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Stamping method for frozen section.

An easy and very quick method for proper orientation of tissue for frozen section is described. In this technique the stickiness of the cold chuck is used to advantage and the resulting slides are of improved quality.

Frozen Sections↗

Laser stapedotomy minus prosthesis (laser STAMP): absence of refixation.

OBJECTIVE: To determine what percentage of patients with otosclerosis could successfully undergo a laser stapedotomy minus prosthesis over a 5-year period, and to determine the percentage of patients in whom refixation develops during follow-up. STUDY DESIGN: Retrospective case review of 136 patients (137 ears) who underwent primary surgery for otosclerosis. SETTING: An otology/neurotology tertiary referral center. PATIENTS: Patients were chosen if they had clinical evidence of otosclerosis without a history of otologic surgery. INTERVENTIONS: A standard stapes approach was used for all patients. For the laser stapedotomy minus prosthesis, a hand-held laser probe was used to vaporize the anterior crus of the stapes and perform a linear stapedotomy across the anterior one third of the footplate. If otosclerosis was confined to the fissula ante fenestram, the stapes became completely mobile. The stapedotomy opening was sealed with an adipose tissue graft from the ear lobe. MAIN OUTCOME MEASURES: Pure-tone audiometry with appropriate masking and auditory discrimination testing was performed before surgery, 6 weeks after surgery, and every year thereafter. RESULTS: Of the 137 cases, favorable anatomy and minimal otosclerosis allowed 46 (33.6%) of these patients to undergo laser stapedotomy minus prosthesis. Fifty-seven patients (41.6%) could not undergo the procedure because of extensive otosclerosis. The remaining 34 patients (24.8%) did not receive laser stapedotomy minus prosthesis because of other anatomic or technical difficulties. Of the 34 patients in the laser stapedotomy minus prosthesis group with more than 4 months follow-up, the average air-bone gap was closed from a mean of 22 dB (SD 10 dB) to 6 dB (SD 4 dB) 6 weeks postoperatively. Follow-up periods ranged from 5 months to 53 months (mean 767 days, SD 437 days). The long-term air-bone gap improved slightly to an average of 5 dB (SD 6 dB) in comparison with the sixth postoperative week value. CONCLUSION: Laser stapedotomy minus prosthesis is a minimally invasive procedure, which over the follow-up period has a very low incidence of refixation, as evidenced by a lack of progressive conductive hearing loss. The success of this procedure depends on the correct selection of cases. This procedure has been successfully performed on 33.6% of patients undergoing primary stapes surgery. Laser stapedotomy minus prosthesis seems to be a viable alternative to conventional stapedotomy that yields good results without evidence of refixation over an extended time.

Adipose Tissue↗

A visualization system for space-time and multivariate patterns (VIS-STAMP).

The research reported here integrates computational, visual, and cartographic methods to develop a geovisual analytic approach for exploring and understanding spatio-temporal and multivariate patterns. The developed methodology and tools can help analysts investigate complex patterns across multivariate, spatial, and temporal dimensions via clustering, sorting, and visualization. Specifically, the approach involves a self-organizing map, a parallel coordinate plot, several forms of reorderable matrices (including several ordering methods), a geographic small multiple display, and a 2-dimensional cartographic color design method. The coupling among these methods leverages their independent strengths and facilitates a visual exploration of patterns that are difficult to discover otherwise. The visualization system we developed supports overview of complex patterns and, through a variety of interactions, enables users to focus on specific patterns and examine detailed views. We demonstrate the system with an application to the IEEE InfoVis 2005 Contest data set, which contains time-varying, geographically referenced, and multivariate data for technology companies in the US.

Algorithms↗

Does date stamping ICD-9-CM codes increase the value of clinical information in administrative data?

CONTEXT: Comorbidity measures are designed to exclude complications when they map International Classification of Diseases (ICD-9-CM) codes to diagnostic categories. The use of data fields that indicates whether each secondary diagnosis was present at the time of hospital admission may lead to the more accurate identification of preexisting conditions. OBJECTIVE: To examine the rate of misclassification of ICD-9-CM codes into diagnostic categories by the Dartmouth-Manitoba adaptation of the Charlson index and by the Elixhauser comorbidity algorithm. DATA SOURCE: Analysis of 178,838 patients in the California State Inpatient Database (CA SID) admitted in 2000 for one of seven major medical and surgical conditions. The CA SID includes a condition present at admission (CPAA) modifier for each ICD-9-CM code. STUDY DESIGN: The Dartmouth/Charlson index and the Elixhauser comorbidity measure were used to map the ICD-9-CM codes into diagnostic categories for patients in each study population. We calculated the misclassification rate for each mapping algorithm, using information from the CPAA as the "gold standard." PRINCIPAL FINDINGS: The Dartmouth/Charlson index underestimated the prevalence of hemiplegia/paraplegia by 70 percent, cerebrovascular disease by 70 percent, myocardial infarction by 65 percent, congestive heart failure (CHF) by 45 percent, and peptic ulcer disease by 34 percent. The Elixhauser algorithm misclassified complications as preexisting conditions for 43 percent of the coagulopathies, 25 percent of the fluid and electrolyte disorders, 18 percent of the cardiac arrhythmias, 18 percent of the cardiac arrhythmias, and 9 percent of the cases of CHF. CONCLUSION: Adding the CPAA modifier to administrative data would significantly enhance the ability of the Dartmouth/Charlson index and of the Elixhauser algorithm to map ICD-9-CM codes to diagnostic categories accurately.

Algorithms↗