Abstract 037: The Accuracy of Self-reported Blood Pressure in the Medication Adherence Improvement Support App for Engagement - Blood Pressure (MedISAFE-BP) Trial

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Kyle Morawski ◽  
Roya Ghazinouri ◽  
Alexis Krumme ◽  
Julie Lauffenburger ◽  
Jessica Lee ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Clinical Care ◽  
Population Level ◽  
Smartphone Application ◽  
Self Report ◽  
Study Cohort ◽  
Use Of Self ◽  
Hypertension Knowledge

Introduction: The use of self-reported biometric values, such as blood pressure (BP), has been proposed as an efficient strategy for monitoring clinical care, evaluating health system performance, and conducting pragmatic randomized trials. Unfortunately, there is limited evidence about whether self-reported biometric readings are accurate and, if so, whether their accuracy is predicted by readily identifiable patient characteristics. Enrollment data from the ongoing Med ication adherence I mprovement S upport A pp F or E ngagement - B lood P ressure (MedISAFE-BP) trial provide a unique opportunity to address these questions. Methods: MedISAFE-BP is a randomized clinical trial evaluating the effect of the Medisafe smartphone application on BP among subjects with poorly controlled hypertension, defined as ≥140mmHg systolic per JNC8 guidelines. Subjects were recruited through online patient communities, social media, and targeted advertisements. Subjects who indicated that their BP was poorly controlled while on medication underwent further screening. After informed consent, subjects provided baseline information including demographics, comorbidities, the number of BP medications they were currently taking, hypertension knowledge, patient activation measured by the Consumer Health Activation Index, and self-reported adherence. Subjects were then mailed a home BP cuff to verify their self-reported blood pressure. We evaluated the positive predictive value of self-reported poorly controlled hypertension using the measured BP readings. We then used multivariable logistic regression to identify predictors of having a measured BP value that was actually poorly controlled. Results: Our study cohort consisted of 1,142 individuals who self-reported as having poorly controlled BP. The positive predictive value of poorly-controlled BP by self-report was only 37%. In fact, 284 (24%) subjects had systolic BPs that were normal (systolic BP < 120 mmHg). Factors that were independently associated with accurate self-report included older age (odds ratio [OR] 1.3 per decade, 95% confidence interval [CI] 1.2-1.5), a history of prior stroke (OR 2.5, CI 1.2-5.2), diabetes mellitus (OR 1.5, CI 1.1-2.2), and a low level of activation (OR 1.63, CI 1.2-2.2). Hypertension knowledge, education, and self-reported adherence were not associated with accurately self-reporting BP. Discussion: In this cohort of individuals who reported that their BP was poorly controlled, only one-third actually had elevated BP when measured with a home BP cuff. While this discrepancy may have many underlying causes, it suggests that the use of self-reported BPs is not an accurate method of monitoring hypertension control at the population-level. Reassuringly, several factors are independently associated with accurate self-reported BPs, and thus there may be some subgroups for whom self-report can be relied upon.

scholarly journals Blood Pressure Trajectories Across the Life Course

2021 ◽  
Vol 34 (3) ◽  
pp. 234-241
Author(s):  
Norrina B Allen ◽  
Sadiya S Khan
Keyword(s):  
Blood Pressure ◽  
Measurement Errors ◽  
Clinical Care ◽  
Population Level ◽  
Cumulative Exposure ◽  
Older Adulthood ◽  
Individual Level ◽  
The Life Course ◽  
Level Group ◽  
Improve Health

Abstract High blood pressure (BP) is a strong modifiable risk factor for cardiovascular disease (CVD). Longitudinal BP patterns themselves may reflect the burden of risk and vascular damage due to prolonged cumulative exposure to high BP levels. Current studies have begun to characterize BP patterns as a trajectory over an individual’s lifetime. These BP trajectories take into account the absolute BP levels as well as the slope of BP changes throughout the lifetime thus incorporating longitudinal BP patterns into a single metric. Methodologic issues that need to be considered when examining BP trajectories include individual-level vs. population-level group-based modeling, use of distinct but complementary BP metrics (systolic, diastolic, mean arterial, mid, and pulse pressure), and potential for measurement errors related to varied settings, devices, and number of readings utilized. There appear to be very specific developmental periods during which divergent BP trajectories may emerge, specifically adolescence, the pregnancy period, and older adulthood. Lifetime BP trajectories are impacted by both individual-level and community-level factors and have been associated with incident hypertension, multimorbidity (CVD, renal disease, cognitive impairment), and overall life expectancy. Key unanswered questions remain around the additive predictive value of BP trajectories, intergenerational contributions to BP patterns (in utero BP exposure), and potential genetic drivers of BP patterns. The next phase in understanding BP trajectories needs to focus on how best to incorporate this knowledge into clinical care to reduce the burden of hypertensive-related outcomes and improve health equity.

