Objectives
The aim of this study was to identify care settings associated with increased pressure ulcer risk among elderly hip fracture patients in the post-fracture period.
Design
Prospective cohort study.
Setting
Nine hospitals that participate in the Baltimore Hip Studies network and 105 postacute facilities to which patients from these hospitals were discharged.
Participants
Hip fracture patients age ≥65 years who underwent surgery for hip fracture.
Measurements
A full-body skin examination was conducted at baseline (as soon as possible after hospital admission) and repeated on alternating days for 21 days. Patients were deemed to have an acquired pressure ulcer (APU) if they developed ≥1 new pressure ulcers stage 2 or higher following hospital admission.
Results
Among 658 study participants, the APU cumulative incidence at 32 days after initial hospital admission was 36.1% (standard error 2.5%). Compared to home, the adjusted APU incidence rate was highest during the initial acute hospital stay (relative rate [RR] 2.2, 95% confidence interval [CI] 1.3–3.7) and during re-admission to the acute hospital (RR 2.2, 95% CI 1.1–4.2). The relative rates in rehabilitation and nursing home settings were 1.4 (95% CI 0.8–2.3) and 1.3 (95% CI 0.8–2.1), respectively.
Conclusion
Approximately one-third of hip fracture patients developed an APU during the study period. The rate was highest in the acute setting, a finding that is significant in light of Medicare’s policy of not reimbursing hospitals for the treatment of hospital-acquired pressure ulcers. Hip fracture patients constitute an important group to target for pressure ulcer prevention in hospitals.
Background
Quantification of islet mass is a crucial criterion for defining the quality of the islet product ensuring a potent islet transplant when used as a therapeutic intervention for select patients with type I diabetes.
Methods
This multi-center study involved all 8 member institutions of the National Institutes of Health-supported Islet Cell Resources (ICR) consortium. The study was designed to validate the standard counting procedure for quantifying isolated, dithizone-stained human islets as a reliable methodology by ascertaining the accuracy, repeatability (intra-observer variability), and intermediate precision (inter-observer variability). The secondary aim of the study was to evaluate a new software-assisted digital image analysis method as a supplement for islet quantification.
Results
The study demonstrated the accuracy, repeatability and intermediate precision of the standard counting procedure for isolated human islets. This study also demonstrated that software-assisted digital image analysis as a supplemental method for islet quantification was more accurate and consistent than the standard manual counting method.
Conclusions
Standard counting procedures for enumerating isolated stained human islets is a valid methodology, but computer-assisted digital image analysis assessment of islet mass has the added benefit of providing a permanent record of the isolated islet product being evaluated that improves quality assurance operations of current good manufacturing practice (cGMP).
In recent years, industries have turned to the field of operations research to help improve the efficiency of production and distribution processes. Largely absent is the application of this methodology to biological materials, such as the complex and costly procedure of human pancreas procurement and islet isolation. Pancreatic islets are used for basic science research and in a promising form of cell replacement therapy for a subset of patients afflicted with severe type 1 diabetes mellitus. Having an accurate and reliable system for cell distribution is therefore crucial. The Islet Cell Resource Center Consortium was formed in 2001 as the first and largest cooperative group of islet production and distribution facilities in the world. We previously reported on the development of a Matching Algorithm for Islet Distribution (MAID), an automated web-based tool used to optimize the distribution of human pancreatic islets by matching investigator requests to islet characteristics. This article presents an assessment of that algorithm and compares it to the manual distribution process used prior to MAID. A comparison was done using an investigator’s ratio of the number of islets received divided by the number requested pre- and post-MAID. Although the supply of islets increased between the pre- versus post-MAID period, the median received-to-requested ratio remained around 60% due to an increase in demand post-MAID. A significantly smaller variation in the received-to-requested ratio was achieved in the post- versus pre-MAID period. In particular, the undesirable outcome of providing users with more islets than requested, ranging up to four times their request, was greatly reduced through the algorithm. In conclusion, this analysis demonstrates, for the first time, the effectiveness of using an automated web-based cell distribution system to facilitate efficient and consistent delivery of human pancreatic islets by enhancing the islet matching process.
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