Prevalence of frailty and its association with mortality in general surgery

doi:10.1016/j.amjsurg.2014.05.022

The American Journal of Surgery

Volume 209, Issue 2, February 2015, Pages 254-259

https://doi.org/10.1016/j.amjsurg.2014.05.022 Get rights and content

Abstract

Background

We assessed the prevalence of frailty in an older acute general surgical population and its correlation with length of hospital stay, readmission to hospital, and 30- and 90-day mortality.

Methods

In 3 acute surgical admission units, we assessed consecutive participants aged over 65 years with general surgical conditions. We measured the prevalence of frailty using a 7-point frailty score. We measured length of hospital stay, readmission to hospital, and mortality at both 30 and 90 days.

Results

We studied 325 participants with an average age of 77.3 years 8.2 (standard deviation), 185 (57%) women. There were 88 (28%) participants who were classified as being mildly, moderately, or severely frail. The frail group spent longer in hospital (7.6 days, 95% confidence interval [CI] 6.1 to 9.2 vs 11.1, 95% CI 7.2 to 15.0; P = .03). They also were more likely to die at both 30 and 90 days (adjusted odds ratio [OR] 4.0, 95% CI 1.1 to 15.2, P = .04; OR 3.0, 95% CI 1.3 to 7.4, P = .02). Readmission to hospital did not differ (OR 1.1, 95% CI .5 to 2.3).

Conclusions

Over 1 in 4 people were frail. These individuals spent longer in hospital and were more likely to die.

Section snippets

Patients and Methods

In 3 sites, 1 in Wales, 1 in England, and 1 in Scotland, comprising rural and urban populations, we prospectively studied consecutive patients aged over 65 years of age admitted to the acute general surgical admission units during May and June 2013. This study was part of a wider surgical collaboration, which focuses on surgical disease in the older person (www.opsoc.eu).

In each of the 3 sites, patients with orthopedic, urological, neurosurgical, or vascular conditions would ordinarily be

Statistical Analysis

Cross-sectional observations were tested using the chi-square test. Odds ratios (ORs) were constructed using a forward fitting model, which was tested for confounding using all the available variables. A final parsimonious model was derived by incorporating any variable that altered the unadjusted model by at least 5%. All statistical calculations were conducted using STATA 11 (Stata Corp, USA).

Results

We collected data on 325 people, all of whom were included in the analysis. Their mean age was 77.3 years (standard deviation 8.2, range 65 to 101), and 185 (57%) were women, who were not older than the men (P = .13). Three people were deemed to have a primary diagnosis consistent with a vascular surgical condition, 2 with a primary urological diagnosis and 1 with a primary diagnosis of an orthopedic condition. The remaining 319 had diagnoses in keeping with acute general surgical conditions,

Comments

The great advances in life expectancy in the recent past are a cause for celebration. As a result of this development, all aspects of medicine are learning to appropriately manage the older person and emergency general surgery is no exception. However, in keeping with most aspects of current surgical practice in older people, there is a distinct lack of epidemiological evidence to support it. This study uses the comparatively new concept of frailty to describe the older surgical patient and

