The aim of this study was to assess the predictive ability of the frailty phenotype (FP), Groningen Frailty Indicator (GFI), Tilburg Frailty Indicator (TFI) and frailty index (FI) for the outcomes mortality, hospitalization and increase in dependency in (instrumental) activities of daily living ((I)ADL) among older persons. This prospective cohort study with 2-year follow-up included 2420 Dutch community-dwelling older people (65+, mean age 76.3±6.6 years, 39.5% male) who were pre-frail or frail according to the FP. Mortality data were obtained from Statistics Netherlands. All other data were self-reported. Area under the receiver operating characteristic curves (AUC) was calculated for each frailty instrument and outcome measure. The prevalence of frailty, sensitivity and specifcity were calculated using cutoff values proposed by the developers and cutoff values one above and one below the proposed ones (0.05 for FI). All frailty instruments poorly predicted mortality, hospitalization and (I)ADL dependency (AUCs between 0.62–0.65, 0.59–0.63 and 0.60–0.64, respectively). Prevalence estimates of frailty in this population varied between 22.2% (FP) and 64.8% (TFI). The FP and FI showed higher levels of specifcity, whereas sensitivity was higher for the GFI and TFI. Using a different cutoff point considerably changed the prevalence, sensitivity and specifcity. In conclusion, the predictive ability of the FP, GFI, TFI and FI was poor for all outcomes in a population of pre-frail and frail community-dwelling older people. The FP and the FI showed higher values of specifcity, whereas sensitivity was higher for the GFI and TFI.
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Abstract Objective: To determine the associations between four validated multidimensional self-report frailty scales and nine indices of oral health in communitydwelling older persons. Materials and Methods: This pilot study was conducted in a sample of 208 older persons aged 70 years and older who visited two dental practices in the Netherlands. Frailty status was measured by four different self-report frailty questionnaires: Tilburg Frailty Indicator (TFI), Groningen Frailty Indicator (GFI), Sunfrail Checklist (SC), and the Sherbrooke Postal Questionnaire (SPQ). Oral health was assessed by two calibrated examiners. Results: The prevalence of frailty according to the four frailty measures TFI, GFI, SC, and SPQ was 32.8%, 31.5%, 24.5%, and 49.7%, respectively. The SC correlated with four oral health variables (DMFT, number of teeth, percentage of occlusal contacts, Plaque Index), the TFI with three (number of teeth, percentage of occlusal contacts, Plaque Index), the GFI only with DPSI, and the SPQ with the number of teeth and the number of occlusal contacts. Conclusion: Of the studiedmultidimensional frailty scales, the SC and TFIwere correlated with most oral health variables (four and three, respectively). However, it should be noticed that these correlations were small. Clinical relevance: The SCand TFImight help to identify older people with risk of poor oral health so that preventive care can be used to ensure deterioration of oral health and maintenance of quality of life. Vice versa early detection of frailty by oral care professionals could contribute to interprofessional management of frailty.
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Background: In frail older people with natural teeth factors like polypharmacy, reduced salivary flow, a decrease of oral self-care, general healthcare issues, and a decrease in dental care utilization contribute to an increased risk for oral complications. On the other hand, oral morbidity may have a negative impact on frailty. Objective: This study explored associations between oral health and two frailty measures in community-dwelling older people. Design: A cross-sectional study. Setting: The study was carried out in a Primary Healthcare Center (PHC) in The Netherlands. Participants: Of the 5,816 persons registered in the PHC, 1,814 persons were eligible for participation at the start of the study. Measurements: Two frailty measures were used: 1. Being at risk for frailty, using Electronical Medical Record (EMR) data, and: 2. Survey-based frailty using ‘The Groningen Frailty Indicator’ (GFI). For oral health measures, dental-record data (dental care utilization, dental status, and oral health information) and self-reported oral problems were recorded. Univariate regression analyses were applied to determine the association between oral health and frailty, followed by age- and sex-adjusted multivariate logistic regressions. Results: In total 1,202 community-dwelling older people were included in the study, 45% were male and the mean age was 73 years (SD=8). Of all participants, 53% was at risk for frailty (638/1,202), and 19% was frail based on the GFI (222/1,202). A dental emergency visit (Odds Ratio (OR)= 2.0, 95% Confidence Interval (CI)=1.33;3.02 and OR=1.58, 95% CI=1.00;2.49), experiencing oral problems (OR=2.07, 95% CI=1.52;2.81 and OR=2.87, 95% CI= 2.07;3.99), and making dietary adaptations (OR=2.66, 95% CI=1.31;5.41 and OR=5.49, 95% CI= 3.01;10.01) were associated with being at risk for frailty and surveybased frailty respectively. Conclusions: A dental emergency visit and self-reported oral health problems are associated with frailty irrespective of the approach to its measurement. Healthcare professionals should be aware of the associations of oral health and frailty in daily practice.
