scholarly journals Determining the Clinical Utility of an Absolute Procalcitonin Value for Predicting a Positive Culture Result

2017 ◽  
Vol 61 (5) ◽  
Author(s):  
Erica M. Caffarini ◽  
Joshua DeMott ◽  
Gourang Patel ◽  
Ishaq Lat
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Positive Culture ◽  
Threshold Value ◽  
Culture Result ◽  
Culture Positivity ◽  
Positive Culture Result ◽  
Tract Infections ◽  
The Impact

ABSTRACT Various procalcitonin ranges have been established to guide antimicrobial therapy; however, there are no data that establish whether the initial procalcitonin value can determine the likelihood of a positive culture result. This study aimed to establish if the initial procalcitonin value, on clinical presentation, has a positive predictive value for any positive culture result. This was a retrospective study of 813 medical intensive care unit patients. Data collected included patient demographics, procalcitonin assay results, sources of infection, culture results, and lengths of stay. Patients were excluded if they were immunocompromised. The primary outcome of this study was to determine a procalcitonin value that would predict any positive culture. Secondary outcomes included the sensitivity, specificity, positive predictive value, and negative predictive value for procalcitonin. After exclusions, a total of 519 patient charts were reviewed to determine the impact of the initial procalcitonin value on culture positivity. In our analyses, the receiver operating characteristic values were 0.62 for all cultures, 0.49 for pulmonary infections, 0.43 for urinary tract infections, and 0.78 for bacteremia. A procalcitonin value of 3.61 ng/ml was determined to be the threshold value for a positive blood culture result (prevalence, 4%). For bacteremia, the sensitivity of procalcitonin was 75%, the specificity was 72%, the positive predictive value was 20%, and the negative predictive value was 97%. Procalcitonin was a poor predictor of culture positivity. An initial procalcitonin value of less than 3.61 ng/ml may be useful in predicting whether bacteremia is absent. Procalcitonin should not be used as the only predictor for determining initiation of antibiotic therapy.

scholarly journals Investigating the impact of disease and health record duration on the eMERGE algorithm for rheumatoid arthritis

2020 ◽  
Vol 27 (4) ◽  
pp. 601-605
Author(s):  
Vanessa L Kronzer ◽  
Liwei Wang ◽  
Hongfang Liu ◽  
John M Davis ◽  
Jeffrey A Sparks ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Index Date ◽  
Model Performance ◽  
Area Under The Curve ◽  
Population Based ◽  
Health Record ◽  
The Impact

Abstract Objective The study sought to determine the dependence of the Electronic Medical Records and Genomics (eMERGE) rheumatoid arthritis (RA) algorithm on both RA and electronic health record (EHR) duration. Materials and Methods Using a population-based cohort from the Mayo Clinic Biobank, we identified 497 patients with at least 1 RA diagnosis code. RA case status was manually determined using validated criteria for RA. RA duration was defined as time from first RA code to the index date of biobank enrollment. To simulate EHR duration, various years of EHR lookback were applied, starting at the index date and going backward. Model performance was determined by sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC). Results The eMERGE algorithm performed well in this cohort, with overall sensitivity 53%, specificity 99%, positive predictive value 97%, negative predictive value 74%, and AUC 76%. Among patients with RA duration <2 years, sensitivity and AUC were only 9% and 54%, respectively, but increased to 71% and 85% among patients with RA duration >10 years. Longer EHR lookback also improved model performance up to a threshold of 10 years, in which sensitivity reached 52% and AUC 75%. However, optimal EHR lookback varied by RA duration; an EHR lookback of 3 years was best able to identify recently diagnosed RA cases. Conclusions eMERGE algorithm performance improves with longer RA duration as well as EHR duration up to 10 years, though shorter EHR lookback can improve identification of recently diagnosed RA cases.

scholarly journals Cut-off Values of Bacteriuria and Leukocyturia for the Diagnosis of Urinary Tract Infections in Pediatric Patients

