急性心筋梗塞後の心臓リハビリテーション継続への退院支援および連携に関する実態調査

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  • キュウセイ シンキン コウソク ゴ ノ シンゾウ リハビリテーション ケイゾク エ ノ タイイン シエン オヨビ レンケイ ニ カンスル ジッタイ チョウサ
  • Survey on Discharge Planning and Cooperation on Cardiac Rehabilitation after Acute Myocardial Infarction

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目的:急性心筋梗塞(AMI)患者への入院期から回復期(退院後5カ月まで)心臓リハビリテーション(CR)継続への退院支援と連携の現状を明らかにする.方法:日本循環器学会循環器専門医研修施設に質問紙調査(郵送法)し,回答187施設(回収率:20.7%)でデータ解析可能な153施設を心大血管疾患CR施設基準認定施設(認定群:36施設)と末認定施設(未認定群:117施設)で比較した.結果:AMI後の回復期CR参加率は認定群33%,未認定群12%であった.回復期CR継続への退院支援は認定群89%,末認定群26%で有意差を認めた(p<0.001).回復期CR施設への連携は認定群4施設(11%),未認定群11施設(9%)であった.認定群の42%が他施設からAMI患者を平均10.3名/年受け入れていた.結語:AMI後の回復期CR継続への退院支援は認定群では8割が実施していたが,末認定群は3割以下で半数が退院支援を受けず退院していた.CR継続への地域連携は施設認定基準の取得にかかわらず1割と低く,今後の課題である.

Objectives : In this study, we evaluated a computerized scheme for automated setting of grayscale display for diffusion-weighted magnetic resonance images (DWI) of brains based on the density histogram analysis against existing standard methods for setting display conditions for DWI to ascertain whether the automated methods provided more consistent display. Methods : We used 60 brain DWI cases, which were scanned within the first 6 hours after stroke onset. In our computerized scheme, the existing method of setting the display conditions for DWI using the thalamic signal intensity in a b0 image was first applied for one DWI case. The display grayscale was converted into 8-bits by the linear grayscale transfer technique. The density histogram was then determined, and the full width of pixel values corresponding to half of the maximum (FWHM) in density histogram was determined. The DWI volumes were then created for 60 cases, and the density histogram was determined from the brain region based on DWI volumes. The pixel value corresponding to the maximum in density histogram was determined for DWI volume. The display grayscale for DWI volumes was adjusted by setting the determined pixel value as a window center, and the pixel value that FWHM in the density histogram of adjusted DWI is corresponding to FWHM previously obtained as a window width. To compare the existing manual method to the automated method, the variation in signal intensity and image contrast was evaluated subjectively using a two-alternative-forced-choice test for pairs of images prepared by each method. Results : The subjective similarity for pairs of DWI volumes adjusted using our computerized scheme was judged to be more similar than those using existing manual methods by 71.7%, which indicated clearly our automated method provided more consistent display. Conclusions : Our computerized scheme is a promising technique for accurate, prompt automated setting of display conditions in brain DWI, and may be useful to radiologists in decision-making for radiological diagnosis.

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