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Restrictive measures due to the COVID-19 pandemic may cause problems in the physical, social, and psychological functioning of older people, resulting in increased frailty. In this cross-sectional study, we aimed to assess the prevalence and characteristics of frailty, to examine differences in perceived COVID-19-related concerns and threats between frail and non-frail people and to identify variables associated with frailty in the first wave of the COVID-19 pandemic, in Dutch older people aged ≥ 65 years. We used data from the Lifelines COVID-19 Cohort Study. The Groningen Frailty Indicator (GFI) was used, with a score ≥ 4 indicating frailty. Frailty was described per domain (i.e., physical, cognitive, social, and psychological). The association between demographic, health and lifestyle variables and frailty was determined with logistic regression analyses. Frailty was present in 13% of the 11,145 participants that completed the GFI. Most items contributing to a positive frailty score were found within the social domain, in the frail (51%) and the non-frail (59%) persons. For items related to concerns and threats, a significantly higher proportion of frail people reported being worried or feeling threatened. In conclusion, during Corona restrictions, prevalence of frailty was considerable in older people from the Northern Netherlands, with one in eight being frail. Frailty was characterized by social problems and frail people were more often worried and felt threatened by the COVID-19 pandemic.
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Rationale: Lean body mass, including muscle, is known to decrease with age, which may contribute to loss of physical function, an indicator of frailty. Moreover, low muscle thickness is considered an indicator of frailty in critically ill patients. However, little is known about the relationship between muscle thickness and frailty in community dwelling adults. Therefore, we studied the association between frailty and whole body lean body mass index (LBMi) and muscle thickness of the rectus femoris (RF) in community dwelling older adults. Methods: In older adults aged ≥55y, who participated in the Hanze Health and Ageing Study, frailty status was assessed with a multidimensional instrument, measuring frailty on a cognitive, psychosocial en physical level, i.e., the Groningen Frailty Indicator (GFI), using ≥4 as cut-off score for frailty. LBMi (kg/m2) was estimated with BIA (Quadscan 4000©, Bodystat), using the build-in equation. Muscle thickness (mm) of the RF was measured with ultrasound, using the Bodymetrix© (Intelametrix). Univariate and multivariate binary logistic regression analyses were performed for LBMi and for RF thickness. Multivariate analysis corrected for age, sex, body mass index (kg/m2), and handgrip strength (handgrip dynamometer; kg). A p-level of <0.05 was considered significant and Odds Ratios (OR; [95% CI]) were presented. Results: 93 participants (age 65.2±7.7 years; male 46 %; LBMi 17.2±2.6 kg/m2; RF 14.6±4.4 mm; median GFI =1 (interquartile range=0-3; frail: n=18) were included in the analysis. In both the univariate and multivariate analysis, LBMi (p=0.082, OR=0.82 [0.66-1.03]; p=0.077, OR=0.55 [0.28-1.07] respectively) and muscle thickness of RF (p=0.436, OR=0.95 [0.84-1.08]; p=0.796, OR= 1.02 [0.88-1.18] respectively) were not significantly associated with frailty. None of the co-variables were significantly associated with frailty either. Conclusion: In this sample of older adults aged ≥55 years, LBMi and RF thickness are not associated with frailty. However, frail participants scored at cut-off or just above, and measurements in a population with higher scores for frailty may provide further insight in the association between lean body mass and muscle thickness and frailty.