2020 ◽  
Vol 27 (1) ◽  
Author(s):  
Muhamad Ramdani Ibnu Taufik ◽  
Dian Ariningrum ◽  
Yusuf Ari Mashuri
Keyword(s):  
Urinary Tract ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Likelihood Ratio ◽  
Urinary Tract Infections ◽  
Predictive Value ◽  
Pediatric Patients ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Tract Infections

The diagnosis of Urinary Tract Infection (UTI) in infants and children is often missed. There have been no studies ondiagnostic tests using automated urine analyzer in pediatric patients. This study aimed to determine the cut-off values ofbacteriuria and leukocyturia using the automated urine analyzer Sysmex UX-2000 to diagnose UTI with the gold standard ofautomated urine culture using VITEK 2 in pediatric patients at Dr. Moewardi Hospital, Surakarta. An observational analyticalstudy with the cross-sectional design was during August-October 2019 at the Clinical Pathology Laboratory and ClinicalMicrobiology Laboratory of Moewardi Hospital, Surakarta. Eighty-four patients sample were collected. This study'sdependent variable was the diagnosis of urinary tract infections in pediatric patients established with positive culture results(bacterial count of ≥ 105 CFU/mL urine). This study's independent variables were the number of urine bacteria (BACT) andthe number of urine leukocytes (WBC) from urinalysis using the Sysmex UX-2000 automated urine analyzer. A diagnostictest was used for data analysis. The best cut-off value for leukocyturia was 37 cells/μL with a 61.1% sensitivity, 63.6%specificity, a positive predictive value of 31.4%; a negative predictive value of 85.7; positive likelihood ratio of 1.64; negativelikelihood ratio of 0.595, and accuracy of 63%. The best cut-off for the number of bacteria was 143 cells/μL with a sensitivityof 66.7%; specificity of 71.2%, the positive predictive value of 38.7%, the negative predictive value of 88.7%; positivelikelihood ratio of 2.14; negative likelihood ratio of 0.432 and an accuracy of 70.2%. A cut-off of 37 cells/μL for leukocyturiaand 143 cells/μL for bacteriuria using an automated urine analyzer can be used for UTI screening in pediatric patients.

scholarly journals Added value of diffusion-weighted MRI in assessment of pleural lesions

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Youssriah Yahia Sabri ◽  
Ikram Hamed Mahmoud ◽  
Lamis Tarek El-Gendy ◽  
Mohamed Raafat Abd El-Mageed ◽  
Sally Fouad Tadros
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diagnostic Value ◽  
Added Value ◽  
Adc Value ◽  
Pleural Diseases ◽  
Conventional Mri ◽  
Malignant Lesions

Abstract Background There are many causes of pleural disease including variable benign and malignant etiologies. DWI is a non-enhanced functional MRI technique that allows qualitative and quantitative characterization of tissues based on their water molecules diffusivity. The aim of this study was to evaluate the diagnostic value of DWI-MRI in detection and characterization of pleural diseases and its capability in differentiating benign from malignant pleural lesions. Results Conventional MRI was able to discriminate benign from malignant lesions by using morphological features (contour and thickness) with sensitivity 89.29%, specificity 76%, positive predictive value 89%, negative predictive value 76.92%, and accuracy 85.37%. ADC value as a quantitative parameter of DWI found that ADC values of malignant pleural diseases were significantly lower than that of benign lesions (P < 0.001). Hence, we discovered that using ADC mean value of 1.68 × 10-3 mm2/s as a cutoff value can differentiate malignant from benign pleural diseases with sensitivity 89.3%, specificity 100%, positive predictive value 100%, negative predictive value 81.2%, and accuracy 92.68% (P < 0.001). Conclusion Although DWI-MRI is unable to differentiate between malignant and benign pleural effusion, its combined morphological and functional information provide valid non-invasive method to accurately characterize pleural soft tissue diseases differentiating benign from malignant lesions with higher specificity and accuracy than conventional MRI.

