivity, 13.4%; specificity, 97.7%; PPV, 82.6%; and NPV, 58.1%. Scenario 4 yielded the following performance values: sensitivity, 19.6%; specificity, 96.4%; PPV, 81.6%; and NPV, 59.5%. Scenario 5 produced the following performance values: sensitivity, 32.7%; specificity, 96.8%; PPV, 89.2%; and NPV, 63.8%. CONCLUSION. Uncertain chest radiography results for the evaluation of pneumonia are prevalent. A chest radiography impression using the strongest language in support of a pneumonia diagnosis is useful to rule in pneumonia radiographically, but a negative result performs poorly at ruling out disease.

Entities:  

Keywords:  chest radiography; performance measures; pneumonia; uncertain or intermediate results

Mesh:

Year:  2019        PMID: 31509449     DOI: 10.2214/AJR.19.21521

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  10 in total

1.  Natural Language Processing and Machine Learning to Enable Clinical Decision Support for Treatment of Pediatric Pneumonia.

Authors:  Joshua C Smith; Ashley Spann; Allison B McCoy; Jakobi A Johnson; Donald H Arnold; Derek J Williams; Asli O Weitkamp
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  Blue Lungs in Covid-19 Patients: A Step beyond the Diagnosis of Pulmonary Thromboembolism using MDCT with Iodine Mapping.

Authors:  Virginia Pérez Dueñas; María Allona Krauel; Emilio Agrela Rojas; Maria Teresa Ramírez Prieto; Laura Díez Izquierdo; Ulpiano López de la Guardia; Isabel Torres Sánchez
Journal:  Arch Bronconeumol       Date:  2020-08-28       Impact factor: 4.872

3.  [Blue Lungs in Covid-19 Patients: A Step beyond the Diagnosis of Pulmonary Thromboembolism using MDCT with Iodine Mapping].

Authors:  Virginia Pérez Dueñas; María Allona Krauel; Emilio Agrela Rojas; Maria Teresa Ramírez Prieto; Laura Díez Izquierdo; Ulpiano López de la Guardia; Isabel Torres Sánchez
Journal:  Arch Bronconeumol       Date:  2020-08-28       Impact factor: 4.872

4.  Lung ultrasound patterns in paediatric pneumonia in Mozambique and Pakistan.

Authors:  Amy Sarah Ginsburg; Pio Vitorino; Zunera Qasim; Jennifer L Lenahan; Jun Hwang; Alessandro Lamorte; Marta Valente; Benazir Balouch; Carmen Muñoz Almagro; M Imran Nisar; Susanne May; Fyezah Jehan; Quique Bassat; Giovanni Volpicelli
Journal:  ERJ Open Res       Date:  2021-02-01

5.  Giant compressive emphysema: a rare complication of COVID-19.

Authors:  Julien Rakotoson; Johary Andriamizaka Andriamamonjisoa; Mandimbisoa Noely Oberlin Andriamihary; Solohery Jean Noël Ratsimbazafy; Roger Dominique Randrianarimalala; Rivo Andry Rakotoarivelo; Stéphane Ralandison
Journal:  BMC Infect Dis       Date:  2021-12-30       Impact factor: 3.090

6.  High-resolution chest computed tomography findings of coronavirus disease 2019 (COVID-19) - A retrospective single center study of 152 patients.

Authors:  Navdeep Kaur; Soumya S Sahoo; Harvinder S Chhabra; Amandeep Kaur; Navdeep Singh; Shivane Garg
Journal:  J Family Med Prim Care       Date:  2021-11-05

7.  An adaptive and altruistic PSO-based deep feature selection method for Pneumonia detection from Chest X-rays.

Authors:  Rishav Pramanik; Sourodip Sarkar; Ram Sarkar
Journal:  Appl Soft Comput       Date:  2022-08-10       Impact factor: 8.263

8.  Impact of rapid molecular testing on diagnosis, treatment and management of community-acquired pneumonia in Norway: a pragmatic randomised controlled trial (CAPNOR).

Authors:  Sondre Serigstad; Christian Ritz; Daniel Faurholt-Jepsen; Dagfinn Markussen; Marit H Ebbesen; Øyvind Kommedal; Rune O Bjørneklett; Lars Heggelund; Tristan W Clark; Cornelis H van Werkhoven; Siri T Knoop; Elling Ulvestad; Harleen M S Grewal
Journal:  Trials       Date:  2022-08-01       Impact factor: 2.728

9.  Evaluating the Usefulness of Lab-Based Test for the Diagnosis of Pneumonia in Children.

Authors:  Fariba Tarhani; Alireza Nezami; Ghobad Heidari
Journal:  Int J Gen Med       Date:  2020-05-27

Review 10.  Diagnostic value and key features of computed tomography in Coronavirus Disease 2019.

Authors:  Bingjie Li; Xin Li; Yaxuan Wang; Yikai Han; Yidi Wang; Chen Wang; Guorui Zhang; Jianjun Jin; Hongxia Jia; Feifei Fan; Wang Ma; Hong Liu; Yue Zhou
Journal:  Emerg Microbes Infect       Date:  2020-12       Impact factor: 7.163

  10 in total

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