Abstract P4-12-04: Healthcare utilization and symptoms among hospitalized patients with breast cancer
Notice bibliographique
Résumé
Abstract Background: Patients with breast cancer generally receive most of their care in an outpatient setting, but unplanned hospitalizations may occur to help manage uncontrolled symptoms. We sought to investigate healthcare utilization and symptoms among patients with breast cancer experiencing an unplanned hospitalization. Methods: We enrolled patients with cancer and unplanned hospitalizations from 9/2014 to 2/2017. The current study focuses on the patients with breast cancer in this cohort. Following hospital admission, we assessed patient-reported symptoms using the Edmonton Symptom Assessment System (ESAS). We reviewed the electronic health record to obtain information about patient demographics, clinical characteristics, healthcare utilization, and reasons for hospital admission (elicited from primary and secondary diagnoses listed on the hospitalization discharge summary). We examined the associations among patients’ symptoms, healthcare utilization (i.e., hospital length of stay and 90-day readmissions), and survival using regression models. Results: We identified 101 patients with breast cancer (median age=60 years [range 22-86]. In this cohort, 74% had metastatic breast cancer. Primary/secondary reasons for hospitalization included fever/infection (34%), pain (18%), dyspnea (12%), gastrointestinal diagnoses (constipation, diarrhea, bowel obstruction, biliary obstruction, ascites, 10%), nausea/vomiting (7%), failure to thrive (6%), pleural effusion (5%), renal failure (4%), blood clot (3%), cardiac diagnoses (atrial fibrillation, cardiomyopathy, 3%), lightheadedness/hypotension (3%), neurologic diagnoses (altered mental status, seizure, subdural hematoma, 3%), fracture (2%), lower extremity swelling (2%), and other (i.e., rash, ptosis, SVC syndrome, fall, 1% each). Table 1 describes the baseline ESAS symptoms collected upon hospital admission. The mean length of hospital stay was 6.2 days and 90-day readmission rates were 28%. Patient disposition post hospitalization included discharge to home (76%), post-acute care facility (12%), hospice (5%), and death in the hospital (6%). We found that patients’ ESAS-physical symptoms were associated with longer hospital length of stay (B=0.08, p=0.029), greater risk of death or readmission within 90-days (OR=1.07, p<0.001), and worse overall survival (HR=1.04, p=0.001). Similarly, patients’ ESAS-total symptoms were associated with longer hospital length of stay (B=0.07, p=0.013), greater risk of death or readmission within 90-days (OR=1.05, p=0.001), and worse overall survival (HR=1.02, p=0.003). Conclusions: In this cohort of hospitalized patients with breast cancer, the majority had metastatic disease and presented with a high symptom burden. Unplanned admissions in these patients with breast cancer commonly occurred for fever/infection, pain, dyspnea, and gastrointestinal reasons. We identified novel associations among patients’ symptoms upon admission with their hospital length of stay, risk of readmissions/death, and overall survival. These findings highlight the need for timely outpatient interventions that address patient symptoms when seeking to enhance health care utilization and survival outcomes in this population. Table 1.Baseline symptom% of patients with moderate or severe symptomsMedian ESAS scoreTiredness*90%8 (Severe)Pain*78%7 (Severe)Well-being76%5 (Moderate)Drowsiness*71%6 (Moderate)Lack of appetite*68%5 (Moderate)Anxiety61%5 (Moderate)Depression52%4 (Moderate)Nausea*45%2 (Mild)Shortness of breath*45%2 (Mild)Constipation*44%0 (None)Total ESAS scoreMedian score 47 Total ESAS_physical score. . Median score 34*components included in ESAS_physical score Citation Format: Neelima Vidula, Emilia Kaslow-Zieve, Carolyn Qian, Isabel Neckermann, Eva Gaufberg, Charu Vyas, Richard Newcomb, Patrick C Johnson, Daniel Lage, Jennifer Shin, Ryan Nipp. Healthcare utilization and symptoms among hospitalized patients with breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-12-04.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».