THE UNMET NEEDS OF LUPUS PATIENTS: CREATING VISIBILITY AND SUPPORTING PATIENTS AND FAMILIES IN THEIR JOURNEY
Bibliographic record
Abstract
PV290 / #641 Case Report Poster Topic: AS17 - Miscellaneous Introduction Right from the first symptom, through diagnosis and coping with the many phases of living with lupus, this chronic autoimmune disease has proven to be a lonely journey that most patients thread. With 3 rheumatologists to a population of about 31 million, the huge provider to patient gap in the workforce necessitates the need for interdisciplinary and collaborative efforts from both clinical and nonclinical personnel to meet the demand for holistic care of not only patients, but their caregivers, families, loved ones and society at large. Case Presentation With Investigation Over the years, the increasing report of autoimmune conditions, particularly lupus, in Ghana, and the continent of Africa at large, suggests their ubiquity and not rareness as was previously perceived. The autoimmune disease landscape, as studies reveal, is complex, almost other-worldly in contexts with dearth of information. Lupus has been a mysterious silent killer in Ghana. It is significantly difficult to get any relevant information required to inform policy as well as garner support for lupus patients. Literature Review In Ghana, this situation is further compounded by challenges such as misdiagnosis, delayed referrals, economic challenges and sociocultural beliefs. The labyrinth of accessing the needed healthcare, lengthy process of obtaining clinical diagnoses and its ripple effect on the quality of life, finances and social life in themselves, often overwhelms many patients and pushes them to the edge of despair. Moreover, the lack of awareness among relevant stakeholders and the public further exacerbates the challenges that exist. Acknowledgment of these challenges has been the reason for the work of Oyemam Autoimmune Foundation (OYEMAM) in creating visibility about lupus and raising support for those affected directly and indirectly through its flagship lupus awareness campaign since 2016 in Ghana. Discussion The Foundation, which is a patient-led registered nonprofit has remained committed to inspiring hope through advocacy with policymakers and other relevant stakeholders; education and raising awareness through the media, engaging with diverse audiences in-person and virtually, as well as providing support for people living with lupus and other autoimmune conditions. OYEMAM has been deliberate about the counseling needs for those affected, recognizing this often-overlooked burden and addressing it in many little ways has brough much relief and hope to many patients and their families. This paper adopts a walkthrough approach to examine the strategies of OYEMAM’s interventions by presenting the lived experiences of those we have engaged with and some of the impact made so far. We acknowledge patients and all who have and continue to contact OYEMAM giving us a reason to strive on and contribute to this misunderstood and underserved aspect of human life and health.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".