transfer

#Step 5: (Optional) Merge and visualize
library(ggplot2)

ggplot(icu_spo2_summary, aes(x = n_spo2_measurements_first_hour)) +
  geom_histogram(binwidth = 1, fill = "darkgreen", color = "black") +
  labs(
    title = "SpO₂ Measurements in First ICU Hour (After First Contiguous ≥1h Stay)",
    x = "Number of SpO₂ Measurements",
    y = "Number of Patients"
  ) +
  theme_minimal()

# Assuming `icu_one_hour_start` (the data frame with person_id and icu_start times)
# and `spo2_counts` (the count of SpO₂ measurements) are already available:

# Merge the results from both data frames
icu_spo2_summary <- icu_one_hour_start %>%
  left_join(spo2_counts, by = c("person_id", "icu_start")) %>%
  mutate(n_spo2_measurements_first_hour = coalesce(n_spo2_measurements_first_hour, 0))

# Check the first few rows of merged data
head(icu_spo2_summary)

# Now plot the histogram
library(ggplot2)

ggplot(icu_spo2_summary, aes(x = n_spo2_measurements_first_hour)) +
  geom_histogram(binwidth = 1, fill = "darkgreen", color = "black") +
  labs(
    title = "SpO₂ Measurements in First ICU Hour (After First Contiguous ≥1h Stay)",
    x = "Number of SpO₂ Measurements",
    y = "Number of Patients"
  ) +
  theme_minimal()