scholarly journals A Methodology for Evaluating the Performance of Alerting and Detection Algorithms Running on Continuous Patient Data

2017 ◽  
Author(s):  
Larry J. Eshelman ◽  
Minnan Xu-Wilson ◽  
Abigail A. Flower ◽  
Brian Gross ◽  
Larry Nielsen ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Hemodynamic Instability ◽  
Patient Data ◽  
Physiological Data ◽  
Retrospective Data ◽  
Icu Stay ◽  
Sensitivity Specificity ◽  
Measures Of Performance

ABSTRACTObjectivesClinicians in the intensive care unit (ICU) are presented with a large number of physiological data consisting of periodic and frequently sampled measurements, such as heart rate and blood pressure, as well as aperiodic measurements, such as noninvasive blood pressure and laboratory studies. Because this data can be overwhelming, there is considerable interest in designing algorithms that help integrate and interpret this data and assist ICU clinicians in detecting or predicting in advance patients who may be deteriorating. In order to decide whether to deploy such algorithms in a clinical trial, it is important to evaluate these algorithms using retrospective data. However, the fact that these algorithms will be running continuously, i.e., repeatedly sampling incoming patient data, presents some novel challenges for algorithm evaluation. Commonly used measures of performance such as sensitivity and positive predictive value (PPV) are easily applied to static “snapshots” of patient data, but can be very misleading when applied to indicators or alerting algorithms that are running on continuous data. Our objective is to create a method for evaluating algorithm performance on retrospective data with the algorithm running continuously throughout the patient’s stay as it would in a real ICU.MethodsWe introduce our evaluation methodology in the context of evaluating an algorithm, a Hemodynamic Instability Indicator (HII), for assisting bedside ICU clinicians with the early detection of hemodynamic instability before the onset of acute hypotension. Each patient’s ICU stay is divided into segments that are labelled as hemodynamically stable or unstable based on clinician interventions typically aimed at treating hemodynamic instability. These segments can be of varying length with varying degrees of exposure to potential alerts, whether true positive or false positive. Furthermore, to simulate how clinicians might interact with the alerting algorithm, we use a dynamic alert supervision mechanism which suppresses subsequent alerts unless the indicator has significantly deteriorated since the prior alert. Under these conditions determining what counts as a positive or negative instance, and calculations of sensitivity, specificity, and positive predictive value can be problematic. We introduce a methodology for consistently counting positive and negative instances. The methodology distinguishes between counts based on alerting events and counts based on sub-segments, and show how they can be applied in calculating measures of performance such as sensitivity, specificity, positive predictive value.ResultsThe introduced methodology is applied to retrospective evaluation of two algorithms, HII and an alerting algorithm based on systolic blood pressure. We use a database, consisting of data from 41,707 patients from 25 US hospitals, to evaluate the algorithms. Both algorithms are evaluated running continuously throughout each patient’s stay as they would in a real ICU setting. We show how the introduced performance measures differ for different algorithms and for different assumptions.DiscussionThe standard measures of diagnostic tests in terms of true positives, false positives, etc. are based on certain assumptions which may not apply when used in the context of measuring the performance on an algorithm running continuously, and thus repeatedly sampling from the same patient. When such measures are being reported it is important that the underlying assumptions be made explicit; otherwise, the results can be very misleading.ConclusionWe introduce a methodology for evaluating how an alerting algorithm or indicator will perform running continuously throughout every patient’s ICU stay, not just for a subset of patients for selected episodes.

