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Advancing the integration of biosignal-based automated pain assessment methods into a comprehensive model for addressing cancer pain.
Cascella, Marco; Di Gennaro, Piergiacomo; Crispo, Anna; Vittori, Alessandro; Petrucci, Emiliano; Sciorio, Francesco; Marinangeli, Franco; Ponsiglione, Alfonso Maria; Romano, Maria; Ovetta, Concetta; Ottaiano, Alessandro; Sabbatino, Francesco; Perri, Francesco; Piazza, Ornella; Coluccia, Sergio.
Afiliación
  • Cascella M; Department of Medicine, Surgery and Dentistry, Anesthesia and Pain Medicine, University of Salerno, Via Salvador Allende 43, Baronissi Salerno, 84081, Italy.
  • Di Gennaro P; Epidemiology and Biostatistics Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Via Mariano Semmola 53, Naples, 80131, Italy.
  • Crispo A; Epidemiology and Biostatistics Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Via Mariano Semmola 53, Naples, 80131, Italy.
  • Vittori A; Department of Anesthesia and Critical Care, ARCO Roma, Ospedale Pediatrico Bambino Gesù IRCCS, Piazza S. Onofrio 4, Rome, 00165, Italy. alexvittori82@gmail.com.
  • Petrucci E; Department of Anesthesia and Intensive Care Unit, San Salvatore Academic Hospital of L'Aquila, Via Lorenzo Natali, 1, Coppito L'Aquila, 67100, Italy.
  • Sciorio F; Department of Anesthesiology, Intensive Care and Pain Treatment, University of L'Aquila, Piazzale Salvatore Tommasi, 1,, Coppito, AQ, 67100, Italy.
  • Marinangeli F; Department of Anesthesiology, Intensive Care and Pain Treatment, University of L'Aquila, Piazzale Salvatore Tommasi, 1,, Coppito, AQ, 67100, Italy.
  • Ponsiglione AM; Department of Information Technology and Electrical Engineering, University of Naples Federico II, Corso Umberto I, 40, Napoles, 80138, Italy.
  • Romano M; Department of Information Technology and Electrical Engineering, University of Naples Federico II, Corso Umberto I, 40, Napoles, 80138, Italy.
  • Ovetta C; Department of Information Technology and Electrical Engineering, University of Naples Federico II, Corso Umberto I, 40, Napoles, 80138, Italy.
  • Ottaiano A; SSD Innovative Therapies for Abdominal Metastases, Abdominal Oncology, INT IRCCS Foundation "G. Pascale", Via Mariano Semmola 53, Naples, 80131, Italy.
  • Sabbatino F; Department of Medicine, Surgery and Dentistry, Oncology Unit, University of Salerno, Via Salvador Allende 43, Baronissi Salerno, 84081, Italy.
  • Perri F; Medical and Experimental Head and Neck Oncology Unit, Istituto Nazionale Tumori - IRCCS Fondazione G. Pascale, Via Mariano Semmola 53, Naples, 80131, Italy.
  • Piazza O; Department of Medicine, Surgery and Dentistry, Anesthesia and Pain Medicine, University of Salerno, Via Salvador Allende 43, Baronissi Salerno, 84081, Italy.
  • Coluccia S; Epidemiology and Biostatistics Unit, Istituto Nazionale Tumori, IRCCS Fondazione G. Pascale, Via Mariano Semmola 53, Naples, 80131, Italy.
BMC Palliat Care ; 23(1): 198, 2024 Aug 03.
Article en En | MEDLINE | ID: mdl-39097739
ABSTRACT

BACKGROUND:

Tailoring effective strategies for cancer pain management requires a careful analysis of multiple factors that influence pain phenomena and, ultimately, guide the therapy. While there is a wealth of research on automatic pain assessment (APA), its integration with clinical data remains inadequately explored. This study aimed to address the potential correlations between subjective and APA-derived objectives variables in a cohort of cancer patients.

METHODS:

A multidimensional statistical approach was employed. Demographic, clinical, and pain-related variables were examined. Objective measures included electrodermal activity (EDA) and electrocardiogram (ECG) signals. Sensitivity analysis, multiple factorial analysis (MFA), hierarchical clustering on principal components (HCPC), and multivariable regression were used for data analysis.

RESULTS:

The study analyzed data from 64 cancer patients. MFA revealed correlations between pain intensity, type, Eastern Cooperative Oncology Group Performance status (ECOG), opioids, and metastases. Clustering identified three distinct patient groups based on pain characteristics, treatments, and ECOG. Multivariable regression analysis showed associations between pain intensity, ECOG, type of breakthrough cancer pain, and opioid dosages. The analyses failed to find a correlation between subjective and objective pain variables.

CONCLUSIONS:

The reported pain perception is unrelated to the objective variables of APA. An in-depth investigation of APA is required to understand the variables to be studied, the operational modalities, and above all, strategies for appropriate integration with data obtained from self-reporting. TRIAL REGISTRATION This study is registered with ClinicalTrials.gov, number (NCT04726228), registered 27 January 2021, https//classic. CLINICALTRIALS gov/ct2/show/NCT04726228?term=nct04726228&draw=2&rank=1.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Dimensión del Dolor / Dolor en Cáncer Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Palliat Care Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Dimensión del Dolor / Dolor en Cáncer Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Palliat Care Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Reino Unido