update project design
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/.quarto/
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**/*.quarto_ipynb
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@@ -1,6 +1,8 @@
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---
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title: "Target Trial Basics: Early Vasopressors in Septic Shock"
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format: html
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format:
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html:
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embed-resources: true
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execute:
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echo: true
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warning: false
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@@ -18,18 +20,20 @@ The clinical question is:
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## Setup
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```{r}
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library(dplyr)
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library(gt)
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library(gtsummary)
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library(readr)
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library(skimr)
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library(tibble)
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# library() attaches a package so its functions are available by name.
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# suppressPackageStartupMessages() keeps package startup text out of the report.
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suppressPackageStartupMessages({
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library(dplyr)
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library(gt)
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library(gtsummary)
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library(tibble)
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})
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# source() loads reusable project functions from the R/ folder.
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source("../R/simulate_icu_cohort.R")
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source("../R/estimate_naive_vasopressor_mortality_effect.R")
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```
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These packages make the routine analysis code easier to read.
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`dplyr` handles data manipulation, `readr` reads rectangular files, `skimr` gives quick data summaries, `gt` builds display tables, and `gtsummary` builds analytic summary tables.
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## Why A Target Trial?
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Observational ICU data are not randomized.
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@@ -41,14 +45,25 @@ The target trial framework asks us to describe the randomized trial we wish we h
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## Target Trial Protocol
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```{r}
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target_trial_protocol <- tribble(
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~component, ~definition,
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"Eligibility criteria", "ICU admission, suspected sepsis, hypotension, elevated lactate",
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"Time zero", "ICU admission",
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"Treatment strategy 1", "Start vasopressors within 2 hours",
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"Treatment strategy 2", "Do not start vasopressors within 2 hours",
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"Outcome", "Death within 28 days",
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"Causal contrast", "Risk difference and risk ratio"
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# tibble() creates a small rectangular dataset.
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# Each named argument becomes one column.
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target_trial_protocol <- tibble(
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component = c(
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"Eligibility criteria",
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"Time zero",
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"Treatment strategy 1",
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"Treatment strategy 2",
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"Outcome",
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"Estimand"
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),
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definition = c(
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"ICU admission, suspected sepsis, hypotension, elevated lactate",
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"ICU admission",
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"Start vasopressors within 2 hours",
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"Do not start vasopressors within 2 hours",
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"Death within 28 days",
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"Risk difference and risk ratio"
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)
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)
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target_trial_protocol |>
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@@ -60,112 +75,73 @@ target_trial_protocol |>
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)
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```
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`tribble()` creates a small tibble by typing the rows directly.
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## Simulate The Cohort
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`gt()` turns that tibble into a clearer presentation table.
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For this report, we call the reusable simulation function directly.
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## Load The Simulated Cohort
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This first version uses a CSV generated by `scripts/01_simulate_icu_data_base_r.R`.
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Using the same seed gives the same simulated cohort each time the notebook renders.
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```{r}
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icu_data <- read_csv("../data/icu_septic_shock_base_r.csv", show_col_types = FALSE)
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icu_data <- simulate_icu_cohort(n_patients = 1000, seed = 20260531)
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naive_mortality_analysis <- estimate_naive_vasopressor_mortality_effect(icu_data)
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eligible_icu_patients <- naive_mortality_analysis$eligible_icu_patients
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```
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`read_csv()` reads a rectangular CSV file into R.
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The object `icu_data` is a tibble, where each row is one ICU patient.
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## Inspect The Data
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## Cohort Overview
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```{r}
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icu_data |>
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slice_head(n = 6)
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```
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`slice_head()` prints the first few rows so we can inspect the structure before analyzing anything.
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```{r}
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skim(icu_data)
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```
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`skim()` gives a quick summary of variable types, missingness, and distributions.
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## Apply Eligibility Criteria
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```{r}
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eligible_data <- icu_data |>
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filter(eligible == 1)
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```
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`filter()` keeps rows that satisfy a condition.
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Here, we keep only patients who satisfy the simulated eligibility criteria.
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## Count Treatment Groups
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```{r}
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eligible_data |>
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count(early_vasopressor)
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```
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`count()` counts how many eligible patients were observed under each treatment group.
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In this first simplified dataset:
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- `1` means vasopressors started within 2 hours.
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- `0` means vasopressors were not started within 2 hours.
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## Estimate Naive Mortality Risks
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```{r}
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naive_risks <- eligible_data |>
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group_by(early_vasopressor) |>
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summarize(
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n_patients = n(),
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risk_death_28d = mean(death_28d),
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.groups = "drop"
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)
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naive_risks |>
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gt() |>
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tab_header(title = "Naive 28-Day Mortality Risk") |>
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cols_label(
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early_vasopressor = "Early vasopressor",
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n_patients = "Patients",
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risk_death_28d = "28-day mortality risk"
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) |>
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fmt_number(columns = risk_death_28d, decimals = 3)
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```
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Because `death_28d` is coded as 0 or 1, its mean is the proportion who died.
