Surgery, anesthesiology, and emergency and critical care medicine

The Biostatistics Clinic on Wednesdays is dedicated to biostatistics applications in surgery, anesthesiology, and emergency and critical care medicine.

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Current Notes (2024)

2024 March 6

Eesha Singh (Jillian Berkman), Neurology

Moyamoya vasculopathy (MMV) is a disease of the intracranial arteries leading to narrowing and occlusion. This contributes to increased stroke risk, with most patients being diagnosed with MMV after they have had a stroke.
MMV can occur in the setting of genetic predisposition, Moyamoya disease (MMD), or vascular remodeling secondary to another pathologic process, Moyamoya Syndrome (MMS). In the United States, MMS often occurs
concurrently with uncontrolled stroke risk factors such as hypertension, diabetes, or smoking.

The mainstay of treatment remains bypass surgery, with lack of significant data regarding medical management of MMS in the US. While there are some anecdotal or case series-based data, there is little to no representative data
examining the management of MMS patients, especially in the context of socioeconomic factors.

Social determinants of health contribute to risk factors that can increase risk for MMS and lead to poor management and outcomes. Anecdotally, patients with uncontrolled vascular risk factors and subsequent atherosclerosis do not reliably receive appropriate monitoring or treatment. We aim to assess the treatment and interventions that adult patients with symptomatic MMS in the Stroke Belt are offered and receive.

The severe limitation that sparse data and lack of guidelines in this population imposes on clinical practice requires that more studies and reviews to identify the unique risk factors contributing to MMS. We hope to evaluate the impact of individual as well as population-level social determinants, outlined below, on MMS management, both medical and surgical.

Meeting Notes:
  • Main research question: How do SDOH affect clinical outcomes and management in Moyamoya disease?
Recommendations:
  • Clearly define outcomes (clinical and management)
    • Clarify the time frame for follow up
  • Consider any potential confounders
  • Include medical history (ex. history of diabetes, history of hypertension, medications, etc.)
  • Can consider a time-to-event analysis or logistic regression (primary outcome = recurrent stroke)
  • Recommended to apply for a VICTR voucher

Andrew James (Patrick Assi), Plastic Surgery

We are looking to have a statistician review our statistical strategy for an upcoming publication and provide insight into additional considerations we may need to take into account.

Meeting Notes:
  • Hypothesis: Exposure to testosterone does not increase the incidence of pathology
    • 80% of cohort are using hormone therapy

Recommendations:
  • Stratify Table 1 by testosterone (yes/no)
    • Include an overall column
    • Include demographics, medical history, pathology results
    • Chi-squared tests (include p-value)
      • This is fine for an unadjusted analysis (but does not take order of pathology severity into account)
  • Can collapse some of the levels for pathology with small cell counts
  • In Table 2, include subjects with benign pathology, so the total adds up to the full cohort
  • Use Fisher’s exact when cell counts are less than 5

2024 January 31

Kevin Johnson, Pediatric Surgery

Our project utilizes a large database doing a time-to-event analysis on neurologic complications in ECMO patients. Our question is whether there is a statistical analysis that we can do to compare the risk of a neurologic complication when splitting the analysis around a time point (currently have Kaplan Meier curves).

Meeting Notes:
  • If there is an established collaboration plan with the biostatistics department, this might be the best place to go (Dandan to make this connection)
  • Otherwise, can apply for a VICTR voucher

Recommendations:
  • Look at cumulative incidence plots to help identify what timeframe to look at
  • Eventually will want to run a proportional hazards model, to include all potential risk factors in one model
    • Large event rate \x{2013} should not have a problem fitting everything in the model

2024 January 24

Kevin Johnson, Pediatric Surgery - No Show

Our project utilizes a large database doing a time-to-event analysis on neurologic complications in ECMO patients. Our question is whether there is a statistical analysis that we can do to compare the risk of a neurologic complication when splitting the analysis around a time point (currently have Kaplan Meier curves).

2024 January 17

Kristina Betters, Pediatrics Critical Care

We are implementing a diary for caregivers and patients to use in the PICU and would like to assess whether the diary is effective in helping patients and caregivers cope and reduce anxiety, stress and trauma related to hospitalization.

Meeting Notes:
  • Discussed specific comments from the VICTR application and ways to address them

Recommendations:
  • If considering a control group, a 2:1 ratio could work
  • Will want to consider using Wilcoxon tests (or other non-parametric tests), since data is likely not normal
Topic revision: r912 - 07 Mar 2024, CassieHennessy
 

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