Accuracy of Medical Examiner’s Assessment for Near–Real-Time Surveillance of Fatal Drug Overdoses, King County, Washington, March 2017–February 2018

2021 ◽  
pp. 003335492110084
Author(s):  
Kirsten Vannice ◽  
Julia Hood ◽  
Nicole Yarid ◽  
Meagan Kay ◽  
Richard Harruff ◽  
...  
Keyword(s):  
Public Health ◽  
Positive Predictive Value ◽  
Real Time ◽  
Negative Predictive Value ◽  
Drug Overdose ◽  
Predictive Value ◽  
Death Certificate ◽  
King County ◽  
Public Health Response ◽  
Drug Overdoses

Objectives Up-to-date information on the occurrence of drug overdose is critical to guide public health response. The objective of our study was to evaluate a near–real-time fatal drug overdose surveillance system to improve timeliness of drug overdose monitoring. Methods We analyzed data on deaths in the King County (Washington) Medical Examiner’s Office (KCMEO) jurisdiction that occurred during March 1, 2017–February 28, 2018, and that had routine toxicology test results. Medical examiners (MEs) classified probable drug overdoses on the basis of information obtained through the death investigation and autopsy. We calculated sensitivity, positive predictive value, specificity, and negative predictive value of MEs’ classification by using the final death certificate as the gold standard. Results KCMEO investigated 2480 deaths; 1389 underwent routine toxicology testing, and 361 were toxicologically confirmed drug overdoses from opioid, stimulant, or euphoric drugs. Sensitivity of the probable overdose classification was 83%, positive predictive value was 89%, specificity was 96%, and negative predictive value was 94%. Probable overdoses were classified a median of 1 day after the event, whereas the final death certificate confirming an overdose was received by KCMEO an average of 63 days after the event. Conclusions King County MEs’ probable overdose classification provides a near–real-time indicator of fatal drug overdoses, which can guide rapid local public health responses to the drug overdose epidemic.

scholarly journals Role of annexin A2 and osteopontin for early diagnosis of hepatocellular carcinoma in hepatitis C virus patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Abd El-Fattah F. Hanno ◽  
Fatma M. Abd El-Aziz ◽  
Akram A. Deghady ◽  
Ehab H. El-Kholy ◽  
Aborawy I. Aborawy
Keyword(s):  
Hepatocellular Carcinoma ◽  
Chronic Hepatitis ◽  
Hepatitis C ◽  
Early Diagnosis ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Chronic Hepatitis C ◽  
Predictive Value ◽  
Annexin A2 ◽  
Alpha Fetoprotein

Abstract Background Liver cancer is the fifth most common cancer and the second most frequent cause of cancer-related death globally. Early stages of hepatocellular carcinoma (0&A) can be treated with curative procedures. The aim of this work was to evaluate the role of annexin A2 and osteopontin for early diagnosis of hepatocellular carcinoma in hepatitis C virus patients. Methods The study was carried out on 80 patients classified into two groups. Group A had 40 chronic hepatitis C patients without hepatocellular carcinoma, while group B had 40 chronic hepatitis C patients with early hepatocellular carcinoma (stages; 0&A). All patients were subjected to thorough history taking, clinical examination, liver function tests, renal function tests, serum alpha-fetoprotein, serum osteopontin, and serum annexin A2. Results Serum alpha-fetoprotein was found to be statistically significantly higher in patients with the hepatocellular carcinoma group than the chronic hepatitis C group. The ROC curve for alpha-fetoprotein for detection of HCC was significant, its diagnostic performance was 0.818* (p < 0.001*), and the cutoff point for predicting the probability for HCC was 6.0 (ng/ml) with sensitivity of 77.50%, specificity of 82.50%, positive predictive value of 81.60%, negative predictive value of 78.6%, and accuracy of 80%. Serum osteopontin was found to be statistically significantly higher in patients from the hepatocellular carcinoma group than the chronic hepatitis C group. The ROC curve for osteopontin was significant, its diagnostic performance was 0.739* (p < 0.001*), the cutoff point was 13.2 (ng/ml) with sensitivity of 65.0%, specificity of 90.0%, positive predictive value of 86.70%, negative predictive value of 72.0%, and accuracy of 77.0%. Serum annexin A2 was found to be statistically significantly higher in patients from the hepatocellular carcinoma group than the chronic hepatitis C group. The ROC curve for annexin A2 was significant, its diagnostic performance was 0.927* (p < 0.001*), the cutoff point was 10.1(ng/ml) with sensitivity of 85.0%, specificity of 85.0%, positive predictive value of 85.0%, negative predictive value of 85.0%, and accuracy of 85.0%. Conclusions Osteopontin had better specificity but lower sensitivity than serum alpha-fetoprotein for early diagnosis of hepatocellular carcinoma. Annexin A2 had better diagnostic sensitivity and specificity than alpha-fetoprotein for early diagnosis of hepatocellular carcinoma.

