Adjusted horizontal stacked bar graphs ("Grotta bars") for consistent presentation of observational stroke study results.

Background: Modified Rankin Scale (mRS) scores are used to measure functional outcomes after stroke. Researchers create horizontal stacked bar graphs (nicknamed "Grotta bars") to illustrate distributional differences in scores between groups. In well-conducted randomized controlled trials, Grotta bars have a causal interpretation. However, the common practice of exclusively presenting unadjusted Grotta bars in observational studies can be misleading in the presence of confounding. We demonstrated this problem and a possible solution using an empirical comparison of 3-month mRS scores among stroke/TIA patients discharged home versus elsewhere after hospitalization. Patients and methods: Using data from the Berlin-based B-SPATIAL registry, we estimated the probability of being discharged home conditional on prespecified measured confounding factors and generated stabilized inverse probability of treatment (IPT) weights for each patient. We visualized mRS distributions by group with Grotta bars for the IPT-weighted population in which measured confounding was removed. We then used ordinal logistic regression to quantify unadjusted and adjusted associations between being discharged home and the 3-month mRS score. Results: Of 3184 eligible patients, 2537 (79.7%) were discharged home. In the unadjusted analyses, those discharged home had considerably lower mRS compared with patients discharged elsewhere (common odds ratio, cOR = 0.13, 95% CI: 0.11-0.15). After removing measured confounding, we obtained substantially different mRS distributions, visually apparent in the adjusted Grotta bars. No statistically significant association was found after confounding adjustment (cOR = 0.82, 95% CI: 0.60-1.12). Discussion and conclusion: The practice of presenting only unadjusted stacked bar graphs for mRS scores together with adjusted effect estimates in observational studies can be misleading. IPT weighting can be implemented to create Grotta bars that account for measured confounding, which are more consistent with the presentation of adjusted results in observational studies.