Frailty scoring systems in clinical practice: are we underdiagnosing?
Notice bibliographique
Résumé
Frailty has emerged as one of the most critical geriatric syndromes influencing morbidity, hospitalization rates, treatment tolerance, and overall survival and has emerged as one of the most critical determinants of adverse outcomes in older adults, yet it remains inconsistently identified in daily medical practice (1). Although populations are aging globally, the detection of frailty has not kept pace with clinical need. Frailty is no longer viewed as a vague geriatric concept but rather as a measurable, prognostically significant syndrome characterized by diminished physiological reserves and reduced resilience to stressors (2). Despite the availability of frailty assessment tools for nearly two decades, screening remains sporadic, and underdiagnosis persists in outpatient clinics, emergency departments, and inpatient settings (3). This disconnect between knowledge and practice has implications for mortality, hospitalization duration, functional decline, and healthcare utilization. Multiple validated instruments, such as the Fried Frailty Phenotype, Clinical Frailty Scale (CFS), Edmonton Frail Scale, and FRAIL questionnaire, have been proposed; yet, integration into internal medicine workflows is far from standardized (4). Each tool offers different levels of feasibility, sensitivity, and clinical applicability. Although these tools are validated and relatively simple to administer, they are not consistently integrated into internal medicine, cardiology, oncology, nephrology, or primary care settings. Most clinicians acknowledge frailty as a concept but do not routinely document it or formally measure it before making diagnostic or therapeutic decisions. This disconnect between awareness and implementation remains a major barrier to recognizing frailty early. Frailty is frequently overlooked due to time constraints, insufficient training, and an overemphasis on chronological age rather than biological vulnerability. In many institutions, frailty scoring is seen as optional rather than essential. As a result, patients with subtle functional decline or low physiological reserve are often categorized as “fit” or “stable” based solely on basic laboratory tests, vital signs, or self-reported independence. Without formal scoring, these individuals undergo invasive procedures, polypharmacy, or aggressive treatments without adequate risk adjustment. The absence of systematic screening prevents proactive interventions such as nutritional support, physiotherapy, medication review, or shared decision-making based on functional status (5). Failure to identify frailty promptly has direct consequences on patient outcomes. Hospitalizations become longer, complication rates rise, and recovery after acute illness or surgery is often delayed. Inappropriate medication regimens, increased risk of delirium, and higher rates of institutionalization are frequently observed in frail individuals who were never assessed formally (6). Moreover, when frailty is not documented, multidisciplinary interventions are either postponed or never initiated. Treatment goals may not align with the patient’s physiological capacity, leading to emotional distress for both patients and families. Ultimately, the health system absorbs higher costs due to preventable adverse events and prolonged care needs. Frailty scoring should not be viewed as an additional administrative step but as a clinical necessity. Integrating these tools into admission protocols, outpatient evaluations, and preoperative assessments can transform care planning. When clinicians routinely incorporate frailty scores, they are better equipped to individualize therapies, adjust drug dosages, and determine realistic rehabilitation targets. Hospitals and academic centers that embed frailty assessments into electronic health records and clinical algorithms report improved outcomes and more efficient resource allocation. Making frailty screening part of standard internal medicine practice would increase awareness, guide multidisciplinary collaboration, and improve continuity of care. Frailty is not merely a geriatric concept but a cross-disciplinary determinant of prognosis and treatment tolerance. Underdiagnosis persists because scoring systems are not routinely applied, despite being practical and valid. To close this gap, healthcare providers must adopt a proactive approach by incorporating frailty assessment into everyday clinical workflows. Education, institutional protocols, and simple screening steps can significantly improve recognition rates. By normalizing frailty scoring in internal medicine and related specialties, we can better align treatments with physiological reserve, reduce complications, and improve the quality of life for older adults.
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 | 0,091 | 0,250 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,010 | 0,011 |
| Science ouverte | 0,008 | 0,007 |
| Intégrité de la recherche | 0,006 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,002 |
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 ».