Healthcare contacts among patients lost to follow-up in HIV care: review of a large regional cohort utilizing electronic health records
Bibliographic record
Abstract
In the United States 40% of HIV patients are lost to follow-up (LTFU) following linkage to HIV care and an estimated 30–61% of new HIV transmissions are attributed to this group. To characterize those LTFU and healthcare contacts they make, we retrospectively analyzed a large regional HIV cohort in Calgary, Canada, utilizing a province-wide electronic health record. Adults engaged in HIV care between January 2010 and August 2014 who had >12 months without HIV clinic contact were identified as LTFU. Of 1928 individuals engaged in care, 176 became LTFU with 64% having no healthcare contacts, 20% receiving HIV care elsewhere, and 16% making non-HIV healthcare contacts. Those LTFU making non-HIV healthcare contacts did so a median of six times (interquartile range 2–8), 76% attending emergency departments (ED). Compared to those retained in care, LTFU patients were younger (median age 43 versus 47 years), had lower CD4 + cell counts (median 420 versus 500 × 10 6 /l) and more commonly resided outside of the centralized HIV clinic’s city (odds ratio 4.58) (all p < 0.01). Our finding that a majority of those LTFU did not make healthcare contacts suggests that community and HIV clinic-based relinkage programs are needed. For those LTFU who make healthcare contacts enhanced ED-based relinkage programs could engage a majority.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".