scholarly journals POS0706 PERFORMANCES OF DIFFERENT CLASSIFICATION CRITERIA FOR SYSTEMIC LUPUS ERYTHEMATOSUS IN A SINGLE CENTER COHORT FROM TURKEY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 602.1-603
Author(s):  
E. S. Torun ◽  
E. Bektaş ◽  
F. Kemik ◽  
M. Bektaş ◽  
C. Cetin ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Antiphospholipid Syndrome ◽  
Lupus Erythematosus ◽  
Predictive Value ◽  
Sjogren's Syndrome ◽  
Classification Criteria ◽  
Systemic Lupus ◽  
Acr Criteria

Background:Recently developed EULAR/ACR classification criteria for systemic lupus erythematosus (SLE) have important differences compared to the 2012 Systemic Lupus International Collaborating Clinics (SLICC) SLE classification criteria and the revised 1997 American College of Rheumatology (ACR) criteria: The obligatory entry criterion of antinuclear antibody (ANA) positivity is introduced and a “weighted” approach is used1. Sensitivity and specificity of these three criteria have been debated and may vary in different populations and clinical settings.Objectives:We aim to compare the performances of three criteria sets/rules in a large cohort of patients and relevant diseased controls from a reference center with dedicated clinics for SLE and other autoimmune/inflammatory connective tissue diseases from Turkey.Methods:We reviewed the medical records of SLE patients and diseased controls for clinical and laboratory features relevant to all sets of criteria. Criteria sets/rules were analysed based on sensitivity, positive predictive value, specificity and negative predictive value, using clinical diagnosis with at least 6 months of follow-up as the gold standard. A subgroup analysis was performed in ANA positive patients for both SLE patients and diseased controls. SLE patients that did not fulfil 2012 SLICC criteria and 2019 EULAR/ACR criteria and diseased controls that fulfilled these criteria were evaluated.Results:A total of 392 SLE patients and 294 non-SLE diseased controls (48 undifferentiated connective tissue disease, 51 Sjögren’s syndrome, 43 idiopathic inflammatory myopathy, 50 systemic sclerosis, 52 primary antiphospholipid syndrome, 15 rheumatoid arthritis, 15 psoriatic arthritis and 20 ANCA associated vasculitis) were included into the study. Hundred and fourteen patients (16.6%) were ANA negative.Sensitivity was more than 90% for 2012 SLICC criteria and 2019 EULAR/ACR criteria and positive predictive value was more than 90% for all three criteria (Table 1). Specificity was the highest for 1997 ACR criteria. Negative predictive value was 76.9% for ACR criteria, 88.4% for SLICC criteria and 91.7% for EULAR/ACR criteria.In only ANA positive patients, sensitivity was 79.6% for 1997 ACR criteria, 92.2% for 2012 SLICC criteria and 96.1% for 2019 EULAR/ACR criteria. Specificity was 92.6% for ACR criteria, 87.8% for SLICC criteria 85.2% for EULAR/ACR criteria.Eleven clinically diagnosed SLE patients had insufficient number of items for both 2012 SLICC and 2019 EULAR/ACR criteria. Both criteria were fulfilled by 16 diseased controls: 9 with Sjögren’s syndrome, 5 with antiphospholipid syndrome, one with dermatomyositis and one with systemic sclerosis.Table 1.Sensitivity, positive predictive value, specificity and negative predictive value of 1997 ACR, 2012 SLICC and 2019 EULAR/ACR classification criteriaSLE (+)SLE (-)Sensitivity (%)Positive Predictive Value (%)Specificity (%)Negative Predictive Value (%)1997 ACR(+) 308(-) 841527978.695.494.976.92012 SLICC(+) 357(-) 352626891.193.291.288.42019 EULAR/ACR(+) 368(-) 242826693.892.990.591.7Conclusion:In this cohort, although all three criteria have sufficient specificity, sensitivity and negative predictive value of 1997 ACR criteria are the lowest. Overall, 2019 EULAR/ACR and 2012 SLICC criteria have a comparable performance, but if only ANA positive cases and controls are analysed, the specificity of both criteria decrease to less than 90%. Some SLE patients with a clinical diagnosis lacked sufficient number of criteria. Mostly, patients with Sjögren’s syndrome or antiphospholipid syndrome are prone to misclassification by both recent criteria.References:[1]Aringer M, Costenbader K, Daikh D, et al. 2019 European League Against Rheumatism/American College of Rheumatology classification criteria for systemic lupus erythematosus. Ann Rheum Dis 2019;78:1151-1159.Disclosure of Interests:None declared

