Notice bibliographique
Résumé
That Monday morning at the clinic started out like any other—the buzz of nurses directing patients to examination rooms, overhead pages filling the air, and residents milling about before the start of their clinics. A few hours into my morning rounds, I had developed a good rhythm—reviewing the patient’s chart, then recording a history and performing a physical, followed by a review with my preceptor, back to see the patient again, dictating the follow-up letter, and arranging for a follow-up visit. Her name was towards the end of the list that day. “Routine follow-up” was listed as the reason for her visit. My preceptor and I quickly perused her chart before going in—an 82-year-old female with locally advanced colon cancer that had been resected about two years earlier. She had survived her surgery, and no adjuvant therapy was administered. Her chart also made note of “mild to moderate Alzheimer’s.” The radiologist’s notes on her latest CT scan were not reassuring—“lesions most consistent with local recurrence and metastatic disease.” Her blood markers (CEA) were trending upwards and were ominously flagged for being elevated. This was not shaping up to be a routine follow-up visit after all. She was waiting accompanied by her husband when we entered the room. “I’m doing great. I can walk lots. I feel healthy. I have a good appetite,” she replied in response to our first question. We then went on to share the results of her most recent scan and blood tests. Her husband, being hard of hearing, leaned in, his mind and ears focused on what we were telling him. “So what does that mean?” he asked moments after we had told them that the cancer was back, a sign that his cognitive state was not too far behind his wife’s. Our patient had a puzzled and worried look on her face, her eyes darting between us and her husband. She knew something was wrong but couldn’t quite place her finger on it. Wanting to reassure us, she again repeated, “But I feel so good. I can walk. I have a great appetite.” We agreed these were indeed good signs, but inside we knew that her current health would not last for too long. Together, we went over the options for active therapy, and one by one each was ruled out as a possibility. We introduced the couple to the idea of palliative care and psychosocial support and provided the appropriate resources along with a follow-up appointment in the near future. After our encounter, I had a chance to reflect on what had just transpired. Between their medical illnesses and cognitive decline, this couple’s ability to cope with life was teetering on the edge. They were living independently at the time, but that would soon have to change. What started out as routine and predictable drastically changed by the end of the visit. This particular follow-up took a little more than half an hour of my time, but it had thrown the rest of their lives into chaos. It served as a poignant reminder of the responsibility that we as physicians have to take every encounter, however routine it might appear, as one that could have far-reaching ramifications for our patients. George Kurien Christopher de Gara, MB, MS Mr. Kurien is a fourth-year student, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada; ([email protected]). Dr. de Gara is professor of surgery, University of Alberta Faculty of Medicine and Dentistry, Edmonton, Alberta, Canada.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,114 | 0,038 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».