Creation of a New Frailty Scale in Primary Care: The Zulfiqar Frailty Scale (ZFS)

Assessment of the Zulfiqar Frailty Scale (ZFS) in Primary Healthcare

INTRODUCTION

The primary aim of the study was to validate the Zulfiqar Frailty Scale (ZFS) and examine its concordance with the modified Short Emergency Geriatric Assessment (mSEGA) scale, Part A.

METHODS

A prospective observational study was conducted in Guadeloupe (France) over a two-month duration (from 20 February to 20 April 2024), involving elderly individuals aged 65 and older, deemed self-sufficient with an ADL (Activities of Daily Living) score exceeding four out of six.

RESULTS

Within this community cohort of 98 individuals, averaging 75 years in age, frailty according to the modified SEGA criteria was prevalent in 29%. Frailty according to the "ZFS" score was prevalent in 40%. Key predictors of frailty identified in our study included age, comorbidity (Charlson score), polypharmacy (total number of medications and therapeutic classes), and functional ability (ADL scores). Notably, experiences of falls and hospitalizations within the past six months significantly influenced the classification of frailty according to both ZFS and SEGA scales. Significant associations with the presence of home care aides (p < 0.0001), monopodal support test results (p < 0.0001), memory impairments (p < 0.0001), and recent hospitalizations (p = 0.0054) underscored the multidimensional impact of frailty. The Pearson correlation coefficient and its 95% confidence interval between the SEGA and Zulfiqar Frailty Scales stood at 0.73 [0.61: 0.81]. The discernment threshold for frailty was set at three out of six criteria, showcasing a sensitivity of 64% and a negative predictive value of 80%. The area under the curve (AUC) for the Zulfiqar Frailty Scale was reported as 0.8.

CONCLUSION

The "ZFS" tool allows for the detection of frailty with a highly satisfactory sensitivity and negative predictive value.

Frailty detection by healthcare professionals: a systematic review of the available English and French tools and their validation

BACKGROUND

There is a wide variety of frailty detection tools, but no gold standard. Choosing the most appropriate tool can therefore be complicated. Our systematic review seeks to provide useful data on the frailty detection tools available to help healthcare professionals in choosing a tool.

METHOD

We systematically searched for articles published between January 2001 and December 2022 in three electronic databases. Articles were to be written in English or French and were to discuss a frailty detection tool used by healthcare professionals in a population without specific health conditions. Any self-testing, physical testing or biomarkers were excluded. Systematic reviews and meta-analyses were also excluded. Data were extracted from two coding grids; one for the criteria used by the tools to detect frailty and the other for the evaluation of clinimetric parameters. The quality of the articles was assessed using QUADAS-2.

RESULTS

A total of 52 articles, covering 36 frailty detection tools, were included and analysed in the systematic review. Forty-nine different criteria were identified, with a median of 9 (IQR 6-15) criteria per tool. Regarding the evaluation of tool performances, 13 different clinimetric properties were identified, with a mean of 3.6 (± 2.2) properties assessed per tool.

CONCLUSION

There is considerable heterogeneity in the criteria used to detect frailty, as well as in the way tools are evaluated.

Zulfiqar Frailty Scale (ZFS): Concordance Study with the Clinical Frailty Scale (CFS)

Introduction: We designed a new scale for the rapid detection of frailty for use in primary care, referred to as the Zulfiqar Frailty Scale (ZFS). Objective: To evaluate the performance of the “ZFS” tool to screen for frailty as defined in the Clinical Frailty Scale (CFS) criteria in an ambulatory population of patients at least 75 years old. Method: A prospective study conducted in Alsace, France, for a duration of 6 months that included patients aged 75 and over was judged to be autonomous with an ADL (Activity of Daily Living) > 4/6. Results: In this ambulatory population of 124 patients with an average age of 79 years, the completion time for our scale was less than two minutes, and the staff required no training beforehand. Sensibility was 67%, while specificity was 87%. The positive predictive value was 80%, and the negative predictive value was 77%. The Youden index was 59.8%. In our study, we have a moderate correlation between CFS and ZFS (r = 0.674 with 95%CI = [0.565; 0.760]; p-value < 2.2 × 10−16 < 0.05). The Pearson correlations between these two geriatric scores were all strong and roughly equivalent to each other. The kappa of Cohen (k) = 0.46 (Unweighted), moderate concordance between the ZFS and CFS scales according to Fleiss classification. Conclusion: The “ZFS” tool makes it possible to screen for frailty with a high level of specificity and positive/negative predictive value.

Zulfiqar Frailty Scale: Overview, Stakes, and Possibilities

Very few frailty scales are used by general practitioners, as they are time consuming and cumbersome. We developed a frailty screening tool for use in primary care, referred to as the Zulfiqar Frailty Scale (ZFS). This scale was tested in multiple general practitioners' offices in France, and these studies were published. In this paper, we offer a summary of these results.

Validation of the Zulfiqar Frailty Scale (ZFS): A New Tool for General Practitioners

Introduction: The early detection of frailty, a frequent transient state that can be reversible in the elderly and is responsible for significant morbidity and mortality, helps prevent complications from it. Objective: To evaluate the performance of the “ZFS” tool to screen for frailty as defined SEGA scale criteria in an ambulatory population of patients at least 65 years of age. Methods: A prospective non-interventional study conducted in Alsace for a duration of six months that included patients aged 65 and over, judged to be autonomous with an ADL > 4/6. Results: In this ambulatory population of 102 patients with an average age of 76 years, frailty, according to modified SEGA criteria grid A, had a prevalence of 19.6%. Frailty, according to the “ZFS” tool, had a prevalence of 35.0%, and all of its elements except weight loss were significantly associated with frailty. Its threshold for identifying frailty is three criteria out of six. It was rapid (average completion time: 87 s), had a sensitivity of 100%, and a negative predictive value of 100%. Conclusions: The “ZFS” tool makes it possible to screen for frailty with a high level of sensitivity and a negative predictive value.

Frailty in Primary Care: Validation of the simplified Zulfiqar Frailty Scale (sZFS)

Introduction: Frailty scales are used very rarely by general practitioners as they are time consuming and are not well-adapted to current needs. Thus, we have designed with general practitioners a new scale for the early and rapid detection of frailty syndrome, called the simplified Zulfiqar Frailty Scale (sZFS). Patients and methods: This scale was tested in two general medicine practices in Normandy (France) for a total of six months and compared to the GFST tool “The Gerontopole Frailty Screening Tool”. Only patients who were over 65 years old with an ADL ≥ 4/6 were included. Results: 107 were patients included in the general medicine practice, with an average age of 74 years. The sZFS questionnaire has a shorter administration time than the GFST questionnaire (p < 0.001). Its sensitivity is of 93%, and its specificity is 58%. Its positive predictive value is 57%, and its negative predictive value is 93%. The area under the curve of the sZFS scale is 0.83 [0.76; 0.91] (IC95%). Conclusion: Our frailty screening scale is simple, relevant, and quick.