Notice bibliographique
Résumé
Sir, Cancer is an important stroke etiology, and occult cancer may be often missed as stroke mechanisms in such cases are stamped as cryptogenic. In a group of patients with Embolic stroke of undetermined source (ESUS), 20% of patients had active cancer, and these patients had D-dimer levels twenty times higher compared to those without cancer.[1] The infarcts in these cases were in multiple vascular territories.[1] In fact, the “Three Territory Sign” is very specific for malignancy-related stroke and six times commoner than atrial fibrillation-related stroke.[2] One out of ten patients hospitalized with ischemic stroke in the United States had comorbid cancer.[3] If we detect cancer within a year after stroke, we may assume it to be present during the vascular event and might have a contribution towards it.[4] In a Canadian study involving 30,097 patients (age group 45–85 years), the diagnosis of cancer within the first year of a stroke was 2.4 times compared to individuals without stroke.[5] Patients aged between 15 and 49 years have up to fivefold increased chance of having cancer within first year of stroke diagnosis and incidence falls gradually with time (in a study from the Netherlands involving 390,398 patients).[6] In fact, arterial thromboembolism is commonly detected five months before cancer is diagnosed; with maximum incidence, a month before the detection of cancer.[7] Cancer patients have high chance of embolic stroke (detected by Transcranial Doppler) related to hypercoagulopathy, especially among those who do not have conventional stroke mechanism (CSM) and stamped as cryptogenic strokes compared to patients with CSM (57.9% vs 33.3%).[8] Interestingly, hypercoagulability is a double-eyed sword as it can also precipitate tumor growth and needs to be detected and treated at the earliest opportunity. Besides cancer-induced coagulopathy, cancer may speed up the CSMs. Mucin secreted into the bloodstream from adenocarcinoma provokes a coagulation cascade. Local infiltration of blood vessels occurs by tumor emboli or nonbacterial thrombotic endocarditis. Hyperleukocytosis in leukemia and hyperviscosity because of increased protein formation in multiple myeloma are other mechanisms. One out of four cancer patients are detected to have patent foramen ovale (PFO), while one out of five cancer patients have venous thromboembolism; thus, PFO and cancer are another important association.[6] Extracellular vesicles derived from cancer cells and NETosis markers were found prominently high in stroke patients with cancer.[1] Stroke among the young is on rise in every corner of the world and almost 50% of them are still cryptogenic. So, we need to search for markers of cancer-related stroke. Very high levels of D-Dimer, C-reactive protein (CRP), fibrinogen, cancer cell-derived extracellular vesicles, NETosis markers, micro-emboli (detection via Transcranial doppler [TCD]), and finally the presence of PFO in patients of cryptogenic stroke are probably such markers. Thus, when a patient comes with stroke (especially young), cancer needs to be ruled out even in the presence of conventional risk factors when the stroke mechanism remains undetermined. It will cause early detection of cancer and save precious time as we can intervene early. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 tête enseignante, 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 ».