How Is Surgical Risk Best Assessed? A Cohort Comparison of Measures in Total Joint Arthroplasty

30-day to 10-year mortality rates following total hip arthroplasty: a meta-analysis of the last decade (2011-2021)

BACKGROUND

Mortality after total hip arthroplasty (THA) is a rare but devastating complication. This meta-analysis aimed to: (1) determine the mortality rates at 30 days, 90 days, 1 year, 5 years and 10 years after THA; (2) identify risk factors and causes of mortality after THA.

METHODS

Pubmed, MEDLINE, Cochrane, EBSCO Host, and Google Scholar databases were queried for studies reporting mortality rates after primary elective, unilateral THA. Inverse-proportion models were constructed to quantify the incidence of all-cause mortality at 30 days, 90 days, 1 year, 5 years and 10 years after THA. Random-effects multiple regression was performed to investigate the potential effect modifiers of age (at time of THA), body mass index, and gender.

RESULTS

A total of 53 studies (3,297,363 patients) were included. The overall mortality rate was 3.9%. The 30-day mortality was 0.49% (95% CI; 0.23-0.84). Mortality at 90 days was 0.47% (95% CI, 0.38-0.57). Mortality increased exponentially between 90 days and 5 years, with a 1-year mortality rate of 1.90% (95% CI, 1.22-2.73) and a 5-year mortality rate of 9.85% (95% CI, 5.53-15.22). At 10-year follow-up, the mortality rate was 16.43% (95% CI, 1.17-22.48). Increasing comorbidity indices, socioeconomic disadvantage, age, anaemia, and smoking were found to be risk factors for mortality. The most commonly reported causes of death were ischaemic heart disease, malignancy, and pulmonary disease.

CONCLUSIONS

All-cause mortality remains low after contemporary THA. However, 1 out of 10 patients and 1 out of 6 patients were deceased after 5 years and 10 years of THA, respectively. As expected, age, but not BMI or gender, was significantly associated with mortality.

A comparative analysis of the Hospital Frailty Risk Score in predicting postoperative outcomes among intracranial tumor patients

OBJECTIVE

In recent years, frailty indices such as the 11- and 5-factor modified frailty indices (mFI-11 and mFI-5), American Society of Anesthesiologists (ASA) physical status classification, and Charlson Comorbidity Index (CCI) have been shown to be effective predictors of various postoperative outcomes in neurosurgical patients. The Hospital Frailty Risk Score (HFRS) is a well-validated tool for assessing frailty; however, its utility has not been evaluated in intracranial tumor surgery. In the present study, the authors investigated the accuracy of the HFRS in predicting outcomes following intracranial tumor resection and compared its utility to those of other validated frailty indices.

METHODS

A retrospective analysis was conducted using an intracranial tumor patient database at a single institution. Patients eligible for study inclusion were those who had undergone resection for an intracranial tumor between January 1, 2017, and December 31, 2019. ICD-10 codes were used to identify HFRS components and subsequently calculate risk scores. In addition to several postoperative variables, ASA class, CCI, and mFI-11 and mFI-5 scores were determined for each patient. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUROC), and the DeLong test was used to assess for significant differences between AUROCs. Multivariate models for continuous outcomes were constructed using linear regression, whereas logistic regression models were used for categorical outcomes.

RESULTS

A total of 2518 intracranial tumor patients (mean age 55.3 ± 15.1 years, 53.4% female, 70.4% White) were included in this study. The HFRS had a statistically significant greater AUROC than ASA status, CCI, mFI-11, and mFI-5 for postoperative complications, high hospital charges, nonroutine discharge, and 90-day readmission. In the multivariate analysis, the HFRS was significantly and independently associated with postoperative complications (OR 1.14, p < 0.0001), hospital length of stay (coefficient = 0.50, p < 0.0001), high hospital charges (coefficient = 1917.49, p < 0.0001), nonroutine discharge (OR 1.14, p < 0.0001), and 90-day readmission (OR 1.06, p < 0.0001).

CONCLUSIONS

The study findings suggest that the HFRS is an effective predictor of postoperative outcomes in intracranial tumor patients and more effectively predicts adverse outcomes than other frailty indices. The HFRS may serve as an important tool for reducing patient morbidity and mortality in intracranial tumor surgery.

The association between frailty and mortality among lower limb arthroplasty patients: a systematic review and meta-analysis

Background

Some studies associate frailty and postoperative mortality in hip or knee replacement patients, and others have explored the relationship between the frailty index and changes in postoperative mortality in hip or knee replacement patients, but their findings are not consistent. This meta-analysis and systematic review aimed to pool the results of existing studies to explore whether frailty is an independent risk factor for postoperative mortality in patients with lower limb arthroplasty (including hip or knee arthroplasty).

Methods

On December 15, 2021, we searched the relevant articles from the PubMed, Embase, Medline (via Ovid), China National Knowledge Infrastructure (CNKI) and Wan Fang Med Online databases. We used the Newcastle–Ottawa Scale (NOS) to assess the quality of the articles that met the exclusion and inclusion criteria. R Studio was used to analyze the effect sizes (based on the random model integration) on the extracted data. Meanwhile, potential publication bias and sensibility analysis were performed.

