Characterizing Hospital Admissions in Persons with Parkinson’s Disease: 10-Year Retrospective Study of Administrative Data in Alberta, Canada (P10-11.015)
Bibliographic record
Abstract
Objective: To characterize the landscape of province-wide hospital admissions in persons with Parkinson’s disease (PD) and inform future healthcare improvement in this population. Background: Persons with PD tend to have longer hospital stays and are more likely to suffer from adverse events. The province of Alberta, Canada has a single healthcare provider (Alberta Health Services), permitting collection of population-level data from all healthcare facilities. Design/Methods: We performed a population-based, retrospective cohort study using discharge abstract data for all persons admitted to hospital from 2011 through 2021, in Alberta. We extracted data from the Discharge Abstract Database (DAD), which contains ICD-10-CA coded diagnoses for all patients discharged from hospital. Hospitalizations with PD as both main and pre-admission comorbid diagnoses were identified using the ICD-10-CA G20 (PD) and F02.3 (Dementia in PD) codes. Results: A total of 17168 hospitalizations were identified during the study period. Mean age was 78 (SD 9 years), and 39% (6761) were female. Median length of hospital stay was 12 days (interquartile range 27). For most patients, the attending service was family practice/general practice (67%, 11496), followed by internal medicine (16%, 2763), orthopedics (6%, 959), psychiatry (3%, 504), and neurology (3%, 497). In-hospital adverse events occurred in 11% (1857) of admissions; 1% (122) were life-threatening. The outcome in 54% (9289) of admissions was discharge home, 24% (4099) long-term care, and 13% (2244) to rehab or other acute care facility. In-hospital mortality was 7% (1225). Conclusions: Our study describes the landscape of PD hospitalization in a Canadian context. The main admitting specialties are family practice and internal medicine, and over half of patients are discharged home. Future directions include further analysis of this data to understand predictors for adverse outcomes and guide care delivery improvement. Disclosure: Dr. Mahjoub has nothing to disclose. Dr. Peters has nothing to disclose.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".