Clinical validation of the self-reported Glasgow Antipsychotic Side-effect Scale using the clinician-rated UKU side-effect scale as gold standard reference

2020 ◽  
Vol 34 (8) ◽  
pp. 820-828
Author(s):  
Marlene Schouby Bock ◽  
Oona Nørgaard Van Achter ◽  
David Dines ◽  
Maria Simonsen Speed ◽  
Christoph U Correll ◽  
...  
Keyword(s):  
Side Effects ◽  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Gold Standard ◽  
Side Effect ◽  
Self Report ◽  
Measurement Based Care ◽  
Gold Standard Reference ◽  
Antipsychotic Side Effects

Background: Antipsychotics are key for the treatment of psychotic and several non-psychotic disorders. Unfortunately, antipsychotic medications are associated with side effects, which may reduce quality of life and treatment adherence. Therefore, regular screening of antipsychotic side effects is essential. The Glasgow Antipsychotic Side-effect Scale is a patient self-report scale developed for this purpose. However, the Glasgow Antipsychotic Side-effect Scale has only been validated against another self-report side effect measure, which is suboptimal. Objective: We aimed to validate the Glasgow Antipsychotic Side-effect Scale using the clinician-rated Udvalg for Kliniske Undersøgelser side-effect rating scale as the gold standard reference. Results: 81 antipsychotic-treated outpatients with schizophrenia-spectrum disorders (age = 42±13 years; males = 43%, schizophrenia = 77%, illness duration: median = 11 years) completed the Glasgow Antipsychotic Side-effect Scale and were subsequently scored on the Udvalg for Kliniske Undersøgelser by trained raters. Sensitivity, specificity, positive predictive value and negative predictive value were calculated for paired Glasgow Antipsychotic Side-effect Scale and Udvalg for Kliniske Undersøgelser items. Sensitivity of Glasgow Antipsychotic Side-effect Scale items ranged from 33–96%, with 19 (86%) having >75% sensitivity. Lowest sensitivity emerged for “nocturnal enuresis” (33%), “galactorrhea” (50%) and “hyperkinesia” 14–99%, with 14 items (64%) having >75% specificity, being lowest for “asthenia” (14%), “polyuria/polydipsia” (35%), “sedation” (41%), “akathisia” (53%), “dystonia” (65%), “hyperkinesia” (68%), “hypokinesia” (70%) and “accommodation” (70%). Positive predictive value ranged from 7–85%, with six items (27%) having a positive predictive value >75%. Negative predictive value ranged from 40–98%, with 21 items (95%) having a negative predictive value >75%. The mean time to complete the Glasgow Antipsychotic Side-effect Scale was 4±2 minutes. Conclusion: The Glasgow Antipsychotic Side-effect Scale demonstrated satisfactory validity as a self-rated tool for antipsychotic side effects and may aid measurement-based care and decision-making.

scholarly journals The Performance of Two Rapid Antigen Tests During Population-Level Screening for SARS-CoV-2 Infection

2021 ◽  
Vol 8 ◽  
Author(s):  
Mohammad Alghounaim ◽  
Hamad Bastaki ◽  
Farah Bin Essa ◽  
Hoda Motlagh ◽  
Salman Al-Sabah
Keyword(s):  
Positive Predictive Value ◽  
Prospective Study ◽  
Predictive Value ◽  
Point Of Care ◽  
Population Level ◽  
Lower Sensitivity ◽  
Rt Pcr ◽  
Antigen Tests ◽  
A Prospective Study ◽  
Antigen Testing

