Patient Experience: Living with Cystinuria During the COVID-19 Pandemic
Bibliographic record
Abstract
Background and Objectives Cystinuria is a rare genetic cause of recurrent urolithiasis and requires multimodal treatment, and stringent follow up. We wanted to evaluate the fears and concerns of patients with cystinuria during the COVID-19 pandemic. Materials and Methods An online survey using Google Forms was emailed to 165 patients with cystinuria who are maintained on a prospective database and had previously consented for email correspondence. Results Fifty-five responses were received following a single invitation, 23 were men and 32 women with a median age of 43 (range: 18-72) years. Thirty-nine (70.9%) out of 55 were isolating during the COVID-19 pandemic although only 7(12.7%) were given specific advice to shield officially. Six (10.9%) reported having COVID or COVID like symptoms, but none reported having a positive test. Only 9 (16.4%) had been able to work as usual. In comparison, 20 (36.4%) were able to work from home. Ten out of 19 patients (52.6%) on chelating medication described difficulty in access to their medicine, either due to a shortage at the pharmacy or prescription access. Reassuringly 34 (61.8%) patients described no issues with access to any of their cystinuria medications. Twenty-two patients (40%) reported experiencing pain or passing a stone during the COVID-19 pandemic, while 30 (54.5%) reported no problems. Of patients who felt it applicable, 16/31 (51.6%) were worried about attending the Emergency Department during this time. Of patients who had scheduled hospital appointments during this time, 26/44 (59.1%) had experienced cancellations. The majority of the respondents (37 (67.3%)) did not state any difference in the ability to stay hydrated during the lockdown. Twenty-eight (50.9%) were more anxious about their overall health during the pandemic, and 20 (36.4%) had expressed more concern about their kidney stones. Conclusion This personal fully patient-reported snapshot of the impact of the COVID-19 pandemic on a population of cystine stone formers in the United Kingdom has highlighted additional challenges for patients with a rare disease. The lockdown measures enforced have had a varying effect on patients’ ability to work as normal, access medications, health anxieties, in addition to cancellations of the planned hospital appointments and Emergency Department attendance, which will impact on their future health and pose evolving challenges in delivery of their future care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".