Case Reports, Case Series, Ecologic Studies

Study Designs Overview

  • Case Reports & Case Series

  • Ecologic Studies

  • M SCHOOL OF PUBLIC HEALTH

  • UNIVERSITY OF MICHIGAN

Study Design Overview

  • Descriptive Studies

    • Function: Describes phenomena

    • Limitations: Does not examine relationships

  • Analytic Studies

    • Function: Examines relationships

    • Function: Tests hypotheses

Types of Descriptive Studies

  • Surveillance Data

  • Surveys

  • Case Reports

  • Case Series

Descriptive Studies Questions

  • WHO?

  • WHEN?

  • WHERE?

  • WHAT?

  • HOW?

Public Health Surveillance

  • Definition: Monitoring public health situations

  • Description:

    • Ongoing

    • Systematic collection, analysis, and interpretation of health-related data

    • Essential for planning, implementation, and evaluation of public health practice

    • Closely integrated with timely dissemination of data to those responsible for prevention and control

  • Key Elements:

    • Systematic

    • Ongoing

    • Collection

    • Analysis

    • Interpretation

    • Dissemination

    • Health Related Data

    • Linked to Public Health Practice

    • Prevention and Control

  • Source: Centers for Disease Control and Prevention (CDC). Introduction to Public Health. In: Public Health 101 Series. Atlanta, GA: U.S. Department of Health and Human Services, CDC; 2014.

Descriptive: Case Report/Series Key Elements

  • Unexpected event while treating disease

  • Unreported or unusual side effects or adverse interactions

  • Presentation of new or emerging disease

  • Unexpected association between diseases or symptoms

  • Findings that shed new light on the possible pathogenesis of a disease

  • Source: Journal of Medical Case Reports

Case Report Example – May 2020

  • Disease: Novel coronavirus 2019 (COVID-19)

  • Abstract:

    • Rationale: COVID-19 (severe acute respiratory syndrome coronavirus 2 - SARS-CoV-2) is an enveloped, non-segmented positive-sense RNA virus belonging to the beta-coronaviridae family. This virus is known to cause severe bilateral pneumonia and acute respiratory distress syndrome (ARDS), which can lead to difficulty breathing requiring mechanical ventilation and intensive care unit management.

    • Patient Concerns: A 77-year-old female with a history of hypertension and hyperlipidemia presented as a transfer to a hospital facility with worsening fevers, cough, and respiratory distress.

    • Diagnosis: Chest X-rays revealed bilateral infiltrates worse at the lung bases; CT scan of the chest showed bilateral ground-glass opacities consistent with COVID-19. Testing revealed a negative COVID-19 result at the current institution but a positive result at a previous hospital.

    • Interventions: Treatment in the intensive care unit included high dose intravenous ascorbic acid, hydroxychloroquine, and anti-interleukin-6 monoclonal antibody. A loading dose of remdesivir was administered but could not be completed due to organ failure and need for vasopressors for hemodynamic stability.

    • Outcomes: The patient remained critically ill, was eventually placed on comfort care per family wishes, and passed away.

    • Lessons: With a rapidly growing death rate exceeding 200,000 confirmed cases worldwide, COVID-19 has become a global pandemic and significantly impacted healthcare systems. While vaccine trials are underway and various medications are utilized to treat the virus and symptomatic cases, no approved medication regiment exists for COVID-19 infections. The increasing daily case rate heightens pressure to find effective treatments to reduce the health burden and mortality rate.

  • Abbreviations:

    • ARDS = acute respiratory distress syndrome

    • CoV = coronavirus

    • COVID-19 = novel coronavirus 2019

    • CWHD = continuous veno-venous hemodialysis

    • ED = emergency department

    • FIO2 = fraction of inspired oxygen

    • ICU = intensive care unit

    • MERS-CoV = Middle East respiratory syndrome coronavirus

    • PCR = polymerase chain reaction

    • PEEP = positive end-expiratory pressure

    • RSV = Respiratory syncytial virus

    • SARS-CoV = severe acute respiratory syndrome coronavirus

    • SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2

Case Series Example – Surma (Kohl) - NYC

  • Incidence: High blood lead level (BLL) identified in 4-year-old child (asymptomatic) in September 2012

  • Follow-up Actions:

    • Home/environment inspection yielded no findings.

