Bibliographic record
Abstract
Clinicians worldwide have been bracing for the fallout resulting from delayed non-COVID presentations during the global pandemic, with especial reference to time-sensitive conditions such as cancer. Patient behaviours have modified significantly, in no small part due to rising individual anxiety surrounding physical health concerns, isolation and serious financial burdens secondary to job losses. Of additional impact is the effect on an individual's ability to reach out and connect with social networks through the closing of the hospitality industry and nonessential shops. The “stay at home” message conveys clear instructions to those who would follow—in many cases, this is occurring at all costs. Across Europe it was theorized early on that lockdown measures could cause additional mortality and morbidity due to the delayed diagnosis of non-COVID disease and other indirect effects on health, such as personal economic crisis and significant psychological upset. The United Kingdom's 2 week-wait referral pathway for all cancer subtypes has borne witness to reduced referral rates to secondary care to around 20% of prelockdown levels. In this system, where only 30% to 40% of eventual cancer diagnoses arise from routine referrals outside of the 2-week wait pathway, this loss is of grave significance.1,2 The disquiet question that one is thus prompted to ask is that if not by this route, then when and how are these patients presenting? Moreover, how can we, as clinicians, provide the best and most appropriate care despite such patients falling outside of the modern realms of diagnostic practice? The inevitable effect of adherence to lockdown measures for so many is the impact on mental health that social isolation and fear of an infectious disease creates, even once lockdown measures are loosened. That quarantine should lead to a decline in mental health of a population is not a novel concept and has been witnessed in previous pandemics. The effects of the 2003 SARS-CoV outbreak included 31.2% of quarantined persons surveyed in Canada reporting symptoms of post-traumatic stress disorder as a direct result of the time spent in isolation. Seventeen years on, a recent, large population survey of psychological distress in China has reported a comparable rate of 35% as a result of the current SARS-CoV-2 pandemic.3 It follows then that isolation can lead to inadvertent physical self-neglect. On the clinical frontline, this has manifested as a return of historical clinical signs of advanced disease, in particular to the General Surgeon. A 90-year-old woman presents with an 8-month history of abdominal pain, nausea, and vomiting. Adhering to the UK guidelines for vulnerable persons, she reported intense anxiety since the pandemic began and had been strictly isolating alone at home, having not ventured outside of her abode for over 8 months. So much so, that her initial referral was to a psychiatrist for management of her mental state and presumed psychosomatic presentation. Meanwhile, an accompanying umbilical lump discharging malodorous fluid was attributed to either an infection or an umbilical hernia by a sequence of telemedicine GP consultations and an eventual ED attendance over the course of 12 weeks. The critical priority, presumably, to keep her shielded at home and away from the exposure risk posed by hospital encounters. The concept of a Sister Mary-Joseph nodule was likely deemed a historical piece of medical miscellany (if considered at all)—sadly now one of a number of nigh prehistoric clinical signs that may become more commonplace (Fig. 1). Many of our colleagues have reported advanced, and at times unthinkable, presentations of what could (and should) been survivable surgical conditions.4–6 This effect is likely to be magnified further in low- to middle-income countries.FIGURE 1: Not just omphalitis.One may make the argument as to whether recognition of these signs is relevant. Does it change the course of the disease? Even when first described by Storer in 1928, the Sister Mary-Joseph nodule was considered a preterminal finding. However, when access to effective palliative care services is wholly dependent on a clear diagnosis—of which terminal cancer is considered an absolute qualifier—surely the best treatment we can offer such individuals is to recognise and diagnose rapidly. For some of us, this may mean dusting off some of the old textbooks, such that these patients’ final days can be passed with comfort and dignity with their families close at hand, and not in a hospital ward where visiting is still significantly restricted. “More harm is done because you do not look, than from not knowing what is in the book,” wrote Sir Zachary Cope in 1949.7 He presumably also envisaged a time where the described clinical signs and spot diagnoses of advanced disease would become obsolete with the advent of screening programs, cross-sectional imaging and ever-more sensitive biomarkers. With such pressures on services due to COVID, the result has been a proportional increase in telemedicine as opposed to in-person encounters. Now, the risk comes from a combination of both not being able to look, and potentially from having forgotten what was in the (older) books. As the introduction of the fastest and most ambitious vaccine programme in history gathers speed, maybe it is time for us to revise some of those old clinical signs and treat the seemingly trivial with an appropriate degree of suspicion, even if the most this achieves is to lessen the burden on these bystander victims of the pandemic and their families, and to enable delivery of quality palliative care.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.032 | 0.009 |
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".