1
|
Sabater-Gárriz Á, Molina-Mula J, Montoya P, Riquelme I. Pain assessment tools in adults with communication disorders: systematic review and meta-analysis. BMC Neurol 2024; 24:66. [PMID: 38368314 PMCID: PMC10873938 DOI: 10.1186/s12883-024-03539-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/15/2024] [Indexed: 02/19/2024] Open
Abstract
BACKGROUND Verbal communication is the "gold standard" for assessing pain. Consequently, individuals with communication disorders are particularly vulnerable to incomplete pain management. This review aims at identifying the current pain assessment instruments for adult patients with communication disorders. METHODS A systematic review with meta-analysis was conducted on PubMed, PEDRO, EBSCOhost, VHL and Cochrane databases from 2011 to 2023 using MeSH terms "pain assessment, "nonverbal communication" and "communication disorders" in conjunction with additional inclusion criteria: studies limited to humans, interventions involving adult patients, and empirical investigations. RESULTS Fifty articles were included in the review. Seven studies report sufficient data to perform the meta-analysis. Observational scales are the most common instruments to evaluate pain in individuals with communication disorders followed by physiological measures and facial recognition systems. While most pain assessments rely on observational scales, current evidence does not strongly endorse one scale over others for clinical practice. However, specific observational scales appear to be particularly suitable for identifying pain during certain potentially painful procedures, such as suctioning and mobilization, in these populations. Additionally, specific observational scales appear to be well-suited for certain conditions, such as mechanically ventilated patients. CONCLUSIONS While observational scales dominate pain assessment, no universal tool exists for adults with communication disorders. Specific scales exhibit promise for distinct populations, yet the diverse landscape of tools hampers a one-size-fits-all solution. Crucially, further high-quality research, offering quantitative data like reliability findings, is needed to identify optimal tools for various contexts. Clinicians should be informed to select tools judiciously, recognizing the nuanced appropriateness of each in diverse clinical situations. TRIAL REGISTRATION This systematic review is registered in PROSPERO (International prospective register of systematic reviews) with the ID: CRD42022323655 .
Collapse
Affiliation(s)
- Álvaro Sabater-Gárriz
- Balearic ASPACE Foundation, Marratxí, Spain
- Department of Nursing and Physiotherapy, University of Balearic Islands, Palma, 07122, Spain
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma, 07122, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma, 07010, Spain
| | - Jesús Molina-Mula
- Department of Nursing and Physiotherapy, University of Balearic Islands, Palma, 07122, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma, 07010, Spain
| | - Pedro Montoya
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma, 07122, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma, 07010, Spain
| | - Inmaculada Riquelme
- Department of Nursing and Physiotherapy, University of Balearic Islands, Palma, 07122, Spain.
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma, 07122, Spain.
- Health Research Institute of the Balearic Islands (IdISBa), Palma, 07010, Spain.
| |
Collapse
|
2
|
Sabater-Gárriz Á, Gaya-Morey FX, Buades-Rubio JM, Manresa-Yee C, Montoya P, Riquelme I. Automated facial recognition system using deep learning for pain assessment in adults with cerebral palsy. Digit Health 2024; 10:20552076241259664. [PMID: 38846372 PMCID: PMC11155325 DOI: 10.1177/20552076241259664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 05/07/2024] [Indexed: 06/09/2024] Open
Abstract
Objective Assessing pain in individuals with neurological conditions like cerebral palsy is challenging due to limited self-reporting and expression abilities. Current methods lack sensitivity and specificity, underlining the need for a reliable evaluation protocol. An automated facial recognition system could revolutionize pain assessment for such patients.The research focuses on two primary goals: developing a dataset of facial pain expressions for individuals with cerebral palsy and creating a deep learning-based automated system for pain assessment tailored to this group. Methods The study trained ten neural networks using three pain image databases and a newly curated CP-PAIN Dataset of 109 images from cerebral palsy patients, classified by experts using the Facial Action Coding System. Results The InceptionV3 model demonstrated promising results, achieving 62.67% accuracy and a 61.12% F1 score on the CP-PAIN dataset. Explainable AI techniques confirmed the consistency of crucial features for pain identification across models. Conclusion The study underscores the potential of deep learning in developing reliable pain detection systems using facial recognition for individuals with communication impairments due to neurological conditions. A more extensive and diverse dataset could further enhance the models' sensitivity to subtle pain expressions in cerebral palsy patients and possibly extend to other complex neurological disorders. This research marks a significant step toward more empathetic and accurate pain management for vulnerable populations.
