Impact of COVID-19 on Hemodialysis Patients: The Quebec Renal Network (QRN) COVID-19 Study
Bibliographic record
Abstract
Background: Hemodialysis patients had to face numerous challenges during the COVID-19 pandemic. They are at increased risk of severe complications of COVID-19 and continued to visit hospitals thrice weekly, increasing their risk of being infected. The objective of this study was to document the impact of the COVID-19 on patient's experience in hemodialysis in Quebec. Methods: Between November 2020 and May 2021, we conducted semi-structured interviews with 20 patients who were undergoing dialysis treatments in six hemodialysis units in Montreal. Interviews were transcribed and analyzed using thematic content analysis. Results: Patients were satisfied by the measures implemented within their units in order to prevent COVID-19 outbreaks, such as making masks mandatory, restricting access to the dialysis ward, and even limiting the number of accompanying persons allowed. Participants reported that following the public health guidelines (social distancing, wearing a mask and washing hands) was easy and important in order to ensure their own and their family members' safety. Because of this, participants were more likely to refuse to see their family resulting in feeling of isolation. This was particularly relevant for Indigenous patients who were having their hemodialysis treatment away from their home and family. This sub-group experienced particular issues due to the prolonged remoteness from their loved ones, change in their hemodialysis center and with the measures put in place by the hotel they were residing at. Even though their usual routine outside of dialysis might have changed due to the pandemic, hemodialysis treatments allowed patients to keep a certain normality in their lives. Positive consequences were mentioned such as frequent contact through telemedicine and the existing solidarity between patients during the pandemics. Conclusions: Patients undergoing hemodialysis faced particular challenges due to the COVID-19 pandemic. Nonetheless, they showed great resilience in their capacity to adapt to the new reality of their hemodialysis treatments. Funding: Government Support - Non-U.S.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".