An Algorithm for Neuropathic Pain Management in Older People.

Neuropathic pain frequently affects older people, who generally also have several comorbidities. Elderly patients are often poly-medicated, which increases the risk of drug-drug interactions. These patients, especially those with cognitive problems, may also have restricted communication skills, making pain evaluation difficult and pain treatment challenging. Clinicians and other healthcare providers need a decisional algorithm to optimize the recognition and management of neuropathic pain. We present a decisional algorithm developed by a multidisciplinary group of experts, which focuses on pain assessment and therapeutic options for the management of neuropathic pain, particularly in the elderly. The algorithm involves four main steps: (1) detection, (2) evaluation, (3) treatment, and (4) re-evaluation. The detection of neuropathic pain is an essential step in ensuring successful management. The extent of the impact of the neuropathic pain is then assessed, generally with self-report scales, except in patients with communication difficulties who can be assessed using behavioral scales. The management of neuropathic pain frequently requires combination treatments, and recommended treatments should be prescribed with caution in these elderly patients, taking into consideration their comorbidities and potential drug-drug interactions and adverse events. This algorithm can be used in the management of neuropathic pain in the elderly to ensure timely and adequate treatment by a multidisciplinary team.

Validation of an acute pain-behavior scale for older persons with inability to communicate verbally: Algoplus.

To compensate for poor acute pain detection in elderly inpatients with inability to communicate verbally (ICV), the Doloplus Collective team devised the 5-item Algoplus behavior-assessment scale specifically aimed at quickly detecting acute pain in these individuals. Algoplus was developed in three successive phases, including expert opinions, caregivers interviews, patient video recordings and statistical procedures. Among the 1500 recorded primary pain behaviors, 48 were selected and clustered into a 5-item scale. This version was validated based on 349 old inpatients (204 with acute pain and 145 without) from different care settings and hospitals. Comparators were objective acute pain clinical situations, experts' clinical judgment on acute pain presence, and self-rating scales (Visual Analog Scale, Numeric Rating Scale and Verbal Descriptor Scale) for a communicative subsample (n=134). Algoplus showed good discriminant validity with adequate internal consistency (Kuder-Richardson-20, 0.712), excellent interrater reliability (intraclass coefficient, 0.812) and high sensitivity to change during specific pain situations and after starting pain management. Excellent correlations were observed between Algoplus and experts' clinical judgment, acute pain clinical situations or each comparator self-rating-pain score. For patients with acute pain conditions, a score ⩾2 out of 5 on the Algoplus scale was retained as the threshold for the presence of acute pain in elderly ICV inpatients, with 87% sensitivity and 80% specificity. In addition, the very brief rating time of ∼1min is particularly relevant in acute-care settings, where repetitive pain-monitoring is required.