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Association of risk analysis index with 90-day failure to rescue following major abdominal surgery in geriatric patients
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Failure to rescue (FTR) is a quality metric defined as mortality after potentially preventable complications after surgery. Predicting patients who are at the highest risk of mortality after a complication may aid in preventing deaths. Thirty-day follow-up period inadequately captures postoperative deaths; alternatively, a 90-day follow-up period has been advocated. This study aimed to examine the association of a validated frailty metric, the risk analysis index (RAI), with 90-day FTR (FTR-90).
Patients aged ≥65 years who underwent a major abdominal operation between 2014 and 2020 at a quaternary care center were abstracted. Institutional data were merged with the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) and Geriatric Surgery Research File variables. The association between RAI and FTR-90 was evaluated using multivariable logistic regression.
A total of 398 patients with postoperative complications were included. Fifty-two patients (13.1%) died during the 90-day follow-up. The FTR-90 group was older (median age: 76 vs 73 years, respectively; P = .002), had a greater preoperative American Society of Anesthesiologists classification score (P < .001), and had a higher ACS NSQIP estimated risk of morbidity (0.33% vs 0.20%, P < .001) and mortality (0.067% vs 0.012%, P < .001). The FTR-90 group had a greater median RAI score (23 vs 19; P = .002). The RAI score was independently associated with FTR-90 (odds ratio, 1.04; 95% CI, 1.0042-1.0770; P = .028) but not with FTR-30 (P = .13).
Preoperative frailty, as defined by RAI, is independently associated with FTR at 90-day follow-up. FTR-90 captured nearly 60% more deaths than did FTR-30. Frailty has major implications beyond the typical 30-day follow-up period, and a longer follow-up period must be considered.
Patients’ frailty and co-morbidities do not affect short-term mortality following emergency colorectal cancer surgery
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To investigate the effects of frailty and co-morbidities on short and medium-term outcome following emergency colorectal cancer surgery.
Data of patients who underwent emergency colorectal cancer operations between January 2013 and December 2016 were reviewed retrospectively. Collected data included demographic and operative variables, clinical frailty scale (CFS), Charlson comorbidity index (CCI) and cause of death with minimum 3 years follow-up.
Three-hundred and six patients (median age 72, range 18–100 years) underwent emergency colorectal cancer surgery; Some 74 (24.2%) patients had metastatic cancer at the time of emergency surgery, 77 (25.2%) were frail (CFS ≥4), while 118 (38.6%) were comorbid (CCI of ≥8). Thirty-day mortality was 4.2% (13 patients) and a further 12 patients died within 90 days (8.2%). By 1 year 73 (23.9%) patients had died, and by 3 years 151 (49.3%) patients died. Frailty did not impact 30-day mortality (6.5% vs 3.5%, p = 0.26) but frail patients (CFS ≥4) had a higher mortality rate at 90 days (16.9% vs 5.2%, p < 0.05), 1 year (37.7% vs 19.2%, p < 0.05) and 3 years (61.0% vs 45.4%, p < 0.05). Similarly, higher comorbidity (CCI ≥8) did not impact 30-day mortality (5.9% vs 3.2%, p = 0.25), but they had a higher mortality rate at 90 days (14.4% vs 4.3%, p < 0.05), 1 year (40.7% vs 13.3%, p < 0.05), and 3 years (76.3% vs 32.4%, p < 0.05).
Thirty-day mortality after emergency colorectal cancer surgery in frail and comorbid patients are similar to that of the general population.
Prevalence and outcomes of frailty in unplanned hospital admissions: a systematic review and meta-analysis of hospital-wide and general (internal) medicine cohorts
2023, eClinicalMedicine
Guidelines recommend routine frailty screening for all hospitalised older adults to inform care decisions, based mainly on studies in elective or speciality-specific settings. However, most hospital bed days are accounted for by acute non-elective admissions, in which the prevalence and prognostic value of frailty might differ, and uptake of screening is limited. We therefore did a systematic review and meta-analysis of frailty prevalence and outcomes in unplanned hospital admissions.
We searched MEDLINE, EMBASE and CINAHL up to 31/01/2023 and included observational studies using validated frailty measures in adult hospital-wide or general medicine admissions. Summary data on the prevalence of frailty and associated outcomes, measurement tools, study setting (hospital-wide vs general medicine), and design (prospective vs retrospective) were extracted and risk of bias assessed (modified Joanna Briggs Institute checklists). Unadjusted relative risks (RR; moderate/severe frailty vs no/mild) for mortality (within one year), length of stay (LOS), discharge destination and readmission were calculated and pooled, where appropriate, using random-effects models. PROSPERO CRD42021235663.
