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Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies01:22

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The key clinical manifestations of Rheumatic heart disease (RHD) include several distinct cardiac symptoms.Carditis, a hallmark of acute rheumatic fever, involves inflammation of the heart's endocardium, myocardium, and pericardium. Chronic RHD often results from recurrent episodes of carditis. Its symptoms include the following:Murmurs are caused by valvular damage, especially to the mitral and aortic valves. Mitral stenosis or regurgitation is common, with characteristic heart murmurs...
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Rheumatic Heart Disease I: Introduction01:23

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Rheumatic heart disease or RHD is a chronic condition that results from rheumatic fever, causing permanent damage to the heart valves.Etiology and Risk FactorsIt primarily arises from rheumatic fever, an inflammatory disease that can develop after untreated or inadequately treated group A streptococcal (GAS) pharyngitis. Streptococcus spreads through direct contact with oral or respiratory secretions. While the bacteria are the causative agents, factors like malnutrition, overcrowding, poor...
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Rheumatic heart disease (RHD) management can be divided into two main strategies: prevention and long-term management.Primary PreventionPrimary prevention focuses on timely diagnosis and management of group A streptococcal pharyngitis to prevent acute rheumatic fever. The most widely used antibiotic for treating this condition is intramuscular benzathine penicillin G.Acute Rheumatic Fever TreatmentThe primary treatment goal for a patient diagnosed with acute rheumatic fever is to suppress the...
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AssessmentA comprehensive assessment is essential in managing a patient with rheumatic heart disease (RHD). Begin with obtaining a detailed medical history, including recent streptococcal infections, a history of rheumatic fever, or previously diagnosed rheumatic heart disease. Assess the patient for symptoms such as fever, chest pain, widespread joint pain (arthralgia), tachycardia, pericardial friction rub, muffled heart sounds, heart murmurs, peripheral edema, subcutaneous nodules, and...
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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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Estimating the likely true changes in rheumatic fever incidence using two data sources.

J Oliver1, N Pierse1, D A Williamson2

  • 1Department of Public Health,University of Otago Wellington,Wellington,New Zealand.

Epidemiology and Infection
|December 7, 2017
PubMed
Summary

Acute rheumatic fever (ARF) incidence in New Zealand has declined, but surveillance data limitations persist. Capture-recapture analysis estimated 2342 cases from 1997-2015, with a 44% drop in 2015 incidence.

Keywords:
Health equityincidencepublic healthrheumatic feversurveillance system

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Area of Science:

  • Public Health
  • Epidemiology
  • Infectious Disease Surveillance

Background:

  • Acute rheumatic fever (ARF) disproportionately affects Māori and Pacific peoples in New Zealand.
  • Existing national surveillance data for ARF is insufficient for accurate case counting.
  • Changes in ARF epidemiology and a national prevention program necessitate updated incidence estimates.

Purpose of the Study:

  • To estimate the true incidence of ARF in New Zealand using capture-recapture methods.
  • To assess the impact of the national rheumatic fever prevention program on ARF incidence.
  • To evaluate the evolving completeness and detectability of ARF cases.

Main Methods:

  • Utilized capture-recapture analysis on national hospitalization and notification databases.
  • Employed the Chapman Estimate to adjust for bias in case detection.
  • Analyzed data spanning from 1997 to 2015, with a focus on the 2012-2015 prevention program period.

Main Results:

  • An estimated 2342 likely true new ARF cases occurred between 1997 and 2015, yielding a mean annual incidence of 2.9 per 100,000.
  • Likely true ARF incidence in 2015 showed a significant decline of 44% compared to the 2009-2011 baseline.
  • Data completeness improved, with 83.8% notification-hospitalization and 87.2% hospitalization-notification matches during 2012-2015.

Conclusions:

  • Despite a 44% decline in ARF incidence, ongoing surveillance improvements are needed.
  • Clinicians must remain vigilant for atypical ARF presentations and ensure proper notification.
  • The national prevention program may have inadvertently led to increased misdiagnosis of ARF.