Influence of lesion location on the accuracy of CT derived FFR: head-to-head comparison with invasive FFR

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Moshage ◽  
S Smolka ◽  
S Achenbach ◽  
F Ammon ◽  
P Ferstl ◽  
...  
Keyword(s):  
Coronary Angiography ◽  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Invasive Coronary Angiography ◽  
Roc Curve Analysis ◽  
Jude Medical ◽  
Lesion Location ◽  
Distal Vessel

Abstract Background The accuracy of CT-derived FFR (FFRCT) has been repeatedly reported. However, the influence of lesion location on accuracy is unknown. Therefore, we evaluated the diagnostic accuracy of FFRCT to detect lesion-specific ischemia and determined the influence of lesion location (proximal vs. distal vessel segments) compared to invasively measured FFR in patients with suspected CAD. Methods A total of 136 vessels in which “Dual-Source”-CT coronary angiography had been performed due to suspected CAD and who were further referred for invasive coronary angiography with invasive FFR measurement within three months of the index CT examination were retrospectively identified and screened for inclusion in this analysis. Patients with either left main coronary artery stenoses, bifurcation or ostial stenoses were excluded. Invasive FFR was measured using a pressure wire (CERTUS®, St. Jude Medical, Minnesota, USA or Verrata®, Volcano, San Diego, USA). FFRCT was calculated using an on-site prototype (cFFR Version 3.0, Siemens Healthineers, Forchheim, Germany). All vessels were analyzed by an experienced observer blinded to the results of invasive FFR. Stenoses with invasively measured FFR ≤0.80 were classified as hemodynamically significant. We evaluated the diagnostic accuracy of FFRCT in proximal vs. non-proximal vessel segments. Proximal lesions included stenoses located in segment one, six, eleven and twelve. All other stenoses were categorized as distal lesions. Results Out of 136 coronary stenoses, 47 (35%) were located in proximal segments and 89 (65%) lesions were located in distal segments. Compared to invasive FFR, the sensitivity of FFRCT to correctly identify/exclude hemodynamically significant stenoses in proximal vessel segments was 93% (95% CI: 68–99.8%) and the specificity was 100% (95% CI: 89–100%), compared to a sensitivity of 72% (95% CI: 46.5–90%) and a specificity of 87% (95% CI: 77–94%) for FFRCT in distal lesions. The positive predictive value was 100% and the negative predictive value was 97% (95% CI: 82.8–99.5%) compared to a positive predictive value of 59% (95% CI: 42–93.9%) and a negative predictive value of 93% (95% CI: 85.4–96.3%) for proximal vs. distal vessel segment, respectively. This corresponds to an accuracy of 98% vs. 84%, respectively (p=0.02). ROC-Curve analysis showed a slightly higher – albeit non-significant – area under the curve for FFRCT to detect hemodynamic relevance in proximal lesions compared to distal lesions (AUC 0.95, p&lt;0.001 vs. AUC: 0.86, p&lt;0.001, respectively, p=0.2). Conclusion FFRCT obtained using an on-site prototype shows overall a high diagnostic accuracy for detecting lesions causing ischemia as compared to invasive FFR with a trend towards better diagnostic performance in proximal vessel segments. Funding Acknowledgement Type of funding source: None

