Fig 1.
Patient flow through the study.
Interventions were identified from a prospective registry of consecutive aortic interventions. Each patient was included only once (i.e., for the latest aortic intervention) during the study period.
Fig 2.
Proposed principle of follow-up assessment.
Individual follow-up is characterized by two indicators: absolute duration and completeness. The duration measures the time, for which valid information on the investigated outcome is available (patients 1 to 6), but must end at the study closing date, even if information becomes available thereafter (patients 2 and 6). Similarly, clinical outcome is defined at this very closing date (patient 6). Summary statistics exclude those known to have died (patient 3) as well as those lost to follow-up within 30 days (patient 7). Both subgroups are reported separately as proportions; those who have died with a median time to death. The completeness, in contrast, is expressed as proportion (follow-up index, FUI), calculated as displayed. Patients known to be alive (patients 1 and 2) and patients known to be dead (patient 3) carry a FUI of 1 by default, all others have a FUI between 0 and 1. The unaccounted follow-up period (1 minus FUI) may hide events (patient 5) leading to underestimation bias. Therefore, the closer the FUI to 1 the smaller the risk of selection bias.
Table 1.
Patient and intervention-related characteristics.
Fig 3.
Kaplan Meier long-term survival estimates for the study population (n = 1207) according to completeness of follow-up.
Scenario A (blue curve) estimated survival based on registry data, which, although collected prospectively during clinical routine, were not up to date for every patient at the study end. Scenario B (red curve), however, estimated survival of the same study population based on a comprehensive survey performed at the study end. Completeness of follow-up differed significantly between scenarios as expressed as follow-up index (FUI, see text). Thereby, scenario A (FUI 0.57±0.35) underestimated effective mortality by almost 30% (scenario B; FUI 1.0±0).
Fig 4.
Association between follow-up index (FUI) and the degree of underestimated mortality among ‘potential survivors’ (n = 1116).
Patients were grouped into equally sized quartiles according to FUI (quartile 1 with highest FUIs; quartile 4 with lowest FUIs). After adjustment for potential confounding factors, underestimation of the actual mortality (i.e., inaccuracy of outcome estimate) correlated significantly with decreasing completeness of follow-up (see Table 2).
Table 2.
Association between FUI and underestimation of mortality in potential survivors (n = 1116).