Background: SARS-CoV-2 antigen assays offer a rapid mean to diagnose and isolate infected individuals. However, their utility in population-level screening is unknown.Objectives: The performance of two antigen tests in detecting SARS-CoV-2 was assessed among individuals randomly selected in the community.Study Design: A prospective study that performed head-to-head comparison of two SARS-CoV-2 antigen assays. Individuals were recruited during community SARS-CoV-2 screening over 10 working days. Demographic and clinical data were collected. Standard Q COVID-19 Ag test, a point-of-care chromatographic assay, was conducted immediately, and then the sample was transported to the virology laboratory to perform PCR and the LIAISON SARS-CoV-2 Ag chemiluminesence immunoassay.Results: respiratory samples from 991 individuals were collected, and 62 were positive by PCR. Inconclusive PCR results were observed in 19 samples and were excluded. The median age of participants was 40.2 years (IQR 32.3–47.8), and 932 (94%) were males. Most (77.4%) of infections were asymptomatic. The sensitivity and the specificity of the LIAISON assay were 43.3% (95%CI 30.6–56.8) and 99.9% (95%CI 99.3–100). The Standard Q assay had lower sensitivity (30.6%, 95%CI 19.6–43.7) but similar specificity (98.8%, 95%CI, 97.8–99.4). Similarly, the LIAISON assay had higher positive predictive value (96.3%, 95%CI 81–99.9% vs. 63.3%, 95%CI, 43.9–80.1%). Both assays performed better in symptomatic patients and among samples with a low-cycle threshold (Ct &lt; 25).Conclusion: In our setting of random community surveillance, rapid antigen testing of nasopharyngeal swabs by either LIAISON SARS-CoV-2 Ag (DiaSorin) or Standard Q COVID-19 Ag (SD Biosensor) was less sensitive to detecting SARS-CoV-2 than the TaqPath COVID-19 RT-PCR.

scholarly journals Agreement between state registry, health record, and self-report of influenza vaccination

2021 ◽  
Author(s):  
Joshua G. Petrie ◽  
Helene Fligiel ◽  
Lois Lamerato ◽  
Emily T. Martin ◽  
Arnold S. Monto
Keyword(s):  
Positive Predictive Value ◽  
Influenza Vaccination ◽  
Predictive Value ◽  
Vaccine Effectiveness ◽  
Vaccination Status ◽  
Self Report ◽  
Health Record ◽  
Specific Product ◽  
Care Improvement

ABSTRACTBackgroundDocumentation of influenza vaccination, including the specific product received, is critical to estimate annual vaccine effectiveness (VE).MethodsWe assessed performance of the Michigan Care Improvement Registry (MCIR) in defining influenza vaccination status relative to documentation by provider records or self-report among subjects enrolled in a study of influenza VE from 2011 through 2019.ResultsThe specificity and positive predictive value of MCIR were high; however, >10% of vaccinations were identified only by other sources each season. The proportion of records captured by MCIR increased from a low of 67% in 2013-2014 to a high of 89% in 2018-2019, largely driven by increased capture of vaccination among adults.ConclusionsState vaccine registries, such as MCIR, are important tools for documenting influenza vaccination, including the specific product received. However, incomplete capture suggests that documentation from other sources and self-report should be used in combination with registries to reduce misclassification.

Abstract 063: Racial/Ethnic Differences In Blood Pressure Around The Time Of The 2016 United States General Election

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Andrew Y Hwang ◽  
Michelle I Cardel ◽  
Steven M Smith
Keyword(s):  
Blood Pressure ◽  
Psychosocial Stress ◽  
Mexican Americans ◽  
Population Level ◽  
General Election ◽  
Self Report ◽  
Stress Effect ◽  
Hypertension Status ◽  
Cross Sectional ◽  
Racial Ethnic