scholarly journals Development of an Electronic Algorithm to Identify Inappropriate Antibiotic Prescribing for Pediatric Pharyngitis

2020 ◽  
Vol 41 (S1) ◽  
pp. s188-s189
Author(s):  
Jeffrey Gerber ◽  
Robert Grundmeier ◽  
Keith Hamilton ◽  
Lauri Hicks ◽  
Melinda Neuhauser ◽  
...  
Keyword(s):  
Predictive Value ◽  
Gold Standard ◽  
Antibiotic Stewardship ◽  
Chart Review ◽  
Antibiotic Use ◽  
Audit And Feedback ◽  
Urgent Care ◽  
Antibiotic Prescribing ◽  
Tract Infections ◽  
The Impact

Background: Antibiotic overuse contributes to antibiotic resistance and unnecessary adverse drug effects. Antibiotic stewardship interventions have primarily focused on acute-care settings. Most antibiotic use, however, occurs in outpatients with acute respiratory tract infections such as pharyngitis. The electronic health record (EHR) might provide an effective and efficient tool for outpatient antibiotic stewardship. We aimed to develop and validate an electronic algorithm to identify inappropriate antibiotic use for pediatric outpatients with pharyngitis. Methods: This study was conducted within the Children’s Hospital of Philadelphia (CHOP) Care Network, including 31 pediatric primary care practices and 3 urgent care centers with a shared EHR serving >250,000 children. We used International Classification of Diseases, Tenth Revision (ICD-10) codes to identify encounters for pharyngitis at any CHOP practice from March 15, 2017, to March 14, 2018, excluding those with concurrent infections (eg, otitis media, sinusitis), immunocompromising conditions, or other comorbidities that might influence the need for antibiotics. We randomly selected 450 features for detailed chart abstraction assessing patient demographics as well as practice and prescriber characteristics. Appropriateness of antibiotic use based on chart review served as the gold standard for evaluating the electronic algorithm. Criteria for appropriate use included streptococcal testing, use of penicillin or amoxicillin (absent β-lactam allergy), and a 10-day duration of therapy. Results: In 450 patients, the median age was 8.4 years (IQR, 5.5–9.0) and 54% were women. On chart review, 149 patients (33%) received an antibiotic, of whom 126 had a positive rapid strep result. Thus, based on chart review, 23 subjects (5%) diagnosed with pharyngitis received antibiotics inappropriately. Amoxicillin or penicillin was prescribed for 100 of the 126 children (79%) with a positive rapid strep test. Of the 126 children with a positive test, 114 (90%) received the correct antibiotic: amoxicillin, penicillin, or an appropriate alternative antibiotic due to b-lactam allergy. Duration of treatment was correct for all 126 children. Using the electronic algorithm, the proportion of inappropriate prescribing was 28 of 450 (6%). The test characteristics of the electronic algorithm (compared to gold standard chart review) for identification of inappropriate antibiotic prescribing were sensitivity (99%, 422 of 427); specificity (100%, 23 of 23); positive predictive value (82%, 23 of 28); and negative predictive value (100%, 422 of 422). Conclusions: For children with pharyngitis, an electronic algorithm for identification of inappropriate antibiotic prescribing is highly accurate. Future work should validate this approach in other settings and develop and evaluate the impact of an audit and feedback intervention based on this tool.Funding: NoneDisclosures: None

