Publications by authors named "Christian Sanderfer"

Article Synopsis
  • The study examined the impact of transitioning to an Acute Care Surgery (ACS) model at a community hospital on Emergency General Surgery (EGS) patients, focusing on access to care and mortality rates.
  • It analyzed data from 467 patients before the transition and 238 patients after, noting an increase in older, Black, and underinsured patients post-transition, but no significant changes in mortality rates or hospital stay length.
  • However, there was a notable increase in hospital readmissions after the transition, suggesting that while access improved, the quality of care necessitates further examination.
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Objectives: Acute Care Surgery (ACS) admissions and procedures are substantially increasing. ACS disproportionally accounts for a majority of morbidity and mortality among surgical patients. Minimally invasive techniques are associated with improved outcomes and shorter hospital length of stay within the ACS population.

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Article Synopsis
  • The study outlines a 10-year quality improvement program for surgical stabilization of rib fractures (SSRF) at a Level 1 trauma center to improve patient outcomes and ensure safety.
  • The research involved a review of cases from 2022, focusing on various data points like patient demographics, complications, and rib fracture specifics for 82 identified patients, where 88% underwent SSRF.
  • Results indicated that SSRF patients had a 15% mortality rate, with notable complications linked to factors like the number of ribs stabilized and trauma severity, emphasizing the need for ongoing scrutiny in surgical practices.*
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Vascular calcification is associated with a higher incidence of cardiovascular events, but its prevalence in different vascular zones and the influence of demographics, risk factors, and morphometry remain insufficiently understood. Computerized tomography angiography scans from 211 subjects 5-93 yr old (mean age 47 ± 24 yr, 127 M/84 F) were used to build 3D vascular reconstructions and measure arterial diameters, tortuosity, and calcification volumes in six vascular zones spanning from the ascending thoracic aorta to the pelvic arteries. A machine learning random forest algorithm was used to determine the associations between calcification in each zone with demographics, risk factors, and vascular morphometry.

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