English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This work was aimed at developing risk-adjusted outcome models for profiling the internal quality of care after major lung resection. One thousand and sixty-two patients submitted to lobectomy (845) or pneumonectomy (217) from 1994 through 2004 at our unit were analyzed. Risk-adjusted models of 30-day or in-hospital morbidity, mortality and failure-to-rescue (death/complication ratio) were developed by stepwise logistic regression analyses and validated by bootstrap procedures. The regression equations were then used to estimate the outcome risks in 3 successive periods of activity (early: 1994-1997; intermediate: 1998-June/2001; late: July/2001-2004). Observed and predicted morbidity, mortality and failure-to-rescue rates were compared within each period by the z-test. The following regression models were developed: Predicted morbidity: ln R/1-R=-2.1+0.035 x age-0.02 x FVC+0.6 x extended resection+0.7 x cardiac co-morbidity (c-index=0.68). Predicted mortality: ln R/1-R=-7.6+0.08 x age-0.04 x ppoFEV1+1.6 x extended resection+1.2 x cardiac co-morbidity+1.1 x cerebrovascular co-morbidity (c-index=0.83). Predicted failure-to-rescue: ln R/1-R=-6.7+0.06 x age+1.5 x extended resection+1.2 x cerebrovascular co-morbidity (c-index=0.71). No differences were noted between observed and predicted outcome rates within each period, despite apparent unadjusted differences between periods. The use of risk-adjusted outcome models prevented misleading information derived from the unadjusted analysis of performance. We are currently using these models for internal quality-of-care audit purposes.

Risk-adjusted morbidity, mortality and failure-to-rescue models for internal provider profiling after major lung resection