Jewish Hospital

About: Jewish Hospital is a healthcare organization based out in Cincinnati, Ohio, United States. It is known for research contribution in the topics: Antigen & Population. The organization has 3881 authors who have published 3414 publications receiving 123044 citations.

Comparison of bone removed during total hip arthroplasty with a resurfacing or conventional femoral component: a cadaveric study.

Abstract: We sought to examine the amount of bone removed during total hip arthroplasty with a resurfacing femoral component, compared to with a conventional, stemmed femoral component, by using 6 male and 4 female cadaveric pelves with attached bilateral proximal femora. Using randomized assignment and order, a total hip arthroplasty with a resurfacing femoral implant was performed on one side, and total hip arthroplasty with a cementless, stemmed femoral implant was performed on the contralateral side. The relationship between native femoral head diameter and the implanted acetabular socket was on average within 2 mm for both procedures. No significant difference was observed in the amount of acetabular bone removed (9.8 g for hip resurfacing vs 8.8 g). However, a resurfacing component resulted in approximated 3 x less bone removal from the femur (25.8 g vs 75.1 g). This study shows that the preservation of femoral bone with a resurfacing femoral component does not result in an increased removal of acetabular bone when compared to the use of a conventional, stemmed femoral component.

Distinguishing Neurocognitive Functions in Schizophrenia Using Partially Ordered Classification Models

Abstract: Current methods for statistical analysis of neuropsychological test data in schizophrenia are inherently insufficient for revealing valid cognitive impairment profiles. While neuropsychological tests aim to selectively sample discrete cognitive domains, test performance often requires several cognitive operations or ‘‘attributes.’’ Conventional statistical approaches assign each neuropsychological score of interest to a single attribute or ‘‘domain’’ (e.g., attention, executive,etc.),andscoresarecalculatedforeach.Thiscan yield misleading information about underlying cognitive impairments. We report findings applying a new method for examining neuropsychological test data in schizophrenia, based on finite partially ordered sets (posets) as classification models. A total of 220 schizophrenia outpatients were administered the Positive and Negative Symptom Scale (PANSS) and a neuropsychological test battery. Selected tests were submitted to cognitive attribute analysis a priori by two neuropsychologists. Applying Bayesian classification methods (posets), each patient was classified with respect to proficiency on the underlying attributes, based upon his or her individual test performance pattern. Twelve cognitive ‘‘classes’’ are described in the sample. Resulting classification models provided detailed ‘‘diagnoses’’ into ‘‘attribute-based’’ profiles of cognitive strength/ weakness, mimicking expert clinician judgment. Classification was efficient, requiring few measures to achieve accurate classification. Attributes were associated with PANSS factors in the expected manner (only the negative and cognition factors were associated with the attributes), and a double dissociation was observed in which divergent thinking was selectively associated with negative symptoms, possibly reflecting a manifestation of Kraepelin’s hypothesis regarding the impact of volitional disturbances on thought. Using posets for extracting more precise cognitive information from neuropsychological data may reveal more valid cognitive endophenotypes, while dramatically reducing the amount of testing required.