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This is a naive comparison because it does not yet adjust for the fact that treatment decisions depend on patient severity.
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## Estimate Naive Contrasts
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```{r}
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risk_early <- naive_risks |>
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filter(early_vasopressor == 1) |>
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pull(risk_death_28d)
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risk_not_early <- naive_risks |>
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filter(early_vasopressor == 0) |>
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pull(risk_death_28d)
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naive_contrasts <- tibble(
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measure = c("Risk difference", "Risk ratio"),
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# These summary counts describe how the full simulated cohort maps onto the
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# eligible target-trial cohort.
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cohort_overview <- tibble(
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measure = c(
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"Simulated ICU patients",
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"Eligible patients",
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"Early vasopressor patients",
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"Not early vasopressor patients"
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),
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value = c(
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risk_early - risk_not_early,
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risk_early / risk_not_early
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nrow(icu_data),
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nrow(eligible_icu_patients),
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sum(eligible_icu_patients$early_vasopressor == 1),
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sum(eligible_icu_patients$early_vasopressor == 0)
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)
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)
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naive_contrasts |>
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cohort_overview |>
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gt() |>
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tab_header(title = "Naive Treatment Contrast") |>
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tab_header(title = "Cohort Overview") |>
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cols_label(
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measure = "Measure",
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value = "Patients"
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) |>
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fmt_integer(columns = value)
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```
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## Naive Mortality Risk
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```{r}
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naive_mortality_analysis$mortality_risks_by_early_vasopressor |>
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gt() |>
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tab_header(title = "Naive 28-Day Mortality Risk") |>
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cols_label(
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observed_treatment_group = "Observed treatment group",
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patient_count = "Patients",
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mortality_risk_28d = "28-day mortality risk"
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) |>
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fmt_integer(columns = patient_count) |>
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fmt_number(columns = mortality_risk_28d, decimals = 3)
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```
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This is a naive comparison because it does not yet adjust for the fact that treatment decisions depend on patient severity.
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## Naive Mortality Effect Estimates
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```{r}
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naive_mortality_analysis$mortality_effect_estimates |>
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gt() |>
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tab_header(title = "Naive Mortality Effect Estimates") |>
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cols_label(
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estimate = "Estimate",
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value = "Value"
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) |>
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fmt_number(columns = value, decimals = 3)
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@@ -175,10 +151,10 @@ The risk difference is an absolute difference in 28-day mortality risk.
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The risk ratio is a relative comparison of 28-day mortality risk.
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## Check Confounding By Severity
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## Baseline Severity By Treatment Group
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```{r}
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eligible_data |>
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eligible_icu_patients |>
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mutate(
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early_vasopressor = factor(
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early_vasopressor,
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@@ -198,14 +174,12 @@ eligible_data |>
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add_overall()
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```
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This compares baseline severity between the two treatment groups.
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Early vasopressor patients are generally sicker at baseline in this simulated observational cohort.
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If early vasopressor patients have higher SOFA scores, higher lactate, or lower MAP, then the naive comparison mixes the treatment effect with baseline severity differences.
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That problem is one reason we need target trial emulation methods rather than a simple treated-versus-untreated comparison.
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That means the naive comparison mixes the effect of treatment with baseline severity differences, which is why we need target trial emulation methods rather than a simple treated-versus-untreated comparison.
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## Next Step
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The next lesson should walk through `R/simulate_icu_cohort.R` line by line.
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After that, we can use `scripts/02_naive_analysis_base_r.R` to compute the first naive association and then discuss why it is not yet a causal estimate.
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After that, we can extend the notebooks to show why the naive mortality effect estimates are biased and start building adjusted analyses in reusable `R/` functions.