Collapse
Affiliation(s)
- Álvaro Sabater-Gárriz
- Department of Research and Training, Balearic ASPACE Foundation, Marratxí, Spain
- Department of Nursing and Physiotherapy, University of the Balearic Islands, Palma de Mallorca, Spain
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma de Mallorca, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| | - F Xavier Gaya-Morey
- Department of Mathematics and Computer Science, University of the Balearic Islands, Palma de Mallorca, Spain
| | - José María Buades-Rubio
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma de Mallorca, Spain
- Department of Mathematics and Computer Science, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Cristina Manresa-Yee
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma de Mallorca, Spain
- Department of Mathematics and Computer Science, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Pedro Montoya
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma de Mallorca, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
- Center for Mathematics, Computation and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
| | - Inmaculada Riquelme
- Department of Nursing and Physiotherapy, University of the Balearic Islands, Palma de Mallorca, Spain
- Research Institute on Health Sciences (IUNICS), University of the Balearic Islands, Palma de Mallorca, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
| |
Collapse
|
3
|
Wojnar-Gruszka K, Sega A, Płaszewska-Żywko L, Wojtan S, Potocka M, Kózka M. Pain Assessment with the BPS and CCPOT Behavioral Pain Scales in Mechanically Ventilated Patients Requiring Analgesia and Sedation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10894. [PMID: 36078609 PMCID: PMC9517797 DOI: 10.3390/ijerph191710894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/19/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Intensive Care Unit (ICU) patients often experience pain, especially during diagnostic, nursing, and therapeutic interventions. Pain assessment using the Behavioral Pain Scale (BPS) and Critical Care Pain Observation Tool (CCPOT) are recommended, but they are difficult to do in patients undergoing deep sedation. This study analyzed the usefulness of the BPS and CCPOT scales in assessing pain among patients with varying degrees of sedation. METHODS In 81 mechanically ventilated and sedated ICU patients, 1005 measurements were performed using the BPS and CCPOT scales. The study was conducted by 3 trained observers 3 times a day (each measurement at rest, during painful nursing interventions, and after the intervention). The Richmond Agitation-Sedation Scale (RASS), the Simplified Acute Physiology Score (SAPS II), and the Acute Physiology and Chronic Health Evaluation (APACHE II) were also analyzed from medical records as well as information on the length of hospitalization and treatment. RESULTS It was shown that signs of pain increased significantly (p < 0.001) during interventions in patients on both scales (BPS and CCPOT), and then returned to values close to the resting period. RASS results correlated significantly (p < 0.05) and positively with the results of the BPS and CCPOT. A strong correlation was found between the results of both scales at each stage of the study (R = 0.622-0.907). CONCLUSIONS Nursing procedures are a source of pain in analgosedated patients. The BPS and CCPOT scales are useful tools for assessing the occurrence of pain in mechanically ventilated patients, including those in deep sedation.
Collapse
Affiliation(s)
- Katarzyna Wojnar-Gruszka
- Department of Clinical Nursing, Faculty of Health Sciences, Collegium Medicum, Jagiellonian University, 31-501 Kraków, Poland
| | - Aurelia Sega
- Department of Clinical Nursing, Faculty of Health Sciences, Collegium Medicum, Jagiellonian University, 31-501 Kraków, Poland
| | - Lucyna Płaszewska-Żywko
- Department of Clinical Nursing, Faculty of Health Sciences, Collegium Medicum, Jagiellonian University, 31-501 Kraków, Poland
| | - Stanisław Wojtan
- Department of Clinical Nursing, Faculty of Health Sciences, Collegium Medicum, Jagiellonian University, 31-501 Kraków, Poland
- Department of Anaesthesiology and Intensive Therapy, University Hospital in Kraków, 30-688 Kraków, Poland
| | - Marcelina Potocka
- Department of Clinical Nursing, Faculty of Health Sciences, Collegium Medicum, Jagiellonian University, 31-501 Kraków, Poland
| | - Maria Kózka
- Department of Clinical Nursing, Faculty of Health Sciences, Collegium Medicum, Jagiellonian University, 31-501 Kraków, Poland
| |
Collapse
|
4
|
Ozga D, Krupa S, Witt P, Mędrzycka-Dąbrowska W. Nursing Interventions to Prevent Delirium in Critically Ill Patients in the Intensive Care Unit during the COVID19 Pandemic-Narrative Overview. Healthcare (Basel) 2020; 8:healthcare8040578. [PMID: 33371277 PMCID: PMC7766119 DOI: 10.3390/healthcare8040578] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/11/2020] [Accepted: 12/13/2020] [Indexed: 01/08/2023] Open
Abstract
It has become a standard measure in recent years to utilise evidence-based practice, which is associated with a greater need to implement and use advanced, reliable methods of summarising the achievements of various scientific disciplines, including such highly specialised approaches as personalised medicine. The aim of this paper was to discuss the current state of knowledge related to improvements in "nursing" involving management of delirium in intensive care units during the SARS-CoV-2 pandemic. This narrative review summarises the current knowledge concerning the challenges associated with assessment of delirium in patients with COVID-19 by ICU nurses, and the role and tasks in the personalised approach to patients with COVID-19.
