MétaCan
Menu
Retour à la cohorte
Enregistrement W3020551862 · doi:10.1111/jgs.16526

Typically Atypical: <scp>COVID</scp> ‐19 Presenting as a Fall in an Older Adult

2020· letter· en· W3020551862 sur OpenAlexaffabout
Richard Norman, Nathan M. Stall, Samir K. Sinha

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueCOVID-19 Clinical Research Studies
Établissements canadiensSinai Health SystemToronto General HospitalUniversity of TorontoUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineEmergency departmentAtypical pneumoniaPneumoniaPast medical historyPediatricsPulmonary embolismTriageCoronavirus disease 2019 (COVID-19)Emergency medicineInternal medicineDiseaseInfectious disease (medical specialty)Psychiatry

Résumé

récupéré en direct d'OpenAlex

To the Editor: Initial reports of the coronavirus disease 2019 (COVID-19) pandemic described a novel respiratory illness resembling severe acute respiratory syndrome (SARS) clustered around a market in Wuhan, China.1 Since then, there has been a surge of scientific inquiry into the spectrum of disease presentation; however, current case definitions still emphasize fever and respiratory symptoms as the primary presenting symptoms.2 A case we recently saw at Mount Sinai Hospital in Toronto, Canada, illustrates why this definition may be overly restrictive, particularly in older adults, and why clinicians should have a low threshold to consider COVID-19 when assessing older patients. An 83-year-old woman presented to an emergency department following an unwitnessed fall at home, with her only complaint being a vague sense of dizziness that developed that day. She had a medical history of hypertension, type 2 diabetes, and osteoporosis. At triage, she was screened for COVID-19 symptoms and was deemed low risk. She was afebrile and not hypoxic. As there was a question as to whether the fall had a syncopal origin, further investigations were completed. Computed tomography (CT) of the brain showed no infarct or hemorrhage. Cardiac telemetry showed normal sinus rhythm. CT pulmonary angiogram showed no evidence of pulmonary embolism; however, ground glass opacities were identified throughout both lungs. The findings were reported as being possibly consistent with COVID-19 pneumonia. A nasopharyngeal swab for SARS coronavirus 2 (SARS-CoV-2) was collected. She was placed on droplet-contact precautions and admitted to hospital. She soon developed hypoxia with a resting oxygen saturation of 87% and so was initiated on oxygen by nasal prongs. The following morning, her SARS-CoV-2 swab was confirmed positive. The local public health authority was notified, and her direct contacts were placed in self-isolation. She developed a fever of 38.7°C on day 2 of her admission. Laboratory investigations performed after admission revealed several abnormalities that have been previously described,3 including elevated d-dimer, ferritin, and C-reactive protein. She was admitted for 7 days in total. She was weaned off oxygen on day 5 and defervesced on day 6. Her dizziness, which has been described in COVID-19,4 resolved. No orthostatic hypotension5 was identified. Much of the attention regarding care of older adults with COVID-19 has focused on its significant mortality rate (reaching 10%-27% for those >85 years6) or the possible need for rationing of limited resources, such as ventilators. Characterizing the spectrum of illness in older adults with COVID-19 will be important, however, to guide policies, support effective prognostication and decision making, and ensure equitable access to care. Atypical presentation of illness is common in older adults. Symptoms, when present, may be nonspecific, with presentations including falls, delirium, or functional decline.7 Symptoms of chronic conditions may mask acute illness, and sensory or cognitive impairment may limit an older adult's ability to perceive or report symptoms. Signs such as fever may be diminished or absent.8 There is already evidence that screening based on typical symptoms alone, which failed in this case, is insufficient to identify COVID-19 in older adults.9, 10 This has significant implications for both clinical care and infection prevention and control, particularly in congregate living settings such as nursing homes, where frail older adults have experienced disproportionately high COVID-19–related morbidity and mortality. Given this, emerging recommendations are increasingly emphasizing the consideration of COVID-19 in older adults with any significant change from baseline.11 The threshold to test should also be low. In this case, testing was initiated because of an incidental finding on chest imaging. As testing capacity increases, criteria for testing should be continuously reevaluated to ensure timely identification of those infected with COVID-19. We thank the patient and her family for agreeing to share aspects of her story. The authors have no conflicts of interest to report. The authors are solely responsible for this content. Richard Norman prepared the original draft; Nathan Stall and Samir Sinha provided critical revisions and intellectual content. No funding was received for this work.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Étude de cas · Signal consensuel: Étude de cas
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,012

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,008
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,003
Science ouverte0,0020,001
Intégrité de la recherche0,0070,005
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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.

Tête enseignante Opus0,035
Tête enseignante GPT0,382
Écart entre enseignants0,347 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeÉtude de cas
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations48
Publié2020
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueJournal of the American Geriatrics SocietyMême sujetCOVID-19 Clinical Research StudiesTravaux en français237 207