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-12
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/* quarto syntax highlight colors */
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:root {
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--quarto-hl-ot-color: #003B4F;
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--quarto-hl-at-color: #657422;
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--quarto-hl-ss-color: #20794D;
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--quarto-hl-cn-color: #8f5902;
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--quarto-hl-sc-color: #5E5E5E;
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--quarto-hl-dv-color: #AD0000;
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--quarto-hl-kw-color: #003B4F;
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}
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/* other quarto variables */
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:root {
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--quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
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}
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/* syntax highlight based on Pandoc's rules */
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pre > code.sourceCode > span {
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color: #003B4F;
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}
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code.sourceCode > span {
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color: #003B4F;
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}
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div.sourceCode,
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div.sourceCode pre.sourceCode {
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color: #003B4F;
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}
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/* Normal */
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code span {
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color: #003B4F;
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code span.al {
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||||
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||||
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||||
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||||
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||||
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||||
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|
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||||
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||||
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||||
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||||
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|
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|
||||
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||||
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|
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|
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}
|
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|
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/*# sourceMappingURL=789ad8cd35626ba772517505b42a116e.css.map */
|
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@@ -1,845 +0,0 @@
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import * as tabsets from "./tabsets/tabsets.js";
|
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|
||||
const sectionChanged = new CustomEvent("quarto-sectionChanged", {
|
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|
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|
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|
||||
const layoutMarginEls = () => {
|
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||||
// top to prevent overlap
|
||||
const marginChildren = window.document.querySelectorAll(
|
||||
".column-margin.column-container > *, .margin-caption, .aside"
|
||||
);
|
||||
|
||||
let lastBottom = 0;
|
||||
for (const marginChild of marginChildren) {
|
||||
if (marginChild.offsetParent !== null) {
|
||||
// clear the top margin so we recompute it
|
||||
marginChild.style.marginTop = null;
|
||||
const top = marginChild.getBoundingClientRect().top + window.scrollY;
|
||||
if (top < lastBottom) {
|
||||
const marginChildStyle = window.getComputedStyle(marginChild);
|
||||
const marginBottom = parseFloat(marginChildStyle["marginBottom"]);
|
||||
const margin = lastBottom - top + marginBottom;
|
||||
marginChild.style.marginTop = `${margin}px`;
|
||||
}
|
||||