    • Interview identified surma (a type of cosmetic) use, but the sample could not be tested; advised to discontinue use.

    • Follow-up conducted 4 months later with no change in BLL.

  • Testing Protocol:

    • NYC Department of Health and Mental Hygiene conducts routine BLL testing; upon identification of cases, conducts risk assessment questionnaires and environmental sampling.

Case Series Data – Surma Analysis

  • Element Names:

    • Kohl Sample Testing Results (Lead Concentration in ppm):

    • #1: 94.31

    • #2: 122,848.82

    • #3: 376.36

    • #4: 7.78

    • #5: 2.83

    • #6: 410,806.98

    • #7: 156.05

    • #8: 11.78

    • #9: 7.80

    • #10: 1.73

    • #11: 2.159

    • #12: 205,540.73

  • EU Limits: 20

  • BVL Limits: 2

  • Data Source: Int. J. Environ. Res. Public Health 2021, 18, 6109. https://doi.org/10.3390/ijerph18116109

Surma Case Series Continued Findings

  • Follow-up Findings:

    • 9 months later, a sibling (15 months old) and the mother (now pregnant) tested. Surma identified with 390,000 ppm of lead.

    • 2.5 years later, the family was tested again; BLL remained high in children, with the youngest child having the highest levels. Strong recommendations made to discontinue use of surma.

Data Visualization – Blood Lead Levels

  • Figure 1: Blood lead levels of a mother and her four children with a history of surma use.

    • Timeframe depicted: Sep 2012 to Mar 2023

    • Critical indicators in blood lead level changes over time.

Case Reports/Series Importance

  • Quote: "Case reports and case series may be the 'lowest' or the 'weakest' level of evidence, but they often remain the 'first line of evidence.' This is where everything begins" - Milos Jenicek, Clinical Case Reporting in Evidence-Based Medicine

Analytic Studies Overview

  • Definition: Examine relationships and test hypotheses

  • Components:

    • Exposure: Associated with

    • Outcome:

Hypothesis Development

  • Key Components when stating a hypothesis:

    • State the relationship between exposure and outcome

    • Magnitude - how significant the relationship is

    • Direction - whether it is positive or negative

  • Example: Increased physical activity is associated with a 20% reduction in cardiovascular disease risk.

  • Hypotheses must be:

    • Clear

    • Limited in scope

    • Consistent with known facts

    • Supported by literature, theory, references

    • Testable

Ecologic Studies Overview

  • Definition: Group-level data used to explore exposure-outcome relationships

    • Groups can vary based on:

    • Place

    • Time

    • Both place and time

  • Key Considerations: Both exposure and outcome measured in aggregate form

Types of Ecologic Measures

  • Aggregate Measures can be:

    • Group-level descriptive data of individuals (i.e., means, proportions)

    • Environmental measures (i.e., pollution, green space, etc.)

    • Global measures that are group-level and cannot be reduced to individual characteristics (i.e., policies, health inequality, laws)

  • Common Characteristics: Most ecologic studies relate exposure and outcomes measured at a single point in time or can include lag time.

Examples of Ecologic Studies

  • GDP per capita and life expectancy

  • Infant mortality and CHD mortality

  • Chocolate intake and Nobel laureates

  • Unemployment rates and traffic deaths

  • Colombian homicide rates and age of menarche

Ecologic Studies: Limitations

  • Concerning Issues:

    • Individuals from whom outcome information is collected may differ from those from whom exposure information is collected.

    • Within groups, the probability of outcome conditional on exposure status is often unavailable, leading to potential aggregation bias (ecologic fallacy).

  • Ecologic Fallacy Defined: Bias that can occur because an association between variables at an aggregate level may not represent the association at the individual level.

Aggregation Bias/Ecologic Fallacy Example

  • Context: Association between high meat intake and colon cancer

  • Data Interpretation Questions:

    • What would findings be based upon available data and presented figures?

Strengths of Ecologic Studies

  • Key Advantages:

    • Some variables can only be defined at the group level

    • Hypotheses can be generated based on group-level differences

    • Cost-effective and straightforward to conduct

Hierarchy of Study Designs

  • Establish Causality:

    • Randomized Trials

    • Cohort Studies

    • Case-Control Studies

    • Cross-Sectional Studies

  • Descriptive Studies: Good for generating hypotheses

  • Ecologic Studies: Useful as a starting point to investigate research questions