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Purpose Pre-stroke frailty in older adults is associated with adverse outcomes after stroke in community-based and hospitalbased populations. The aim of our study was to investigate the prevalence of pre-stroke frailty among older stroke survivors receiving medical specialistic rehabilitation and its association with outcomes and recovery. Methods Pre-stroke frailty was measured by the Groningen Frailty Indicator (GFI, score ≥ 4 indicates frailty) in patients≥65 years receiving stroke medical specialistic rehabilitation. Baseline, follow-up and change (i.e. recovery) scores of the Barthel index (BI), Stroke Impact Scale (SIS) ‘mobility’, ‘communication’, and ‘memory and thinking’, Hospital Anxiety and Depression Scale (HADS) and the EuroQoL-5 dimensions (EQ-5D) were compared between frail and non-frail patients with a multivariable regression model adjusting for confounders. Results Of 322 included patients (34.2% females, median age 70 years), 43 (13.4%) patients reported pre-stroke frailty. There were no diferences in BI or in destination of discharge between pre-stroke frail and non-frail stroke survivors receiving inpatient rehabilitation. However, pre-stroke frailty was associated with worse follow-up scores for all other measures. Recovery in pre-stroke frail patients was less favorable compared to non-frail patients for SIS mobility, HADS subscales and EQ-5D index and visual analogue scale. Conclusion Pre-stroke frailty was present in a minority of older stroke survivors receiving medical specialistic rehabilitation. BI and destination of discharge did not difer. Nevertheless, pre-stroke frailty was associated with worse functioning at follow-up for most measures of health status and with smaller improvements in mobility, mood and quality of life.
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BACKGROUND: Due to the rapidly increasing number of older people worldwide, the prevalence of frailty among older adults is expected to escalate in coming decades. It is crucial to recognize early onset symptoms to initiate specific preventive care. Therefore, early detection of frailty with appropriate screening instruments is needed. The aim of this study was to evaluate the underlying dimensionality of the Groningen Frailty Indicator (GFI), a widely used self-report screening instrument for identifying frail older adults. In addition, criterion validity of GFI subscales was examined and composition of GFI scores was evaluated.METHODS: A cross-sectional study design was used to evaluate the structural validity, internal consistency and criterion validity of the GFI questionnaire in older adults aged 65 years and older. All subjects completed the GFI questionnaire (n = 1508). To assess criterion validity, a smaller sample of 119 older adults completed additional questionnaires: De Jong Gierveld Loneliness Scale, Hospital Anxiety Depression Scale, RAND-36 physical functioning, and perceived general health item of the EuroQol-5D. Exploratory factor analysis and Mokken scale analysis were used to evaluate the structural validity of the GFI. A Venn diagram was constructed to show the composition of GFI subscale scores for frail subjects.RESULTS: The factor structure of the GFI supported a three-dimensional structure of the scale. The subscales Daily Activities and Psychosocial Functioning showed good internal consistency, scalability, and criterion validity (Daily Activities: Cronbach's α = 0.81, Hs = .84, r = -.62; Psychosocial Functioning: Cronbach's α = 0.80, Hs = .35, r = -.48). The subscale Health Problems showed less strong internal consistency but acceptable scalability and criterion validity (Cronbach's α = .57, Hs = .35, r = -.48). The present data suggest that 90% of the frail older adults experience problems in the Psychosocial Functioning domain.CONCLUSIONS: The present findings support a three-dimensional factor structure of the GFI, suggesting that a multidimensional assessment of frailty with the GFI is possible. These GFI subscale scores produce a richer assessment of frailty than with a single overall sum GFI score, and likely their use will contribute to more directed and customized care for older adults.