const styles = window.getComputedStyle(marginChild);
|
||||
const marginTop = parseFloat(styles["marginTop"]);
|
||||
lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
window.document.addEventListener("DOMContentLoaded", function (_event) {
|
||||
// Recompute the position of margin elements anytime the body size changes
|
||||
if (window.ResizeObserver) {
|
||||
const resizeObserver = new window.ResizeObserver(
|
||||
throttle(() => {
|
||||
layoutMarginEls();
|
||||
if (
|
||||
window.document.body.getBoundingClientRect().width < 990 &&
|
||||
isReaderMode()
|
||||
) {
|
||||
quartoToggleReader();
|
||||
}
|
||||
}, 50)
|
||||
);
|
||||
resizeObserver.observe(window.document.body);
|
||||
}
|
||||
|
||||
const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]');
|
||||
const sidebarEl = window.document.getElementById("quarto-sidebar");
|
||||
const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left");
|
||||
const marginSidebarEl = window.document.getElementById(
|
||||
"quarto-margin-sidebar"
|
||||
);
|
||||
// function to determine whether the element has a previous sibling that is active
|
||||
const prevSiblingIsActiveLink = (el) => {
|
||||
const sibling = el.previousElementSibling;
|
||||
if (sibling && sibling.tagName === "A") {
|
||||
return sibling.classList.contains("active");
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
};
|
||||
|
||||
// dispatch for htmlwidgets
|
||||
// they use slideenter event to trigger resize
|
||||
function fireSlideEnter() {
|
||||
const event = window.document.createEvent("Event");
|
||||
event.initEvent("slideenter", true, true);
|
||||
window.document.dispatchEvent(event);
|
||||
}
|
||||
|
||||
const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]');
|
||||
tabs.forEach((tab) => {
|
||||
tab.addEventListener("shown.bs.tab", fireSlideEnter);
|
||||
});
|
||||
|
||||
// dispatch for shiny
|
||||
// they use BS shown and hidden events to trigger rendering
|
||||
function distpatchShinyEvents(previous, current) {
|
||||
if (window.jQuery) {
|
||||
if (previous) {
|
||||
window.jQuery(previous).trigger("hidden");
|
||||
}
|
||||
if (current) {
|
||||
window.jQuery(current).trigger("shown");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// tabby.js listener: Trigger event for htmlwidget and shiny
|
||||
document.addEventListener(
|
||||
"tabby",
|
||||
function (event) {
|
||||
fireSlideEnter();
|
||||
distpatchShinyEvents(event.detail.previousTab, event.detail.tab);
|
||||
},
|
||||
false
|
||||
);
|
||||
|
||||
// Track scrolling and mark TOC links as active
|
||||
// get table of contents and sidebar (bail if we don't have at least one)
|
||||
const tocLinks = tocEl
|
||||
? [...tocEl.querySelectorAll("a[data-scroll-target]")]
|
||||
: [];
|
||||
const makeActive = (link) => tocLinks[link].classList.add("active");
|
||||
const removeActive = (link) => tocLinks[link].classList.remove("active");
|
||||
const removeAllActive = () =>
|
||||
[...Array(tocLinks.length).keys()].forEach((link) => removeActive(link));
|
||||
|
||||
// activate the anchor for a section associated with this TOC entry
|
||||
tocLinks.forEach((link) => {
|
||||
link.addEventListener("click", () => {
|
||||
if (link.href.indexOf("#") !== -1) {
|
||||
const anchor = link.href.split("#")[1];
|
||||
const heading = window.document.querySelector(
|
||||
`[data-anchor-id="${anchor}"]`
|
||||
);
|
||||
if (heading) {
|
||||
// Add the class
|
||||
heading.classList.add("reveal-anchorjs-link");
|
||||
|
||||
// function to show the anchor
|
||||
const handleMouseout = () => {
|
||||
heading.classList.remove("reveal-anchorjs-link");
|
||||
heading.removeEventListener("mouseout", handleMouseout);
|
||||
};
|
||||
|
||||
// add a function to clear the anchor when the user mouses out of it
|
||||
heading.addEventListener("mouseout", handleMouseout);
|
||||
}
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
const sections = tocLinks.map((link) => {
|
||||
const target = link.getAttribute("data-scroll-target");
|
||||
if (target.startsWith("#")) {
|
||||
return window.document.getElementById(decodeURI(`${target.slice(1)}`));
|
||||
} else {
|
||||
return window.document.querySelector(decodeURI(`${target}`));
|
||||
}
|
||||
});
|
||||
|
||||
const sectionMargin = 200;
|
||||
let currentActive = 0;
|
||||
// track whether we've initialized state the first time
|
||||
let init = false;
|
||||
|
||||
const updateActiveLink = () => {
|
||||
// The index from bottom to top (e.g. reversed list)
|
||||
let sectionIndex = -1;
|
||||
if (
|
||||
window.innerHeight + window.pageYOffset >=
|
||||
window.document.body.offsetHeight
|
||||
) {
|
||||
// This is the no-scroll case where last section should be the active one
