Clinical Outcomes and Complications for Achalasia Patients Admitted After Per-Oral Endoscopic Myotomy
Bibliographic record
Abstract
Background: Per-oral endoscopic myotomy (POEM) is a rapidly emerging minimally invasive procedure for management of achalasia. Same-day discharge after POEM is safe and feasible; however, some patients may need hospitalization. We aimed to identify characteristics and outcomes for achalasia patients requiring hospitalizations after POEM in the United States (US). Methods: The US National Inpatient Sample was utilized to identify all adult achalasia patients who were admitted after POEM from 2016 to 2019. Hospitalization characteristics and clinical outcomes were highlighted. Results: From 2016 to 2019, we found that 1,885 achalasia patients were admitted after POEM. There was an increase in the total number of hospitalizations after POEM from 380 in 2016 to 490 in 2019. The mean age increased from 54.2 years in 2016 to 59.3 years in 2019. Most POEM-related hospitalizations were for the 65 - 79 age group (31.8%), females (50.4%), and Whites (68.4%). A majority (56.2%) of the study population had a Charlson Comorbidity Index of 0. The Northeast hospital region had the highest number of POEM-related hospitalizations. Most of these patients (88.3%) were eventually discharged home. There was no inpatient mortality. The mean length of stay decreased from 4 days in 2016 to 3.2 days in 2019, while the mean total healthcare charge increased from $52,057 in 2016 to $65,109 in 2019. Esophageal perforation was the most common complication seen in 1.3% of patients. Conclusion: The number of achalasia patients needing hospitalization after POEM increased. There was no inpatient mortality conferring an excellent safety profile of this procedure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".