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Full text beschikbaar met HU-account Achtergrond Multimorbiditeit, functionele beperkingen en kwetsbaarheid bij thuiswonende ouderen leiden tot een toenemende zorgcomplexiteit in de eerstelijn. Een proactieve, integrale aanpak is hierbij noodzakelijk. In de periode oktober 2014–oktober 2015 is een evidence-based proactief zorgprogramma voor kwetsbare ouderen geïmplementeerd in de regio Noord-West Veluwe en Zeewolde. In deze studie is de haalbaarheid van de implementatie geëvalueerd. De focus lag op de verbinding en samenwerking tussen het medische en sociale domein. Methoden Met een mixed-methods design zijn verschillende procesindicatoren geanalyseerd. Data waren afkomstig van routine zorggegevens uit de huisartsenpraktijk, vragenlijsten en interviews met ouderen. De vragenlijsten gaven inzicht in verwachtingen en ervaringen ten aanzien van het programma en waren op baseline en na zes maanden follow-up afgenomen bij huisartsen, praktijkondersteuners ouderenzorg (POH’s-OZ) en na 12 maanden bij andere professionals uit verschillende domeinen (stakeholders). Interviews met ouderen en hun mantelzorgers brachten de ervaringen in kaart. Regionale werkgroepen waren opgezet waarin verschillende professionals participeerden om de verbinding tussen de domeinen te realiseren. Resultaten Het proactieve zorgprogramma is geïmplementeerd in 42 huisartsenpraktijken die zorg verlenen aan 7904 75-plussers. In totaal vulden 101 zorgverleners en 44 stakeholders de vragenlijst in. Voorafgaand aan de implementatie bleek zowel bij zorgverleners als bij de stakeholders behoefte aan meer structuur, samenwerking en coördinatie in de zorgverlening aan kwetsbare ouderen. De implementatie van het proactieve zorgprogramma verbeterde significant de structuur in de organisatie van zorg en transparantie over verwijsmogelijkheden met respectievelijk 34 % (p ≤ .001) en 27 % (p = .009). Zowel zorgverleners als stakeholders gaven na afloop van de implementatie aan kwetsbare ouderen beter in beeld te hebben dan voor de implementatie (p = .005). Ongeveer de helft van de deelnemers vond na afloop dat de regionale afstemming is verbeterd. Kwetsbare ouderen en hun mantelzorgers waren tevreden met de insteek, opzet en uitvoering van de nieuwe proactieve zorg. De POH’s-OZ gaven aan dat de screeningsvragenlijst te lang was en veel tijd kostte. Ook is niet voor alle ouderen die kwetsbaar waren een zorgplan opgesteld. Conclusie De implementatie van het proactieve zorgprogramma bleek haalbaar. Een sterke verbinding en domein overstijgende samenwerking is gerealiseerd. Het programma kon eenvoudig aangepast worden aan de actualiteit en de lokale context.
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If brief and easy to use self report screening tools are available to identify frail elderly, this may avoid costs and unnecessary assessment of healthy people. This study investigates the predictive validity of three self-report instruments for identifying community-dwelling frail elderly.
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Background: Due to differences in the definition of frailty, many different screening instruments have been developed. However, the predictive validity of these instruments among community-dwelling older people remains uncertain. Objective: To investigate whether combined (i.e. sequential or parallel) use of available frailty instruments improves the predictive power of dependency in (instrumental) activities of daily living ((I)ADL), mortality and hospitalization. Design, setting and participants: A prospective cohort study with two-year followup was conducted among pre-frail and frail community-dwelling older people in the Netherlands. Measurements: Four combinations of two highly specific frailty instruments (Frailty Phenotype, Frailty Index) and two highly sensitive instruments (Tilburg Frailty Indicator, Groningen Frailty Indicator) were investigated. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for all single instruments as well as for the four combinations, sequential and parallel. Results: 2,420 individuals participated (mean age 76.3 ± 6.6 years, 60.5% female) in our study. Sequential use increased the levels of specificity, as expected, whereas the PPV hardly increased. Parallel use increased the levels of sensitivity, although the NPV hardly increased. Conclusions: Applying two frailty instruments sequential or parallel might not be a solution for achieving better predictions of frailty in community-dwelling older people. Our results show that the combination of different screening instruments does not improve predictive validity. However, as this is one of the first studies to investigate the combined use of screening instruments, we recommend further exploration of other combinations of instruments among other study populations.
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