|
||||
sectionIndex = 0;
|
||||
} else {
|
||||
// This finds the last section visible on screen that should be made active
|
||||
sectionIndex = [...sections].reverse().findIndex((section) => {
|
||||
if (section) {
|
||||
return window.pageYOffset >= section.offsetTop - sectionMargin;
|
||||
} else {
|
||||
return false;
|
||||
}
|
||||
});
|
||||
}
|
||||
if (sectionIndex > -1) {
|
||||
const current = sections.length - sectionIndex - 1;
|
||||
if (current !== currentActive) {
|
||||
removeAllActive();
|
||||
currentActive = current;
|
||||
makeActive(current);
|
||||
if (init) {
|
||||
window.dispatchEvent(sectionChanged);
|
||||
}
|
||||
init = true;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const inHiddenRegion = (top, bottom, hiddenRegions) => {
|
||||
for (const region of hiddenRegions) {
|
||||
if (top <= region.bottom && bottom >= region.top) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
return false;
|
||||
};
|
||||
|
||||
const categorySelector = "header.quarto-title-block .quarto-category";
|
||||
const activateCategories = (href) => {
|
||||
// Find any categories
|
||||
// Surround them with a link pointing back to:
|
||||
// #category=Authoring
|
||||
try {
|
||||
const categoryEls = window.document.querySelectorAll(categorySelector);
|
||||
for (const categoryEl of categoryEls) {
|
||||
const categoryText = categoryEl.textContent;
|
||||
if (categoryText) {
|
||||
const link = `${href}#category=${encodeURIComponent(categoryText)}`;
|
||||
const linkEl = window.document.createElement("a");
|
||||
linkEl.setAttribute("href", link);
|
||||
for (const child of categoryEl.childNodes) {
|
||||
linkEl.append(child);
|
||||
}
|
||||
categoryEl.appendChild(linkEl);
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
// Ignore errors
|
||||
}
|
||||
};
|
||||
function hasTitleCategories() {
|
||||
return window.document.querySelector(categorySelector) !== null;
|
||||
}
|
||||
|
||||
function offsetRelativeUrl(url) {
|
||||
const offset = getMeta("quarto:offset");
|
||||
return offset ? offset + url : url;
|
||||
}
|
||||
|
||||
function offsetAbsoluteUrl(url) {
|
||||
const offset = getMeta("quarto:offset");
|
||||
const baseUrl = new URL(offset, window.location);
|
||||
|
||||
const projRelativeUrl = url.replace(baseUrl, "");
|
||||
if (projRelativeUrl.startsWith("/")) {
|
||||
return projRelativeUrl;
|
||||
} else {
|
||||
return "/" + projRelativeUrl;
|
||||
}
|
||||
}
|
||||
|
||||
// read a meta tag value
|
||||
function getMeta(metaName) {
|
||||
const metas = window.document.getElementsByTagName("meta");
|
||||
for (let i = 0; i < metas.length; i++) {
|
||||
if (metas[i].getAttribute("name") === metaName) {
|
||||
return metas[i].getAttribute("content");
|
||||
}
|
||||
}
|
||||
return "";
|
||||
}
|
||||
|
||||
async function findAndActivateCategories() {
|
||||
// Categories search with listing only use path without query
|
||||
const currentPagePath = offsetAbsoluteUrl(
|
||||
window.location.origin + window.location.pathname
|
||||
);
|
||||
const response = await fetch(offsetRelativeUrl("listings.json"));
|
||||
if (response.status == 200) {
|
||||
return response.json().then(function (listingPaths) {
|
||||
const listingHrefs = [];
|
||||
for (const listingPath of listingPaths) {
|
||||
const pathWithoutLeadingSlash = listingPath.listing.substring(1);
|
||||
for (const item of listingPath.items) {
|
||||
const encodedItem = encodeURI(item);
|
||||
if (
|
||||
encodedItem === currentPagePath ||
|
||||
encodedItem === currentPagePath + "index.html"
|
||||
) {
|
||||
// Resolve this path against the offset to be sure
|
||||
// we already are using the correct path to the listing
|
||||
// (this adjusts the listing urls to be rooted against
|
||||
// whatever root the page is actually running against)
|
||||
const relative = offsetRelativeUrl(pathWithoutLeadingSlash);
|
||||
const baseUrl = window.location;
|
||||
const resolvedPath = new URL(relative, baseUrl);
|
||||
listingHrefs.push(resolvedPath.pathname);
|
||||
break;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Look up the tree for a nearby linting and use that if we find one
|
||||
const nearestListing = findNearestParentListing(
|
||||
offsetAbsoluteUrl(window.location.pathname),
|
||||
listingHrefs
|
||||
);
|
||||
if (nearestListing) {
|
||||
activateCategories(nearestListing);
|
||||
} else {
|
||||
// See if the referrer is a listing page for this item
|
||||
const referredRelativePath = offsetAbsoluteUrl(document.referrer);
|
||||
const referrerListing = listingHrefs.find((listingHref) => {
|
||||
const isListingReferrer =
|
||||
listingHref === referredRelativePath ||
|
||||
listingHref === referredRelativePath + "index.html";