Among 45 cohorts (median/SD age = 80/5 years; n = 39,041,266 admissions, n = 22 measurement tools) moderate/severe frailty ranged from 14.3% to 79.6% overall (and in the 26 cohorts with low-moderate risk of bias) with considerable heterogeneity between studies (p_het < 0.001) preventing pooling of results but with rates <25% in only 3 cohorts. Moderate/severe vs no/mild frailty was associated with increased mortality (n = 19 cohorts; RR range = 1.08–3.70), more consistently among cohorts using clinically administered tools (n = 11; RR range = 1.63–3.70; p_het = 0.08; pooled RR = 2.53, 95% CI = 2.15–2.97) vs cohorts using (retrospective) administrative coding data (n = 8; RR range = 1.08–3.02; p_het < 0.001). Clinically administered tools also predicted increasing mortality across the full range of frailty severity in each of the six cohorts that allowed ordinal analysis (all p < 0.05). Moderate/severe vs no/mild frailty was also associated with a LOS >8 days (RR range = 2.14–3.04; n = 6) and discharge to a location other than home (RR range = 1.97–2.82; n = 4) but was inconsistently related to 30-day readmission (RR range = 0.83–1.94; n = 12). Associations remained clinically significant after adjustment for age, sex and comorbidity where reported.
Frailty is common in older patients with acute, non-elective hospital admission and remains predictive of mortality, LOS and discharge home with more severe frailty associated with greater risk, justifying more widespread implementation of screening using clinically administered tools.
None.
Frailty assessment has come to stay: Retrospective analysis pilot study of two frailty scales in oncological older patients undergoing colorectal surgery
2023, Revista Espanola de Anestesiologia y Reanimacion
El cáncer colorrectal es una enfermedad que habitualmente aparece en ancianos y su principal tratamiento continúa siendo quirúrgico. La fragilidad es síndrome clínico que se caracteriza por presentar una disminución de la reserva fisiológica, aumenta con la edad y ha sido reconocido como un factor predictivo de mortalidad postoperatoria. Nuestro objetivo primario ha sido evaluar la asociación entre dos escalas de fragilidad y la mortalidad a un año después de la cirugía, y comparando la fuerza de su asociación del poder predictivo de mortalidad de las escalas de fragilidad y la de la clasificación de la American Society of Anesthesiologists (ASA).
Las escalas utilizadas fueron: Modified Frailty Index (MFI) y el Risk Analysis Index (RAI-A).
Los objetivos secundarios han sido la evaluación de la relación de las escalas de fragilidad con la morbilidad y la comparación de estas con la clasificación ASA en cuanto a predicción de morbilidad.
Analizamos retrospectivamente 172 pacientes mayores de 65 años que fueron intervenidos de cirugía oncológica colorrectal laparoscópica desde enero de 2017 hasta junio de 2018 con un seguimiento de un año posterior a la cirugía.
La fragilidad esta significativamente asociada a la mortalidad y morbilidad (p < 0,001). A más fragilidad, mayor probabilidad de estancia hospitalaria, complicaciones, reingresos y visitas a urgencias. Los pacientes fueron categorizados en dos grupos (pacientes frágiles y no frágiles). Los C-index de la predicción a mortalidad a un año obtenidos con el RAI-A y el MFI fueron 0,89 y 0,86, respectivamente. Por otro lado, la clasificación ASA no se relaciona con mortalidad, su C-index fue del 0,63.
Las escalas de fragilidad deberían empezar a influenciar las intervenciones médicas y quirúrgicas, y se deberían implementar guías y protocolos que tuviesen en cuenta el grado de fragilidad de los pacientes geriátricos.
Colorectal cancer is a disease of the elderly and its main treatment is surgery. Frailty, a clinical syndrome of decreased reserve, increases with age and has been recognized as a predictive factor for postoperative mortality. Our primary objective was to assess the association between twohree frailty scores and mortality.
within the first year after surgery, by retrospectively linking frailty scores to mortality data and comparing the strength of their association with mortality to that of the ASA Classification. The frailty scales used were: the Modified Frailty Index (MFI) and, the Risk Analysis Index-A (RAI-A) and the G8 screening test (G8). As secondary objectives, we assessed the relationship of the frailty scales with morbidity and compared all the scales with the ASA.
We retrospectively studied 172 patients aged 65 years.
and older who underwent laparoscopic colorectal surgery for cancer between January 2017 and June 2018, following them up for 1 year after surgery.