Collapse
Affiliation(s)
- Dorota Ozga
- Institute of Health Sciences, Medical College of Rzeszow University, 35-310 Rzeszow, Poland; (D.O.); (S.K.)
| | - Sabina Krupa
- Institute of Health Sciences, Medical College of Rzeszow University, 35-310 Rzeszow, Poland; (D.O.); (S.K.)
| | - Paweł Witt
- Department of Pediatric Anesthesiology and Intensive Care, Medical University of Warsaw, 02-091 Warszawa, Poland;
| | - Wioletta Mędrzycka-Dąbrowska
- Department of Anaesthesiology Nursing & Intensive Care, Medical University in Gdansk, 80-211 Gdańsk, Poland
- Correspondence:
| |
Collapse
|
5
|
Gélinas C, Joffe AM, Szumita PM, Payen JF, Bérubé M, Shahiri T S, Boitor M, Chanques G, Puntillo KA. A Psychometric Analysis Update of Behavioral Pain Assessment Tools for Noncommunicative, Critically Ill Adults. AACN Adv Crit Care 2020; 30:365-387. [PMID: 31951666 DOI: 10.4037/aacnacc2019952] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
This is an updated, comprehensive review of the psychometric properties of behavioral pain assessment tools for use with noncommunicative, critically ill adults. Articles were searched in 5 health databases. A total of 106 articles were analyzed, including 54 recently published papers. Nine behavioral pain assessment tools developed for noncommunicative critically ill adults and 4 tools developed for other non-communicative populations were included. The scale development process, reliability, validity, feasibility, and clinical utility were analyzed using a 0 to 20 scoring system, and quality of evidence was also evaluated. The Behavioral Pain Scale, the Behavioral Pain Scale-Nonintubated, and the Critical-Care Pain Observation Tool remain the tools with the strongest psychometric properties, with validation testing having been conducted in multiple countries and various languages. Other tools may be good alternatives, but additional research on them is necessary.
Collapse
Affiliation(s)
- Céline Gélinas
- Céline Gélinas is Associate Professor, Ingram School of Nursing, McGill University, 680 Sherbrooke West, Room 1838, Montréal, Québec, Canada, H3A 2M7; and Researcher, Centre for Nursing Research and Lady Davis Institute, Jewish General Hospital, Montréal, Québec, Canada
| | - Aaron M Joffe
- Aaron M. Joffe is Professor, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington
| | - Paul M Szumita
- Paul M. Szumita is Clinical Pharmacy Practice Manager and Program Director - PGY2 Critical Care Pharmacy Practice Residency, Department of Pharmacy Services, Brigham and Women's Hospital, Boston, Massachusetts
| | - Jean-Francois Payen
- Jean-Francois Payen is Professor, Department of Anesthesiology and Critical Care, and Researcher, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble Alpes University Hospital, Grenoble, France
| | - Mélanie Bérubé
- Mélanie Bérubé is Assistant Professor, Faculty of Nursing, Université Laval; and Researcher, CHU de Québec, Université Laval Research Center (Hôpital de l'Enfant-Jésus), Québec City, Québec, Canada
| | - Shiva Shahiri T
- Shiva Shahiri T is a PhD Student, Ingram School of Nursing, McGill University
| | - Madalina Boitor
- Madalina Boitor is a Student, Faculty of Dentistry, McGill University
| | - Gerald Chanques
- Gerald Chanques is Professor, Department of Anesthesia & Critical Care Medicine, Montpellier University Hospital Saint Eloi, and PhyMedExp, University of Montpellier, INSERM, CNRS, 34295 Montpellier cedex 5, France
| | - Kathleen A Puntillo
- Kathleen A. Puntillo is Professor of Nursing Emeritus, University of California San Francisco School of Nursing, San Francisco, California
| |
Collapse
|