|
||||
return isListingReferrer;
|
||||
});
|
||||
|
||||
if (referrerListing) {
|
||||
// Try to use the referrer if possible
|
||||
activateCategories(referrerListing);
|
||||
} else if (listingHrefs.length > 0) {
|
||||
// Otherwise, just fall back to the first listing
|
||||
activateCategories(listingHrefs[0]);
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
if (hasTitleCategories()) {
|
||||
findAndActivateCategories();
|
||||
}
|
||||
|
||||
const findNearestParentListing = (href, listingHrefs) => {
|
||||
if (!href || !listingHrefs) {
|
||||
return undefined;
|
||||
}
|
||||
// Look up the tree for a nearby linting and use that if we find one
|
||||
const relativeParts = href.substring(1).split("/");
|
||||
while (relativeParts.length > 0) {
|
||||
const path = relativeParts.join("/");
|
||||
for (const listingHref of listingHrefs) {
|
||||
if (listingHref.startsWith(path)) {
|
||||
return listingHref;
|
||||
}
|
||||
}
|
||||
relativeParts.pop();
|
||||
}
|
||||
|
||||
return undefined;
|
||||
};
|
||||
|
||||
const manageSidebarVisiblity = (el, placeholderDescriptor) => {
|
||||
let isVisible = true;
|
||||
let elRect;
|
||||
|
||||
return (hiddenRegions) => {
|
||||
if (el === null) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Find the last element of the TOC
|
||||
const lastChildEl = el.lastElementChild;
|
||||
|
||||
if (lastChildEl) {
|
||||
// Converts the sidebar to a menu
|
||||
const convertToMenu = () => {
|
||||
for (const child of el.children) {
|
||||
child.style.opacity = 0;
|
||||
child.style.overflow = "hidden";
|
||||
child.style.pointerEvents = "none";
|
||||
}
|
||||
|
||||
nexttick(() => {
|
||||
const toggleContainer = window.document.createElement("div");
|
||||
toggleContainer.style.width = "100%";
|
||||
toggleContainer.classList.add("zindex-over-content");
|
||||
toggleContainer.classList.add("quarto-sidebar-toggle");
|
||||
toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom
|
||||
toggleContainer.id = placeholderDescriptor.id;
|
||||
toggleContainer.style.position = "fixed";
|
||||
|
||||
const toggleIcon = window.document.createElement("i");
|
||||
toggleIcon.classList.add("quarto-sidebar-toggle-icon");
|
||||
toggleIcon.classList.add("bi");
|
||||
toggleIcon.classList.add("bi-caret-down-fill");
|
||||
|
||||
const toggleTitle = window.document.createElement("div");
|
||||
const titleEl = window.document.body.querySelector(
|
||||
placeholderDescriptor.titleSelector
|
||||
);
|
||||
if (titleEl) {
|
||||
toggleTitle.append(
|
||||
titleEl.textContent || titleEl.innerText,
|
||||
toggleIcon
|
||||
);
|
||||
}
|
||||
toggleTitle.classList.add("zindex-over-content");
|
||||
toggleTitle.classList.add("quarto-sidebar-toggle-title");
|
||||
toggleContainer.append(toggleTitle);
|
||||
|
||||
const toggleContents = window.document.createElement("div");
|
||||
toggleContents.classList = el.classList;
|
||||
toggleContents.classList.add("zindex-over-content");
|
||||
toggleContents.classList.add("quarto-sidebar-toggle-contents");
|
||||
for (const child of el.children) {
|
||||
if (child.id === "toc-title") {
|
||||
continue;
|
||||
}
|
||||
|
||||
const clone = child.cloneNode(true);
|
||||
clone.style.opacity = 1;
|
||||
clone.style.pointerEvents = null;
|
||||
clone.style.display = null;
|
||||
toggleContents.append(clone);
|
||||
}
|
||||
toggleContents.style.height = "0px";
|
||||
const positionToggle = () => {
|
||||
// position the element (top left of parent, same width as parent)
|
||||
if (!elRect) {
|
||||
elRect = el.getBoundingClientRect();
|
||||
}
|
||||
toggleContainer.style.left = `${elRect.left}px`;
|
||||
toggleContainer.style.top = `${elRect.top}px`;
|
||||
toggleContainer.style.width = `${elRect.width}px`;
|
||||
};
|
||||
positionToggle();
|
||||
|
||||
toggleContainer.append(toggleContents);
|
||||
el.parentElement.prepend(toggleContainer);
|
||||
|
||||
// Process clicks
|
||||
let tocShowing = false;
|
||||
// Allow the caller to control whether this is dismissed
|
||||
// when it is clicked (e.g. sidebar navigation supports
|
||||
// opening and closing the nav tree, so don't dismiss on click)
|
||||
const clickEl = placeholderDescriptor.dismissOnClick
|
||||
? toggleContainer
|
||||
: toggleTitle;
|
||||
|
||||
const closeToggle = () => {
|
||||
if (tocShowing) {
|
||||
toggleContainer.classList.remove("expanded");
|
||||
toggleContents.style.height = "0px";
|
||||
tocShowing = false;
|
||||
}
|
||||
};
|
||||
|
||||
// Get rid of any expanded toggle if the user scrolls
|
||||
window.document.addEventListener(
|
||||
"scroll",
|
||||
throttle(() => {
|
||||
closeToggle();
|
||||
}, 50)
|
||||
);
|
||||
|
||||
// Handle positioning of the toggle
|
||||
