ArticleCureus2026
Assessing Return to Performance After Surgery in National Football League Quarterbacks: A Comparative Analysis of Performance Metrics.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Return to play (RTP) is commonly used to assess recovery after injury but does not reflect post-injury performance quality. Return to pre-injury performance (RPIP) offers a more informative outcome, yet its application to National Football League (NFL) quarterbacks and the optimal performance metric remains unclear. This study compared commonly used quarterback performance metrics to determine whether any single measure effectively characterizes RPIP following injury requiring surgery. Methods This retrospective cohort study included NFL quarterbacks who had sustained a first injury requiring surgical intervention between 2006 and 2022, missed regular-season games, and had at least one full pre-injury season. Performance was assessed using Fantasy Football Points, ESPN Total Quarterback Rating (QBR), Passer Rating, and Passing Attempts. Pre-injury baseline was defined as each quarterback's peak single-season performance within the three years preceding injury to provide a stable estimate of individual pre-injury capacity. RPIP was calculated as (peak post-injury performance / pre-injury baseline) × 100 and expressed as a percentage, with 100% indicating complete return to pre-injury peak performance. Paired t-tests compared pre- and post-injury performance, and one-way analysis of variance (ANOVA) assessed differences in recovery magnitude across metrics. Results Seventy-three quarterbacks met inclusion criteria. Mean RPIP was approximately 94% for Fantasy Points, 107% for QBR, 97% for Passer Rating, and 91% for Passing Attempts. No statistically significant differences were observed between pre- and post-injury peak performance for any metric, with only small effect sizes across all measures (Cohen's d range: -0.19 to 0.10), suggesting minimal practical differences between pre- and post-injury performance. No statistically significant differences in recovery magnitude were detected across the performance metrics, although formal equivalence was not established. Conclusion Common quarterback performance metrics demonstrate similar overall patterns of post-injury decline and recovery. While certain metrics may offer advantages within specific subgroups, no single measure demonstrated superior overall sensitivity for assessing RPIP. These conclusions are based on the absence of statistically significant between-metric differences rather than formal equivalence testing and should be interpreted accordingly.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.