Ambulatory Parathyroidectomy for Secondary Hyperparathyroidism at a Large Dialysis Program in Toronto: A Program Report
Bibliographic record
Abstract
Purpose of program: Operative wait times for non-oncology-related procedures continue to rise in Canada, and this was further exacerbated by the COVID-19 pandemic. These challenges will remain prevalent beyond the pandemic given the limited number of acute care beds and resources required to care for patients. As a result, the need for innovative approaches to optimize the utilization of health care resources while maintaining equitable and timely access is needed. In this report, we describe the development of a collaborative ambulatory parathyroidectomy program between two centers in Toronto, allowing for more expedient surgical treatment of secondary hyperparathyroidism among patients from a large dialysis program. Sources of information: The need for expanded access to surgical care for secondary hyperparathyroidism was identified through interdepartmental communication between referring nephrologists and surgeons at Sunnybrook Health Sciences Centre and Women's College Hospital, respectively. Methods: A multidisciplinary ambulatory parathyroidectomy planning team was formed that included nephrologists, endocrine surgeons, nurses, and patient care managers to conduct a needs assessment. It was identified that patients had long wait times, and to address that gap in care, a protocol was developed to identify suitable patients requiring treatment. The teams created a plan to coordinate patient care and transfers. A clinical tool and protocol for post-operative management of hypocalcemia was developed using a Delphi model, gathering input from many members of the care team. The Delphi process to finalize the protocol included a series of virtual meetings over a period of about 4 months with various stakeholders and included input from two departmental heads (medicine and surgery), three nephrologists, a nurse practitioner, a patient care manager, and two nurse educators. Meetings involved core members of the Nephrology Quality Improvement and Patient Safety at Sunnybrook Health Sciences Centre and finalized protocol was agreed upon by members of this group at a quarterly meeting. Key findings: In this article, we describe the development, initial deployment, and planned assessment of the ambulatory parathyroidectomy program at the Women's College Hospital and Sunnybrook Health Sciences Centre. The primary aim of the program is to increase accessibility to parathyroidectomy for secondary hyperparathyroidism. A secondary aim was to allow patients to have streamlined care with a team that is well versed with maintenance dialysis needs and optimizing treatment of post operative hypocalcemia through standardized protocols. Limitations: Ambulatory parathyroidectomy relies on effective communication, flow, and availability of acute care beds. It is anticipated that occasionally, unexpected hospital demands, and health care disruptions may occur, which can limit efficiency of the program. We will also need to examine the cost-effectiveness of this program as it may improve access but increase costs related to the procedure. As the program is implemented, useful adaptations and policies to our protocol to help mitigate these limitations will be documented and published in our outcomes report. Implications: Ontario residents with chronic kidney disease with secondary hyperparathyroidism who have failed medical management will have increased and timely access to parathyroidectomy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".