window.addEventListener(
|
||||
"resize",
|
||||
throttle(() => {
|
||||
elRect = undefined;
|
||||
positionToggle();
|
||||
}, 50)
|
||||
);
|
||||
|
||||
window.addEventListener("quarto-hrChanged", () => {
|
||||
elRect = undefined;
|
||||
});
|
||||
|
||||
// Process the click
|
||||
clickEl.onclick = () => {
|
||||
if (!tocShowing) {
|
||||
toggleContainer.classList.add("expanded");
|
||||
toggleContents.style.height = null;
|
||||
tocShowing = true;
|
||||
} else {
|
||||
closeToggle();
|
||||
}
|
||||
};
|
||||
});
|
||||
};
|
||||
|
||||
// Converts a sidebar from a menu back to a sidebar
|
||||
const convertToSidebar = () => {
|
||||
for (const child of el.children) {
|
||||
child.style.opacity = 1;
|
||||
child.style.overflow = null;
|
||||
child.style.pointerEvents = null;
|
||||
}
|
||||
|
||||
const placeholderEl = window.document.getElementById(
|
||||
placeholderDescriptor.id
|
||||
);
|
||||
if (placeholderEl) {
|
||||
placeholderEl.remove();
|
||||
}
|
||||
|
||||
el.classList.remove("rollup");
|
||||
};
|
||||
|
||||
if (isReaderMode()) {
|
||||
convertToMenu();
|
||||
isVisible = false;
|
||||
} else {
|
||||
// Find the top and bottom o the element that is being managed
|
||||
const elTop = el.offsetTop;
|
||||
const elBottom =
|
||||
elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;
|
||||
|
||||
if (!isVisible) {
|
||||
// If the element is current not visible reveal if there are
|
||||
// no conflicts with overlay regions
|
||||
if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
|
||||
convertToSidebar();
|
||||
isVisible = true;
|
||||
}
|
||||
} else {
|
||||
// If the element is visible, hide it if it conflicts with overlay regions
|
||||
// and insert a placeholder toggle (or if we're in reader mode)
|
||||
if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
|
||||
convertToMenu();
|
||||
isVisible = false;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
};
|
||||
|
||||
const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]');
|
||||
for (const tabEl of tabEls) {
|
||||
const id = tabEl.getAttribute("data-bs-target");
|
||||
if (id) {
|
||||
const columnEl = document.querySelector(
|
||||
`${id} .column-margin, .tabset-margin-content`
|
||||
);
|
||||
if (columnEl)
|
||||
tabEl.addEventListener("shown.bs.tab", function (event) {
|
||||
const el = event.srcElement;
|
||||
if (el) {
|
||||
const visibleCls = `${el.id}-margin-content`;
|
||||
// walk up until we find a parent tabset
|
||||
let panelTabsetEl = el.parentElement;
|
||||
while (panelTabsetEl) {
|
||||
if (panelTabsetEl.classList.contains("panel-tabset")) {
|
||||
break;
|
||||
}
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tocLeftScrollVisibility(
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@@ -1,95 +0,0 @@
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document.querySelectorAll(`div[data-group] a[id^='tabset-']`)
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);
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@@ -1 +0,0 @@
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.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center top}.tippy-box[data-placement^=bottom]>.tippy-arrow{top:0}.tippy-box[data-placement^=bottom]>.tippy-arrow:before{top:-7px;left:0;border-width:0 8px 8px;border-bottom-color:initial;transform-origin:center bottom}.tippy-box[data-placement^=left]>.tippy-arrow{right:0}.tippy-box[data-placement^=left]>.tippy-arrow:before{border-width:8px 0 8px 8px;border-left-color:initial;right:-7px;transform-origin:center left}.tippy-box[data-placement^=right]>.tippy-arrow{left:0}.tippy-box[data-placement^=right]>.tippy-arrow:before{left:-7px;border-width:8px 8px 8px 0;border-right-color:initial;transform-origin:center right}.tippy-box[data-inertia][data-state=visible]{transition-timing-function:cubic-bezier(.54,1.5,.38,1.11)}.tippy-arrow{width:16px;height:16px;color:#333}.tippy-arrow:before{content:"";position:absolute;border-color:transparent;border-style:solid}.tippy-content{position:relative;padding:5px 9px;z-index:1}
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,164 @@
|
||||
---
|
||||
title: "Explore Simulated ICU Data"
|
||||
format:
|
||||
html:
|
||||
embed-resources: true
|
||||
execute:
|
||||
echo: true
|
||||
warning: false
|
||||
message: false
|
||||
---
|
||||
|
||||
## Goal
|
||||
|
||||
This notebook is for exploring the simulated ICU cohort.
|
||||
|
||||
The report notebook focuses on target trial components and core results. This exploratory notebook focuses on visualizing the data-generating process and understanding why the naive comparison can be biased.
|
||||
|
||||
## Setup
|
||||
|
||||
```{r}
|
||||
suppressPackageStartupMessages({
|
||||