scholarly journals Foundational Statistical Principles in Medical Research: Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 503
Author(s):  
Thomas F. Monaghan ◽  
Syed N. Rahman ◽  
Christina W. Agudelo ◽  
Alan J. Wein ◽  
Jason M. Lazar ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Medical Literature ◽  
Disease Prevalence ◽  
Positive Test Result ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Test Result ◽  
Test Probability

Sensitivity, which denotes the proportion of subjects correctly given a positive assignment out of all subjects who are actually positive for the outcome, indicates how well a test can classify subjects who truly have the outcome of interest. Specificity, which denotes the proportion of subjects correctly given a negative assignment out of all subjects who are actually negative for the outcome, indicates how well a test can classify subjects who truly do not have the outcome of interest. Positive predictive value reflects the proportion of subjects with a positive test result who truly have the outcome of interest. Negative predictive value reflects the proportion of subjects with a negative test result who truly do not have the outcome of interest. Sensitivity and specificity are inversely related, wherein one increases as the other decreases, but are generally considered stable for a given test, whereas positive and negative predictive values do inherently vary with pre-test probability (e.g., changes in population disease prevalence). This article will further detail the concepts of sensitivity, specificity, and predictive values using a recent real-world example from the medical literature.

scholarly journals Role of diffusion-weighted magnetic resonance imaging in assessment of mammographically detected asymmetric densities

2020 ◽  
Vol 51 (1) ◽  
Author(s):  
Mohamed Zidan ◽  
Shimaa Ali Saad ◽  
Eman Abo Elhamd ◽  
Hosam Eldin Galal ◽  
Reem Elkady
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Benign Lesions ◽  
Adc Value ◽  
Dce Mri ◽  
Diffusion Weighted ◽  
Breast Asymmetries ◽  
Malignant Lesions

Abstract Background Asymmetric breast density is a potentially perplexing finding; it may be due to normal hormonal variation of the parenchymal pattern and summation artifact or it may indicate an underlying true pathology. The current study aimed to identify the role of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) values in the assessment of breast asymmetries. Results Fifty breast lesions were detected corresponding to the mammographic asymmetry. There were 35 (70%) benign lesions and 15 (30%) malignant lesions. The mean ADC value was 1.59 ± 0.4 × 10–3 mm2/s for benign lesions and 0.82 ± 0.3 × 10–3 mm2/s for malignant lesions. The ADC cutoff value to differentiate between benign and malignant lesions was 1.10 × 10–3 mm2/s with sensitivity 80%, specificity 88.6%, positive predictive value 75%, negative predictive value 91%, and accuracy 86%. Best results were achieved by implementation of the combined DCE-MRI and DWI protocol, with sensitivity 93.3%, specificity 94.3%, positive predictive value 87.5%, negative predictive value 97.1%, and accuracy 94%. Conclusion Dynamic contrast-enhanced MRI (DCE-MRI) was the most sensitive method for the detection of the underlying malignant pathology of breast asymmetries. However, it provided a limited specificity that may cause improper final BIRADS classification and may increase the unnecessary invasive procedures. DWI was used as an adjunctive method to DCE-MRI that maintained high sensitivity and increased specificity and the overall diagnostic accuracy of breast MRI examination. Best results can be achieved by the combined protocol of DCE-MRI and DWI.

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