Community paramedic point of care testing: validity and usability of two commercially available devices
Bibliographic record
Abstract
BACKGROUND: Community Paramedics (CPs) require access to timely blood analysis in the field to guide treatment and transport decisions. Point of care testing (POCT), as opposed to laboratory analysis, may offer a solution, but limited research exists on CP POCT. The purpose of this study was to compare the validity of two devices (Abbott i-STAT® and Alere epoc®) by CPs in the community. METHODS: In a CP programme responding to 6000 annual patient care events, a split sample validation of POCT against traditional laboratory analysis for seven analytes (sodium, potassium, chloride, creatinine, hemoglobin, hematocrit, and glucose) was conducted on a consecutive sample of patients. The difference of proportion of discrepant results between POCT and laboratory was compared using a two sample proportion test. Usability was analysed by survey of CP experience, a linear mixed effects model of Systems Usability Scale (SUS) adjusted for CP clinical and POCT experience, an expert heuristic evaluation of devices, a review of device-logged errors, and coded observations of POCT use during quality control testing. RESULTS: Of 1649 episodes of care screened for enrollment, 174 required a blood draw, with 108 episodes (62.1%) enrolled from 73 participants. Participants had a mean age of 58.7 years (SD16.3); 49% were female. In 4 of 646 (0.6%) comparisons, POCT reported a critical value but the laboratory did not; with no statistically significant (p = 0.323) difference between i-STAT® (0.9%;95%CI:0.0,1.9%) compared with epoc® (0.3%;95%CI:0.0,0.9%). There were no instances of the laboratory reporting a critical value when POCT did not. In 88 of 1046 (8.4%) comparisons the a priori defined acceptable difference between POCT and the laboratory was exceeded; occurring more often in epoc® (10.7%;95%CI:8.1,13.3%) compared with i-STAT® (6.1%;95%CI:4.1,8.2%)(p = 0.007). Eighteen of 19 CP surveys were returned, with 11/18 (61.1%) preferring i-STAT® over epoc®. The i-STAT® had a higher mean SUS score (higher usability) compared with epoc® (84.0/100 vs. 59.6/100; p = 0.011). There were no statistically significant differences in device logged errors between i-STAT® and epoc® (p = 0.063). CONCLUSIONS: CP programmes can expect clinically valid results from POCT. Device usability assessments should be considered with any local implementation as the two POCT systems have different strengths.
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 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 | 0.026 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".