Evidence map›Paper›PMID 37597075›Full record

Observational studyEuropean geriatric medicine2023

Use of a clustering method to describe the clinical profiles of older fallers: the value of a multidisciplinary consultation.

M Pambet, J B Gauvain, A Valery, C Annweiler, S Mandigout, B Fougere, F Puisieux

Abstract readObservational StudyMulticenter Study
PubMed Publisher
In one paragraph

Observational study in European geriatric medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 1 country.

M PambetCourt Séjour Gériatrique, Department of Medicine, CHR d'Orléans, 14 Av. de l'Hôpital, 45067, Orleans, France.
J B GauvainCourt Séjour Gériatrique, Department of Medicine, CHR d'Orléans, 14 Av. de l'Hôpital, 45067, Orleans, France.
A ValeryCourt Séjour Gériatrique, Department of Medicine, CHR d'Orléans, 14 Av. de l'Hôpital, 45067, Orleans, France.
C AnnweilerDepartment of Geriatric Medicine, Centre de Recherche sur l'Autonomie et la Longévité (CeRAL), UPRES EA 4638, UNAM, Université d'Angers, 4 rue Larrey, 49933, Angers, France.
S MandigoutHAVAE, UR20217, University of Limoges, F-87000, Limoges, France. stephane.mandigout@unilim.fr.ORCID 0000-0003-2072-3022
B FougereDepartment of Geriatric Medicine and Pôle Vieillissement, Université de Tours, 2 boulevard tonnellé, 37044, Tours, France.
F PuisieuxClinique de gérontologie et service de médecine interne et gériatrie, Hôpital gériatrique les Bateliers, Université de Lille, 23 Rue des Bateliers, 59037, Lille, France.
Centre hospitalier universitaire d'Orléans · FRLaboratoire Angevin de Recherche en Mathématiques · FRUniversité de Lille · FRUniversité de Limoges · FRUniversité de Tours · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe population of older adults is particularly heterogeneous with regard to frailty and the risk of falling, the two of which are linked. We conducted an exploratory, analysis (with no preconceived ideas) of data collected during multidisciplinary falls consultations (MFCs), to identify people with similar profiles. MATERIALS AND

methodsWe performed an observational, multicentre study of older patients (aged 75 and over) having been evaluated in an MFC. We excluded adults with a Mini Mental State Examination score < 14/30, an activities of daily living score < 4/6, or an unstable medical condition. Each participant underwent a clinical interview, impedancemetry, and a physical activity assessment (a questionnaire, and use of an activity tracker on 5 consecutive days). The K-means method and ascending hierarchical clustering were used to identify clusters of people with common characteristics.

resultsOf the 106 participants, the median [IQR] mean number of falls in the previous 6 months was 1 [2]. Three functional clusters were identified: (i) fallers with poor mobility, difficulty getting up off the ground after a fall, and using a mobility aid for walking; (ii) an intermediate sedentary group with a gait speed of ~ 0.6 m s

conclusionsThe population of older fallers referred for an MFC is heterogeneous. The presence of certain clinical characteristics enabled the definition of three patient clusters, which might help physicians to determine the most appropriate care objectives and pathways.

Indexed as

Accidental FallsFrailtyGeriatric AssessmentReferral and ConsultationActivities of Daily LivingAgedAged, 80 and overCluster AnalysisFemaleFrail ElderlyHumansMaleMobility LimitationRisk FactorsClusteringFallsFrailtyGait speedPhysical inactivity

Identifiers

PMID37597075
OpenAlexW4386001116

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.