library(dplyr)
|
||||
library(ggplot2)
|
||||
library(gt)
|
||||
library(gtsummary)
|
||||
library(tibble)
|
||||
})
|
||||
|
||||
source("../R/simulate_icu_cohort.R")
|
||||
source("../R/estimate_naive_vasopressor_mortality_effect.R")
|
||||
```
|
||||
|
||||
## Simulate Data
|
||||
|
||||
```{r}
|
||||
icu_data <- simulate_icu_cohort(n_patients = 1000, seed = 20260531)
|
||||
naive_mortality_analysis <- estimate_naive_vasopressor_mortality_effect(icu_data)
|
||||
eligible_icu_patients <- naive_mortality_analysis$eligible_icu_patients
|
||||
```
|
||||
|
||||
## Eligibility Overview
|
||||
|
||||
```{r}
|
||||
eligibility_overview <- icu_data |>
|
||||
summarize(
|
||||
simulated_patients = n(),
|
||||
suspected_sepsis = sum(suspected_sepsis == 1),
|
||||
hypotension_at_baseline = sum(hypotension_at_baseline == 1),
|
||||
elevated_lactate_at_baseline = sum(elevated_lactate_at_baseline == 1),
|
||||
eligible = sum(eligible == 1)
|
||||
) |>
|
||||
tidyr::pivot_longer(
|
||||
cols = everything(),
|
||||
names_to = "measure",
|
||||
values_to = "patients"
|
||||
)
|
||||
|
||||
eligibility_overview |>
|
||||
gt() |>
|
||||
tab_header(title = "Eligibility Overview") |>
|
||||
cols_label(
|
||||
measure = "Measure",
|
||||
patients = "Patients"
|
||||
) |>
|
||||
fmt_integer(columns = patients)
|
||||
```
|
||||
|
||||
## Baseline Distributions
|
||||
|
||||
```{r}
|
||||
eligible_icu_patients |>
|
||||
select(age, sofa_score, lactate, map) |>
|
||||
tbl_summary(
|
||||
statistic = all_continuous() ~ "{mean} ({sd}); {median} [{p25}, {p75}]",
|
||||
missing = "no"
|
||||
)
|
||||
```
|
||||
|
||||
## Severity By Observed Treatment
|
||||
|
||||
```{r}
|
||||
eligible_icu_patients |>
|
||||
mutate(
|
||||
observed_treatment = factor(
|
||||
early_vasopressor,
|
||||
levels = c(0, 1),
|
||||
labels = c("No early vasopressor", "Early vasopressor")
|
||||
)
|
||||
) |>
|
||||
ggplot(aes(x = observed_treatment, y = sofa_score, fill = observed_treatment)) +
|
||||
geom_boxplot(alpha = 0.75, width = 0.65, show.legend = FALSE) +
|
||||
labs(
|
||||
title = "SOFA Score Is Higher In Early-Treated Patients",
|
||||
x = NULL,
|
||||
y = "SOFA score"
|
||||
) +
|
||||
theme_minimal()
|
||||
```
|
||||
|
||||
Early vasopressor patients tend to have higher SOFA scores in this simulated cohort. That happens because the treatment assignment mechanism makes sicker patients more likely to receive early vasopressors.
|
||||
|
||||
## Lactate And MAP By Treatment
|
||||
|
||||
```{r}
|
||||
eligible_icu_patients |>
|
||||
mutate(
|
||||
observed_treatment = factor(
|
||||
early_vasopressor,
|
||||
levels = c(0, 1),
|
||||
labels = c("No early vasopressor", "Early vasopressor")
|
||||
)
|
||||
) |>
|
||||
ggplot(aes(x = map, y = lactate, color = observed_treatment)) +
|
||||
geom_point(alpha = 0.55) +
|
||||
labs(
|
||||
title = "Shock Severity Markers Differ By Observed Treatment",
|
||||
x = "Mean arterial pressure",
|
||||
y = "Lactate",
|
||||
color = "Observed treatment"
|
||||
) +
|
||||
theme_minimal()
|
||||
```
|
||||
|
||||
Higher lactate and lower MAP are both markers of greater shock severity. If treatment groups differ on these variables, a simple treated-versus-untreated comparison is not yet a causal estimate.
|
||||
|
||||
## Mortality By SOFA Score
|
||||
|
||||
```{r}
|
||||
eligible_icu_patients |>
|
||||
mutate(
|
||||
observed_treatment = factor(
|
||||
early_vasopressor,
|
||||
levels = c(0, 1),
|
||||
labels = c("No early vasopressor", "Early vasopressor")
|
||||
)
|
||||
) |>
|
||||
ggplot(aes(x = sofa_score, y = death_28d, color = observed_treatment)) +
|
||||
geom_jitter(height = 0.04, width = 0.15, alpha = 0.35) +
|
||||
geom_smooth(method = "glm", method.args = list(family = "binomial"), se = FALSE) +
|
||||
labs(
|
||||
title = "Mortality Risk Rises With SOFA Score",
|
||||
x = "SOFA score",
|
||||
y = "Observed 28-day death",
|
||||
color = "Observed treatment"
|
||||
) +
|
||||
theme_minimal()
|
||||
```
|
||||
|
||||
This plot shows why baseline severity matters. If SOFA score predicts death and also affects treatment assignment, then SOFA score is a confounder for the naive treatment comparison.
|
||||
|
||||
## Naive Mortality Effect Estimates
|
||||
|
||||
```{r}
|
||||
naive_mortality_analysis$mortality_effect_estimates |>
|
||||
gt() |>
|
||||
tab_header(title = "Naive 28-Day Mortality Effect Estimates") |>
|
||||
cols_label(
|
||||
estimate = "Estimate",
|
||||
value = "Value"
|
||||
) |>
|
||||
fmt_number(columns = value, decimals = 3)
|
||||
```
|
||||
|
||||
The next methodological step is to adjust for baseline severity rather than comparing observed treatment groups directly.
|
||||
Reference in New Issue
Block a user