baseline_nach_outcome.png

# ===========================================================================
# MODULE 09 · Baseline by outcome
# ===========================================================================
print("[09] Baseline nach Outcome ...")

variables = [
    ("alter",       "Alter (Jahre)"),
    ("sofa_score",  "SOFA-Score"),
    ("crp_mg_l",    "CRP (mg/l)"),
]

fig, axes = plt.subplots(1, 3, figsize=(13, 4.5))
fig.subplots_adjust(wspace=0.38)

for ax, (var, label) in zip(axes, variables):
    group0 = cohort.loc[cohort["verstorben_30d"] == 0, var].dropna()
    group1 = cohort.loc[cohort["verstorben_30d"] == 1, var].dropna()

    # KDE curves
    from scipy.stats import gaussian_kde
    for group, color, grp_label in [
        (group0, PRIMARY, "Überlebt"),
        (group1, EVENT,   "Verstorben"),
    ]:
        kde = gaussian_kde(group, bw_method="scott")
        xmin, xmax = group.min(), group.max()
        x_range = np.linspace(xmin - (xmax - xmin) * 0.05,
                              xmax + (xmax - xmin) * 0.05, 300)
        density = kde(x_range)
        ax.fill_between(x_range, density, alpha=0.25, color=color)
        ax.plot(x_range, density, color=color, linewidth=1.6, label=grp_label)

    # Median lines
    ax.axvline(group0.median(), color=PRIMARY, linestyle=":", linewidth=1.2)
    ax.axvline(group1.median(), color=EVENT,   linestyle=":", linewidth=1.2)

    ax.set_xlabel(label)
    ax.set_ylabel("Dichte" if ax == axes[0] else "")
    ax.set_title(label)
    ax.set_yticks([])
    ax.grid(axis="x", visible=False)

    # Mann-Whitney p-value
    _, p = stats.mannwhitneyu(group0, group1, alternative="two-sided")
    p_txt = f"p = {p:.3f}" if p >= 0.001 else "p < 0.001"
    ax.text(0.97, 0.95, p_txt, transform=ax.transAxes,
            ha="right", va="top", fontsize=9, color="#444444")

# Shared legend
handles, labels = axes[0].get_legend_handles_labels()
fig.legend(handles, labels, loc="lower center", ncol=2,
           bbox_to_anchor=(0.5, -0.04), fontsize=10)

save(fig, ASSETS / "09-deskriptive-statistik" / "assets" / "baseline_nach_outcome.png")