Routine Diagnostic Tests for Periprosthetic Joint Infection Demonstrate a High False-Negative Rate and Are Influenced by the Infecting Organism

2018 ◽  
Vol 100 (23) ◽  
pp. 2057-2065 ◽  
Author(s):  
Michael M. Kheir ◽  
Timothy L. Tan ◽  
Noam Shohat ◽  
Carol Foltz ◽  
Javad Parvizi
Keyword(s):  
Periprosthetic Joint Infection ◽  
Diagnostic Tests ◽  
Joint Infection ◽  
False Negative ◽  
False Negative Rate ◽  
Negative Rate ◽  
High False Negative Rate

scholarly journals High mortality with High false negative rate: COVID-19 infection in patients with hematologic malignancies

2021 ◽  
Vol 106 ◽  
pp. 106582
Author(s):  
Alex Niu ◽  
Bo Ning ◽  
Francisco Socola ◽  
Hana Safah ◽  
Tim Reynolds ◽  
...  
Keyword(s):  
High Mortality ◽  
False Negative ◽  
False Negative Rate ◽  
Hematologic Malignancies ◽  
Negative Rate ◽  
High False Negative Rate

scholarly journals 0587 Convenience vs Accuracy: Negative Predictability of the Home Sleep Test in Clinical Practice

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A225-A225
Author(s):  
C D Morse ◽  
S Meissner ◽  
L Kodali
Keyword(s):  
Clinical Practice ◽  
Sleep Apnea ◽  
False Negative ◽  
False Negative Rate ◽  
True Negative ◽  
Negative Rate ◽  
High False Negative Rate ◽  
Obstructive Sleep ◽  
Respiratory Disturbance ◽  
Lost To Follow Up

Abstract Introduction Sleep apnea is a serious disorder associated with numerous health conditions. In clinical practice, providers order screening home sleep testing (HST) for obstructive sleep apnea (OSA); however, there is limited research about the negative predictive value (NPV) and false negative rate of this test. Providers may not understand HST limitations; therefore, what is the NPV and false negative rate in clinical practice? Methods A retrospective study of non-diagnostic HST is conducted in a Northeastern US rural community sleep clinic. The study population includes adult patients ≥ 18 years old who underwent HST from 2016-2019. The non-diagnostic HST result is compared to the gold standard, the patient’s nocturnal polysomnogram (NPSG). The results provide the NPV (true negative/total) and false negative (true positive/total) for the non-diagnostic HST. Results We identified 211 potential patients with a mean age of 43 years, of which 67% were female. Of those, 85% (n=179) underwent NPSG, with the others declining/delaying testing or lost to follow up. The non-diagnostic HST showed 15.6% NPV for no apnea using AHI<5 and 8.4% NPV using respiratory disturbance index (tRDI)<5. The false negative rate for AHI/tRDI was 84.4% and 91.6%, respectively. The AHI for positive tests ranged from 5-89 per hour (mean AHI 14.9/tRDI 16/hour), of which OSA was identified with an elevated AHI (≥5) ranging from 54.2% mild, 21.8% moderate, and 8.4% severe. Conclusion The high false negative rate of the HST is alarming. Some providers and patients may forgo NPSG after non-diagnostic HST due to a lack of understanding for the HST’s limitations. Knowing that the non-diagnostic HST is a very poor predictor of no sleep apnea will help providers advise patients appropriately for the necessity of the NPSG. The subsequent NPSG provides an accurate diagnosis and, therefore, an informed decision about pursuing or eschewing sleep apnea treatment. Support none

scholarly journals Septic arthritis of the knee: the use and effect of antibiotics prior to diagnostic aspiration

2012 ◽  
Vol 94 (5) ◽  
pp. 351-355 ◽  
Author(s):  
P Hindle ◽  
E Davidson ◽  
LC Biant
Keyword(s):  
Septic Arthritis ◽  
Joint Infection ◽  
False Negative ◽  
False Negative Rate ◽  
Standard Test ◽  
Entire Cohort ◽  
High False Negative Rate ◽  
Total Knee ◽  
Prosthetic Knees ◽  
No Gold Standard

Septic arthritis of the native knee joint and total knee arthroplasty both cause diagnostic and treatment issues. There is no gold standard test to diagnose a joint infection and the use of joint aspiration is commonly relied on. It is widely accepted by orthopaedic surgeons that antibiotics should be withheld until aspiration has been performed to increase the odds of identifying an organism. Patients often present to other specialties that may not be as familiar with these principles. Our study found that 25 (51%) of the 49 patients treated for septic arthritis of the native or prosthetic knee in our unit over a 3-year period had received antibiotics prior to discussion or review by the on-call orthopaedic service. Patients were significantly less likely to demonstrate an organism on initial microscopy (entire cohort: p=0.001, native knees: p=0.006, prosthetic knees: p=0.033) or on subsequent culture (entire cohort: p=0.001, native knees: p=0.017, prosthetic knees: p=0.012) of their aspirate if they had received antibiotics. The sensitivity of microscopy in all patients dropped from 58% to 12% when patients had received antibiotics (native knees: 46% to 0%, prosthetic knees: 72% to 27%). The sensitivity of the culture dropped from 79% to 28% in all patients when the patient had received antibiotics (native knees: 69% to 21%, prosthetic knees: 91% to 36%). This study demonstrated how the management of patients with suspected cases of septic arthritis of the knee may be compromised by empirical administration of antibiotics. These patients were significantly less likely to demonstrate an organism on microscopy and culture of their initial aspirate. There is a significant high false negative rate associated with knee aspiration with prior administration of antibiotic therapy.