Introduction: Politics are a major source of stress and anxiety among U.S. adults, and the 2016 U.S. general election may have led to increased psychosocial stress among different racial/ethnic populations. Psychosocial stress can manifest physiologically in elevated blood pressure (BP). Yet, little is known regarding whether this response differs among racial/ethnic groups. We sought to characterize population-level changes in BP among non-Hispanic (NH) Whites, NH Blacks, and Mexican Americans before and after the 2016 U.S. general election. Methods: Using cross-sectional 2015-2018 National Health and Nutrition Examination Survey (NHANES) data, we included participants aged ≥20 years with ≥1 systolic BP (SBP) and diastolic BP (DBP) measurement during the examination periods just prior to and after the election. The pre-election period was from May 2016 to October 2016 and the post-election period was from November 2017 to April 2018. Survey-weighted data were analyzed to compare mean SBP and DBP pre- and post-election, stratified by race/ethnicity. Stratified analyses were also performed on hypertension status, defined as self-report, mean BP ≥140/90, or use of ≥1 antihypertensive drug. Results: We included 1,060 NH Whites, 720 NH Blacks, and 223 Mexican Americans during the pre-election period and 676 NH Whites, 564 NH Blacks, and 468 Mexican Americans during the post-election period. We observed a significant increase in SBP among Mexican Americans (mean±SEM, 118±0.5 mmHg [pre-election] vs. 121.7±0.7 mmHg [post-election], p=0.005), but not among NH Blacks (126.7±0.9 mmHg vs. 128.9±0.7 mmHg, p=0.083) nor NH Whites (123±0.6 mmHg vs. 124.8±1.4 mmHg, p=0.256). DBP increased among both Mexican Americans (69.5±0.5 mmHg vs. 72.6±1.1 mmHg, p=0.022) and NH Blacks (72.2±0.8 mmHg vs. 74.9±0.6 mmHg, p=0.012), but not among NH Whites (70.4±0.4 mmHg vs. 72.9±1.3 mmHg, p=0.075). These effects were largely attributable to BP changes among those with hypertension (pre-election: 414 NH Whites, 350 NH Blacks, 60 Mexican Americans; post-election: 330 NH Whites, 298 NH Blacks, 156 Mexican Americans), in whom there was an increase in SBP among NH Blacks (138.8±1.3 mmHg vs. 143.7±1.7 mmHg, p=0.032) and Mexican Americans (133.9±1.1 mmHg vs. 141.9±1.5 mmHg, p=0.0002); and an increase in DBP among NH Blacks (76.2±1.2 mmHg vs. 80.8±0.9 mmHg, p=0.005). No significant changes were observed in any racial/ethnic group without hypertension. Conclusions: At the population-level, NH Blacks and Mexican Americans had increases in BP following the 2016 U.S. general election, largely driven by BP elevations among those with hypertension. Patient-level data, especially linked with political affiliation, may provide additional insights into the psychosocial stress effect of major political events.

scholarly journals Diagnostic value of self-report compared with Beck Depression Inventory (BDI-II) in screening of depression

2020 ◽  
Author(s):  
Mehran zarghami ◽  
Fatemeh Taghizadeh ◽  
Mahmood mousazadeh
Keyword(s):  
Positive Predictive Value ◽  
Beck Depression Inventory ◽  
Predictive Value ◽  
Total Population ◽  
False Negative ◽  
Diagnostic Value ◽  
Self Report ◽  
Case Group ◽  
Predictive Values ◽  
Sensitivity Specificity

AbstractBackgroundDepression is a common cause of mortality and morbidity worldwide. To detect depression, we compared Beck Depression Inventory scoring as a valid tool with participants self-reporting depression.MethodologyThis cross-sectional study aimed to explore the diagnostic values of self-reporting in patients’ with depression comparing to Beck Depression Inventory scoring in Mazandaran Persian cohort study, with a total of 1300 samples. The sample size was determined to include 155 participants through the census method. In order to increase the test power, 310 healthy participants were included in the study through random selection. In order to evaluate the diagnostic value of self-reporting, BDI-II was completed by blind interviewing to the case group as well as to another group who reported that they were not depressed, as control.ResultsSensitivity, specificity, accuracy, false positive, false negative, positive and negative predictive values of self-reporting was calculated 58.4%, 79.1%,73.4%, 20.8%, 41.6%, 51.8%, and 83.2% for the total population respectively, as well as, sensitivity, specificity, accuracy, positive and negative predictive values of self-report in males were 83.3%, 77.2%, 77.1%, 43.8% and 95.6% and 53.7%, 78.1%, 71.2%, 49.2%, and 81.1% for females, respectively.ConclusionThe positive predictive value and sensitivity of self-reporting are insufficient in total population and females, and therefore self-reporting cannot detect depressed patients, but regarding to its average positive predictive value, perhaps, it can be used to identify non-depressant individuals.

scholarly journals Surveillance of atypical femoral fractures in a nationwide fracture register

2022 ◽  
Vol 93 ◽  
pp. 229-233
Author(s):  
Hans Peter Bögl ◽  
Georg Zdolsek ◽  
Lukas Barnisin ◽  
Michael Möller ◽  
Jörg Schilcher
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Gold Standard ◽  
Femoral Fractures ◽  
Study Cohort ◽  
Atypical Femoral Fractures ◽  
User Classification ◽  
Radiology Reports ◽  
Fracture Register ◽  
Standard Classification

