Magnetic resonance imaging of anterior cruciate ligament rupture

BACKGROUND: Magnetic resonance (MR) imaging is a useful diagnostic tool for the assessment of knee joint injury. Anterior cruciate ligament repair is a commonly performed orthopaedic procedure. This paper examines the concordance between MR imaging and arthroscopic findings. METHODS: Between February, 1996 and February, 1998, 48 patients who underwent magnetic resonance (MR) imaging of the knee were reported to have complete tears of the anterior cruciate ligament (ACL). Of the 48 patients, 36 were male, and 12 female. The average age was 27 years (range: 15 to 45). Operative reconstruction using a patellar bone-tendon-bone autograft was arranged for each patient, and an arthroscopic examination was performed to confirm the diagnosis immediately prior to reconstructive surgery. RESULTS: In 16 of the 48 patients, reconstructive surgery was cancelled when incomplete lesions were noted during arthroscopy, making reconstructive surgery unnecessary. The remaining 32 patients were found to have complete tears of the ACL, and therefore underwent reconstructive surgery. Using arthroscopy as an independent, reliable reference standard for ACL tear diagnosis, the reliability of MR imaging was evaluated. The true positive rate for complete ACL tear diagnosis with MR imaging was 67%, making the possibility of a false-positive report of "complete ACL tear" inevitable with MR imaging. CONCLUSIONS: Since conservative treatment is sufficient for incomplete ACL tears, the decision to undertake ACL reconstruction should not be based on MR findings alone

Evaluating the power of surface attendance counts to detect long-term trends in populations of crevice-nesting auklets

Power analyses are essential when developing a long-term monitoring program for a target species whose observation is logistically challenging and expensive. These analyses can be complicated when the observations have a complex variance structure reflecting many factors. Crevice-nesting seabirds such as least and crested auklets Aethia pusilla and Aethia cristatella illustrate both this need and these challenges. They are ecosystem indicators for the Bering Sea, a system expected to undergo large changes. Unfortunately, they are difficult to monitor as colonies occur on remote, hard to access islands in the Aleutians and Bering Sea, and nests occur in crevices underground, preventing direct observation. Current monitoring consists of breeding-season counts of auklets standing on the surface of sample plots in the colony; logically, a substantial decline in nesting population guarantees an eventual substantial decline in surface attendants. Yet, it remains debatable whether these highly variable counts can be used to statistically detect biologically relevant declines in the attending population let alone the nesting population. Subsequently, existing monitoring programs vary widely in survey design, effort levels, and daily summary statistics. The power of different survey designs was assessed by simulating observations from a state model developed from 11 years of observations using mixed-effects models and zero-inflated Poisson-lognormal regression. The analyses illustrate the process required for any monitoring program whose observations are described inadequately by standard statistical models. State model development revealed survey design refinements that reduce sampling variation. For least auklets, current sampling efforts provided 90% power to detect annual declines of 11% ("Critically Endangered" using IUCN Red List criteria), 4.5% ("Endangered"), or 2.4% ("Vulnerable") in two, four, or six generations, respectively; crested auklets took a few years longer. Power was more sensitive to number of days than number of plots. Results appear robust across a range of bird densities, providing guidance for monitoring other colonies or crevice-nesting species with similar life history strategies. Research should now focus on illuminating the relationship between the attending and nesting populations. Given the frequency of complicated variance structures and zero counts in ecological data, the general statistical models used here should prove widely applicable.</p