scholarly journals A False Negative Study of the Steganalysis Tool Stegdetect

2020 ◽  
Vol 10 (22) ◽  
pp. 8188
Author(s):  
Benjamin Aziz ◽  
Jeyong Jung ◽  
Julak Lee ◽  
Yong-Tae Chun
Keyword(s):  
Digital Forensics ◽  
False Negative ◽  
False Negative Rate ◽  
Jpeg Images ◽  
Negative Rate ◽  
High False Negative Rate ◽  
Negative Study

In this study, we evaluated one of the modern automated steganalysis tools, Stegdetect, to study its false negative rates when analysing a bulk of images. In so doing, we used JPHide method to embed a randomly generated messages into 2000 JPEG images. The aim of this study is to help digital forensics analysts during their investigations by means of providing an idea of the false negative rates of Stegdetect. This study found that (1) the false negative rates depended largely on the tool’s sensitivity values, (2) the tool had a high false negative rate between the sensitivity values from 0.1 to 3.4 and (3) the best sensitivity value for detection of JPHide method was 6.2. It is therefore recommended that when analysing a huge bulk of images forensic analysts need to take into consideration sensitivity values to reduce the false negative rates of Stegdetect.

scholarly journals High False-Negative Rate for Nonalcoholic Steatohepatitis in Extreme Obesity

2016 ◽  
Vol 150 (1) ◽  
pp. 283-284 ◽  
Author(s):  
Glenn S. Gerhard ◽  
Christopher D. Still ◽  
Johanna K. DiStefano
Keyword(s):  
Nonalcoholic Steatohepatitis ◽  
False Negative ◽  
False Negative Rate ◽  
Extreme Obesity ◽  
Negative Rate ◽  
High False Negative Rate

scholarly journals Reconciling epidemiological models with misclassified case-counts for SARS-CoV-2 with seroprevalence surveys: A case study in Delhi, India

2020 ◽  
Author(s):  
Rupam Bhattacharyya ◽  
Ritwik Bhaduri ◽  
Ritoban Kundu ◽  
Maxwell Salvatore ◽  
Bhramar Mukherjee
Keyword(s):  
Diagnostic Tests ◽  
False Negative ◽  
False Negative Rate ◽  
Antibody Test ◽  
Population Based ◽  
National Capital Region ◽  
Rt Pcr ◽  
High False Negative Rate ◽  
True Number ◽  
National Capital

Underreporting of COVID-19 cases and deaths is a hindrance to correctly modeling and monitoring the pandemic. This is primarily due to limited testing, lack of reporting infrastructure and a large number of asymptomatic infections. In addition, diagnostic tests (RT-PCR tests for detecting current infection) and serological antibody tests for IgG (to assess past infections) are imperfect. In particular, the diagnostic tests have a high false negative rate. Epidemiologic models with a latent compartment for unascertained infections like the Susceptible-Exposed-Infected-Removed (SEIR) models can provide predictions for unreported cases and deaths under certain assumptions. Typically, the number of unascertained cases is unobserved and thus we cannot validate these estimates for a real study except for simulation studies. Population-based seroprevalence studies can provide a rough estimate of the total number of infections and help us check epidemiologic model projections. In this paper, we develop a method to account for high false negative rates in RT-PCR in an extension to the classic SEIR model. We apply this method to Delhi, the national capital region of India, with a population of 19.8 million and a COVID-19 hotspot of the country, obtaining estimates of underreporting factor for cases at 34-53 times and that for deaths at 8-13 times. Based on a recently released serological survey for Delhi with an estimated 22.86% seroprevalence, we compute adjusted estimates of the true number of infections reported by the survey (after accounting for misclassification of the antibody test results) which is largely consistent with the model outputs, yielding an underreporting factor for cases from 30-42. Together with the model and the serosurvey, this implies approximately 96-98% cases in Delhi remained unreported and whereas only 109,140 cases were reported on July 10, the true number of infections varied somewhere between 4.4-4.6 million across different estimates. While repeated serological monitoring is resource intensive, model-based adjustments, run with the most up to date data, can provide a viable option to keep track of the unreported cases and deaths and gauge the true extent of transmission of this insidious virus.

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