Background and purpose — To continuously assess the incidence of atypical femoral fractures (AFFs) in the population is important, to allow the evaluation of the risks and benefits associated with osteoporosis treatment. Therefore, we investigated the possibility to use the Swedish Fracture Register (SFR) as a surveillance tool for AFFs in the population and to explore means of improvement. Patients and methods — All AFF registrations in the SFR from January 1, 2015 to December 31, 2018 were enrolled in the study. For these patients, radiographs were obtained and combined with radiographs from 176 patients with normal femoral fractures, to form the study cohort. All images were reviewed and classified into AFFs or normal femur fractures by 2 experts in the field (gold-standard classification) and 1 orthopedic resident educated on the specific radiographic features of AFF (educated-user classification). Furthermore, we estimated the incidence rate of AFFs in the population captured by the register through comparison with a previous cohort and calculated the positive predictive value (PPV) and, where possible, the inter-observer agreement (Cohen’s kappa) between the different classifications. Results — Of the 178 available patients with AFF in the SFR, 104 patients were classified as AFF using the goldstandard classification, and 89 using the educated-user classification. The PPV increased from 0.58 in the SFR classification to 0.93 in the educated-user classification. The interobserver agreement between the gold-standard classification and the educated-user classification was 0.81. Interpretation — With a positive predictive value of 0.58 the Swedish Fracture Register outperforms radiology reports and reports to the Swedish Medical Products Agency on adverse drug reactions as a diagnostic tool to identify atypical femoral fractures.

scholarly journals Hepatitis C Virus (HCV) diagnosis, epidemiology and access to treatment in a UK cohort

2017 ◽  
Author(s):  
Emily Adland ◽  
Gerald Jesuthasan ◽  
Louise Downs ◽  
Victoria Wharton ◽  
Gemma Wilde ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Viral Load ◽  
Hepatitis C ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Clinical Care ◽  
Virologic Response ◽  
Hcv Infection ◽  
Hcv Rna ◽  
Direct Acting Antiviral

ABSTRACTBackgroundAs direct acting antiviral (DAA) therapy is progressively rolled out for patients with hepatitis C virus (HCV) infection, careful scrutiny of HCV epidemiology, diagnostic testing, and access to care is crucial to underpin improvements in delivery of treatment.MethodsWe performed a retrospective study of HCV infection in a UK teaching hospital to evaluate the performance of different diagnostic laboratory tests, to describe the population with active HCV infection, and to determine the proportion of these individuals who access clinical care.ResultsOver a total time period of 33 months between 2013 and 2016, we tested 38,510 individuals for HCV infection and confirmed a new diagnosis of active HCV infection (HCV-Ag+ and/or HCV RNA+) in 359 (positive rate 0.9%). Our in-house HCV-Ab test had a positive predictive value of 87% when compared to repeat HCV-Ab testing in a regional reference laboratory, highlighting the potential for false positives to arise based on a single round of antibody-based screening. Of those confirmed Ab-positive, 70% were HCV RNA positive. HCV-Ag screening performed well, with 100% positive predictive value compared to detection of HCV RNA. There was a strong correlation between quantitative HCV-Ag and HCV RNA viral load (p<0.0001). Among the 359 cases of infection, the median age was 37 years, 85% were male, and 36% were in prison. Among 250 infections for which genotype was available, HCV genotype-1 (n=110) and genotype-3 (n=111) accounted for the majority. 117/359 (33%) attended a clinic appointment and 48 (13%) had curative treatment defined as sustained virologic response at 12 weeks (SVR12).ConclusionsHCV-Ab tests should be interpreted with caution as an indicator of population prevalence of HCV infection, both as a result of the detection of individuals who have cleared infection and due to false positive test results. We demonstrate that active HCV infection is over-represented among men and in the prison population. A minority of patients with a diagnosis of HCV infection access clinical care and therapy; enhanced efforts are required to target diagnosis and providing linkage to clinical care within high risk populations.ABBREVIATIONSDAADirect Acting AntiviralELISAEnzyme linked immunosorbent assayHCVHepatitis C VirusHCV-AbIgG antibody to Hepatitis C virusHCV-AgHepatitis C virus core antigenHCV RNAHepatitis C ribonucleic acid (viral load)MSMmen who have sex with menNATnucleic acid testingPCRpolymerase chain reaction (test for viral load)PPVpositive predictive valuePWIDpeople who inject drugsSDGSustainable Development GoalsSVRsustained virologic responseWHOWorld Health Organisation

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