Clinical pearls to managing men’s health conditions during the COVID-19 pandemic
Bibliographic record
Abstract
In late 2019, a novel coronavirus (Sars-CoV-2) was identified in Wuhan, China.1 Subsequently, the rapid spread of the coronavirus disease 2019 (COVID-19) around the world has resulted in the declaration of a pandemic by the World Health Organization,2 with resulting massive changes in societal behaviors. COVID-19 has had a devastating impact on many of those afflicted with the condition, but the pandemic has also had a dramatic effect on healthcare delivery for those patients without COVID-19. In preparation for expected increased hospital resource needs, most centers have limited or cancelled all elective surgical procedures. Furthermore, in accordance with new social distancing norms, clinical encounters for non-emergent patients have shifted, when possible, to virtual visits. Urologic surgical care in Canada has undergone a substantial shift to only offering surgery for emergencies and urgent oncology cases. Most of the “bread-and-butter” urology, including the entire subspecialty of men’s health and andrology, does not qualify as emergent or even urgent care. Surgeries have been postponed indefinitely for most men requiring intervention for the management of infertility, sexual health, voiding dysfunction, and chronic urological pain. Thankfully, men’s health is an ideal field for virtual care (either by telephone or by video calling) given the many medical and patient education options for treatment. There have been several studies across a variety of specialties that appear to show that virtual visits do not worsen outcomes, and in some cases even improve care.3–7 Two studies within the field of urology have been completed showing no adverse outcomes in a general urology virtual followup clinic and in a virtual clinic focused on renal colic.8,9 With the fluid nature of a pandemic scenario, it is unclear when we will once again have access to surgical and clinical resources to provide the standard care for our patients. As a result, we aimed to bring together some of Canada’s urologic leaders in men’s health to provide pearls and pitfalls regarding the management of common men’s health conditions during the pandemic using the virtual care model. A group of urologists from across Canada with expertise in the area of men’s health were invited to provide expert commentary on management of some common men’s health conditions during the COVID-19 pandemic. Each of the experts on the panel was provided with a set of standardized written questions (Table 1) to answer. The answers were edited by authors LW, RF, and KJ to fit into a standardized report. The goal of this manuscript is to provide expert guidance to our urology colleagues on how to safely provide virtual care for patients with some of the common men’s health conditions, and to provide a resource to our primary care colleagues to understand the options available to the consultant urologist assessing these patients. Table 1 Question’s provided to manuscript authors
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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 | 0.011 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.009 | 0.020 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".