Both morbidity and mortality were significantly associated with all frailty scale scores (p < 0.001). The more frailty, the greater probability of prolonged hospital stay, complications, readmissions and emergency department visits. Using each scale, patients were categorized into two groups (frail and non-frail patients). The C-indexes for 1-year mortality with the RAI-A and, MFI and G8 were 0.89 and, 0.86 and 0.86 respectively. On the other hand, ASA status is not strongly associated with mortality, with a C-index of 0.63.
Frailty scores should begin to influence medical and surgical strategies and further research is needed to develop guidelines for interventions in geriatric patients.
The prevalence of frailty and pre-frailty among geriatric hospital inpatients and its association with economic prosperity and healthcare expenditure: A systematic review and meta-analysis of 467,779 geriatric hospital inpatients
2022, Ageing Research Reviews
Citation Excerpt :
There was no significant difference in pooled prevalence estimates of frailty stratified by continent (p = 0.32) (Supplementary Figure H). Fourteen of the included studies were conducted in the United States of America (Baldwin et al., 2014; Courtney-Brooks et al., 2012; Engelhardt et al., 2018; Gleason et al., 2017; Jokar et al., 2016; Joseph et al., 2014; Joseph et al., 2016; Karlekar et al., 2017; Khan et al., 2019; Lee et al., 2018; Madni et al., 2018; Maxwell et al., 2018; Pollack et al., 2017; Purser et al., 2006); 13 the United Kingdom (Hartley et al., 2017; Hewitt et al., 2015; Hewitt et al., 2016; Ibrahim et al., 2019; Induruwa et al., 2017; Keevil et al., 2018; Mason et al., 2018; McGuckin et al., 2018; Morton et al., 2018; Myint et al., 2018; Parmar et al., 2019; Wallis et al., 2015; Wou et al., 2013); 12 Australia (Cheung et al., 2017; Dent et al., 2014; Eeles et al., 2012; Hilmer et al., 2011; Lin et al., 2017; Nguyen et al., 2016; Patel et al., 2018; Peel et al., 2017; Perera et al., 2009; Poudel et al., 2016; Rose et al., 2014; Thai et al., 2015); nine Spain (Alonso Salinas et al., 2018; Amblàs-Novellas et al., 2018; Gullón et al., 2018; Llaó et al., 2018; Martín et al., 2018; Pelavski et al., 2017; Sánchez et al., 2011; Sanchis et al., 2015; Vidán et al., 2014); eight Italy (Attisano et al., 2017; Bo et al., 2015; Bo et al., 2016; Dal Moro et al., 2017; Ferrero et al., 2017; Pasqualetti et al., 2018; Ticinesi et al., 2016; Valentini et al., 2018); five Canada (Andrew et al., 2017; Eamer et al., 2018; Juma et al., 2016; McIsaac et al., 2019; Sikder et al., 2019); five Germany (Dorner et al., 2014; Dutzi et al., 2017; Muessig et al., 2018; Ritt et al., 2015; Sündermann et al., 2014); four Ireland (Coleman et al., 2012; Crozier-Shaw, Joyce, 2018; Nolan et al., 2016; Timmons et al., 2015); three Singapore (Chew et al., 2017; Chia et al., 2016; Chong et al., 2017) two New Zealand (Heppenstall et al., 2011; Hii et al., 2014); two China (Kang et al., 2015; Ma et al., 2013); two France (Blanco et al., 2017; Le Maguet et al., 2014); two Greece (Papageorgiou et al., 2018; Papakonstantinou et al., 2018); two Japan (Koyama et al., 2018; Kusunose et al., 2018); and, two the Netherlands (Andela et al., 2010; Jacobs et al., 2017). Additionally, one study was conducted in each of Belgium (Joosten et al., 2014); Brazil (Oliveira et al., 2013); Turkey (Öztürk et al., 2017); Poland (Kenig et al., 2015); Sweden (Ekerstad et al., 2011); and Switzerland (Müller et al., 2017).
Frailty is a common and clinically significant condition among geriatric populations. Although well-evidenced pooled estimates of the prevalence of frailty exist within various settings and populations, presently there are none assessing the overall prevalence of frailty among geriatric hospital inpatients. The purpose of this review was to systematically search and analyse the prevalence of frailty among geriatric hospital inpatients within the literature and examine its associations with national economic indicators.
Systematic searches were conducted on Ovid, Web of Science, Scopus, CINAHL Plus, and the Cochrane Library, encompassing all literature published prior to 22 November 2018, supplemented with manual reference searches. Included studies utilised a validated operational definition of frailty, reported the prevalence of frailty, had a minimum age ≥ 65 years, attempted to assess the whole ward/clinical population, and occurred among hospital inpatients. Two reviewers independently extracted data and assessed study quality.
Ninety-six studies with a pooled sample of 467,779 geriatric hospital inpatients were included. The median critical appraisal score was 8/9 (range 7–9). The pooled prevalence of frailty, and pre-frailty, among geriatric hospital inpatients was 47.4% (95% CI 43.7–51.1%), and 25.8% (95% CI 22.0–29.6%), respectively. Significant differences were observed in the prevalence of frailty stratified by age, prevalent morbidity, ward type, clinical population, and operational definition. No significant differences were observed in stratified analyses by sex or continent, or significant associations between the prevalence of frailty and economic indicators.
