The Economic Burden of Urinary Tract Infection and Pressure Ulceration in Acute Traumatic Spinal Cord Injury Admissions: Evidence for Comparative Economics and Decision Analytics from a Matched Case-Control Study
Bibliographic record
Abstract
Secondary complications of spinal cord injury (SCI) are a burden to affected individuals and the rest of society. There is limited evidence of the economic burden or cost of complications in SCI populations in Canada, however, which is necessary for comparative economic analyses and decision analytic modeling of possible solutions to these common health problems. Comparative economic analyses can inform resource allocation decisions, but the outputs are only as good as the inputs. In this article, new evidence of the excess or incremental costs of urinary tract infection (UTI) and pressure ulceration (PU) in acute traumatic SCI from an exploratory case series analysis of admissions to a Level I specialized Canadian spine facility (2008-2013) is presented. Participants in a national SCI registry were case-control matched (1:1) on the predicted probability of experiencing UTI or PU during initial acute SCI admission. The excess costs of UTI and PU are estimated as the mean of the differences in total direct acute SCI admission costs (length of stay, accommodation, nursing, pharmacy) from the perspective of the admitting facility between participants matched or paired on demographic and SCI characteristics. Even relatively minor UTI and PU, respectively, added an average of $7,790 (standard deviation [SD] $6,267) and $18,758 (SD $27,574) to the direct cost of acute SCI admission in 2013 Canadian dollars (CAD). This case series analysis established evidence of the excess costs of UTI and PU in acute SCI admissions, which will support decision-informing analyses in SCI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".