Perioperative Tablet-Based Telemonitoring After Abdominal Wall Hernia Surgery: Pilot Prospective Observational Cohort Study
Bibliographic record
Abstract
BACKGROUND: Hernia repairs account for millions of general surgical procedures performed each year worldwide, with a notable shift to outpatient settings over the last decades. As technical possibilities such as smartphones, tablets, and different kinds of probes are becoming more and more available, such systems have been evaluated for applications in various clinical settings. However, there have been few studies conducted in the surgical field, especially in general surgery. OBJECTIVE: We aimed to assess the feasibility of a tablet-based follow up to monitor activity levels after repair of abdominal wall hernias and to evaluate a possible reduction of adverse events by their earlier recognition. METHODS: Patients scheduled for elective surgical repair of minor abdominal wall hernias (eg, inguinal, umbilical, or trocar hernias) were equipped with a telemonitoring system, including a tablet, pulse oximeter, and actimeter, for a monitoring phase of 7 days before and 30 days after surgery. Descriptive statistical analyses were performed. RESULTS: We enrolled 16 patients with a mean overall age of 48.75 (SD 16.27) years. Preoperative activity levels were reached on postoperative day 12 with a median of 2242 (IQR 0-4578) steps after plunging on the day of surgery. The median proportion of available activity measurements over the entire study period of 38 days was 69% (IQR 56%-81%). We observed a gradual decrease in the proportion of available data for all parameters during the postoperative course. Six out of ten patients (60%) regained preoperative activity levels within 3 weeks after surgery. Overall, patients rated the usability of the system as relatively easy. CONCLUSIONS: Tablet-based follow up is feasible after surgical repair of minor abdominal wall hernias, with good adherence rates during the first couple of weeks after surgery. Thus, such a system could be a useful tool to supplement or even replace traditional outpatient follow up in selected general surgical patients.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".