Frailty is highly prevalent among geriatric hospital inpatients. High heterogeneity exists within this setting based on various clinical and demographic characteristics. Pooled estimates reported in this review place the prevalence of frailty among geriatric hospital inpatients between that reported for community-dwelling older adults and older adults in nursing homes, outlining an increase in the relative prevalence of frailty with progression through the healthcare system.
Evaluating frailty may complement APACHE II in estimating mortality in elderly patients admitted to the ICU after digestive surgery
2022, Medicina Intensiva
Analizar si la fragilidad puede mejorar la predicción de mortalidad en los pacientes ingresados en UCI tras una cirugía digestiva.
Estudio prospectivo, observacional y con seguimiento a 6 meses de una cohorte de pacientes que ingresaron en UCI entre el 1 de junio de 2018 hasta el 1 de junio de 2019.
UCI quirúrgica de un hospital de tercer nivel.
Serie de pacientes sucesivos mayores de 70 años que ingresaron en UCI inmediatamente después de una intervención quirúrgica sobre el aparato digestivo. Fueron incluidos 92 pacientes y se excluyeron 2 por pérdida de seguimiento a los 6 meses.
Al ingreso en UCI se estimó gravedad y pronóstico mediante el APACHE II, y fragilidad mediante la Clinical Frailty Scale y el modified Frailty Index.
Mortalidad en UCI, intrahospitalaria y a los 6 meses.
El modelo que mejor predice mortalidad en UCI es el APACHE II, con un área bajo la curva ROC (ABC) de 0,89 y una buena calibración. El modelo que combina APACHE II y Clinical Frailty Scale es el que mejor predice mortalidad intrahospitalaria (ABC: 0,82), mejorando significativamente la predicción del APACHE II aislado (ABC: 0,78; Integrated Discrimination Index: 0,04). La fragilidad es un factor predictor de mortalidad a los 6 meses, siendo el modelo que combina la Clinical Frailty Scale y el modified Frailty Index el que ha demostrado mayor discriminación (ABC: 0,84).
La fragilidad puede complementar al APACHE II mejorando su predicción de mortalidad hospitalaria. Además, ofrece una buena predicción de la mortalidad a los 6 meses de la cirugía. Para la mortalidad en UCI, la fragilidad pierde su poder de predicción mientras que el APACHE II aislado muestra una excelente capacidad predictiva.
To analyze whether frailty can improve the prediction of mortality in patients admitted to the ICU after digestive surgery.
Prospective, observational, 6-month follow-up study of a cohort of patients admitted to the ICU between June 1, 2018, and June 1, 2019.
Surgical ICU of a third level hospital.
Series of successive patients older than 70 years who were admitted to the ICU immediately after a surgical intervention on the digestive system. 92 patients were included and 2 were excluded due to loss of follow-up at 6 months.
Upon admission to the ICU, severity and prognosis were assessed by APACHE II, and fragility by the Clinical Frailty Scale and the modified Frailty Index.
ICU, in-hospital and 6-month mortality.
The model that best predicts mortality in the ICU is the APACHE II, with an area under the ROC curve (AUC) of 0.89 and a good calibration. The model that combines APACHE II and Clinical Frailty Scale is the one that best predicts in-hospital mortality (AUC: 0.82), significantly improving the prediction of isolated APACHE II (AUC: 0.78; Integrated Discrimination Index: 0.04). Frailty is a predictor of mortality at 6 months, being the model that combines Clinical Frailty Scale and Frailty Index the one that has shown the greatest discrimination (AUC: 0.84).
Frailty can complement APACHE II by improving its prediction of hospital mortality. Furthermore, it offers a good prediction of mortality 6 months after surgery. For mortality in ICU, frailty loses its predictive power, whereas isolated APACHE II shows excellent predictive capacity.

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: Jonathan Hewitt, the lead author and guarantor, affirms that the manuscript is an honest, accurate, and transparent account of the study being reported and that no important aspects of the study have been omitted.

: There were no relevant financial relationships or any sources of support in the form of grants, equipment, or drugs.

: The authors declare no conflicts of interest.

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Clinical SciencePrevalence of frailty and its association with mortality in general surgery

Abstract

Background

Methods

Results

Conclusions

Section snippets

Patients and Methods

Statistical Analysis

Results

Comments

J Am Med Dir Assoc

Arch Gerontol Geriatr

J Am Coll Surg

J Am Coll Surg

J Am Coll Surg

Lancet

Best Pract Res Clin Anaesthesiol

Frailty in the older surgical patient: a review

Age Ageing

Frailty in older adults: evidence for a phenotype

J Gerontol A Biol Sci Med Sci

Clinical Science
Prevalence of frailty and its association with mortality in general surgery