Results

We included seven studies, which included a total of 460,594 patients, for quantitative analysis. Overall, frailty increased the risk of mortality in lower limb arthroplasty patients compared to those without frailty, as measured by a pooled risk ratio (RR) of 2.46 (95% confidence interval [CI]: 1.81–3.33). Additionally, subgroup analysis based on population revealed that the pooled RRs for total knee arthroplasty (TKA) patients in three studies and total hip arthroplasty (THA) patients in four studies were 2.61 (95% CI: 2.26–3.02) and 3.18 (95% CI: 1.92–5.28), respectively, for TKA patients in three studies and THA patients in four studies. Additionally, these statistically significant positive associations persisted in subgroup analyses by study design, geographic region, and follow-up period.

Conclusion

Frailty is an independent risk factor for postoperative mortality in patients undergoing lower limb arthroplasty, according to our findings. This suggests that frailty may be a predictor of preoperative risk stratification for patients with such elective surgery and could alert doctors and nurses of early screening and medical care interventions in patients with such a need for surgery to reduce postoperative mortality in lower limb arthroplasty patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03369-w.

Effect of the Age-Adjusted Charlson Comorbidity Index on All-Cause Mortality and Readmission in Older Surgical Patients: A National Multicenter, Prospective Cohort Study

Background

Identifying a high-risk group of older people before surgical procedures is very important. The study aimed to explore the association between the age-adjusted Charlson comorbidity index (ACCI) and all-cause mortality and readmission among older Chinese surgical patients (age ≥65 years).

Methods

A large-scale cohort study was performed in 25 general public hospitals from six different geographic regions of China. Trained registered nurses gathered data on clinical and sociodemographic characteristics. All-cause mortality was recorded when patients died during hospitalization or during the 90-day follow-up period. Readmission was also tracked from hospital discharge to the 90-day follow-up. The ACCI, in assessing comorbidities, was categorized into two groups (≥5 vs. &lt;5). A multiple regression model was used to examine the association between the ACCI and all-cause mortality and readmission.

Results

There were 3,911 older surgical patients (mean = 72.46, SD = 6.22) in our study, with 1,934 (49.45%) males. The average ACCI score was 4.77 (SD = 1.99), and all-cause mortality was 2.51% (high ACCI = 5.06% vs. low ACCI = 0.66%, P &lt; 0.001). After controlling for all potential confounders, the ACCI score was an independent risk factor for 90-day hospital readmission (OR = 1.18, 95% CI: 1.14, 1.23) and 90-day all-cause mortality (OR = 1.26, 95% CI: 1.16–1.36). Furthermore, older surgical patients with a high ACCI (≥5) had an increased risk of all-cause mortality (OR = 6.13, 95% CI: 3.17, 11.85) and readmission (OR = 2.13, 95% CI: 1.78, 2.56) compared to those with a low ACCI (&lt;5). The discrimination performance of the ACCI was moderate for mortality (AUC:0.758, 95% CI: 0.715–0.80; specificity = 0.591, sensitivity = 0.846) but poor for readmission (AUC: 0.627, 95% CI: 0.605–0.648; specificity = 0.620; sensitivity = 0.590).

Conclusions

The ACCI is an independent risk factor for all-cause mortality and hospital readmission among older Chinese surgical patients and could be a potential risk assessment tool to stratify high-risk older patients for surgical procedures.

Frailty Transitions One Year After Total Joint Arthroplasty: A Cohort Study

BACKGROUND

Total joint arthroplasty (TJA) is prevalent and offered to patients regardless of frailty status experiencing pain, disability, and functional decline. This study aims to describe changes in levels of frailty 1 year after TJA.

METHODS

We identified a retrospective cohort of adult patients undergoing primary TJA between 2005 and 2016 using an institutional total joint registry. Associations between categorized frailty deficit index (FI) and change in FI were analyzed using linear regression models. Mortality, deep periprosthetic joint infection, and reoperation were analyzed using time to event methods.

RESULTS

In total, 5341 patients (37.6% non-frail, 39.4% vulnerable, and 23.0% frail) with items necessary to determine FI at 1 year after TJA were included. Preoperatively, 29% of vulnerable patients improved to non-frail 1 year later, compared to only 11% regressing to frail. Four in 10 frail patients improved to vulnerable/non-frail. Improvements in activities of daily living (ADL) were more evident in frail and vulnerable patients, with >30% reduction in the percentage of patients expressing difficulties with walking, climbing stairs, and requiring ADL assistance 1 year after TJA. Increases in frailty 1 year after TJA were associated with significantly increased rates of mortality (hazard ratio [HR] 1.50, 95% confidence interval [CI] 1.24-1.82, P < .001), deep periprosthetic joint infection (HR 3.98, 95% CI 1.85-8.58, P < .001), and reoperation (HR 1.80, 95% CI 1.19-2.72, P = .005).

CONCLUSION

Frailty states are dynamic with patient frailty shown to be modifiable 1 year after TJA. Preoperative frailty measurement is an important step toward identifying those that may benefit most from TJA and for postoperative frailty surveillance.

Is Frailty Associated with Adverse Outcomes After Orthopaedic Surgery?: A Systematic Review and Assessment of Definitions

BACKGROUND

There is increasing evidence supporting the association between frailty and adverse outcomes after surgery. There is, however, no consensus on how frailty should be assessed and used to inform treatment. In this review, we aimed to synthesize the current literature on the use of frailty as a predictor of adverse outcomes following orthopaedic surgery by (1) identifying the frailty instruments used and (2) evaluating the strength of the association between frailty and adverse outcomes after orthopaedic surgery.

METHODS

A systematic review was performed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, Scopus, and the Cochrane Central Register of Controlled Trials were searched to identify articles that reported on outcomes after orthopaedic surgery within frail populations. Only studies that defined frail patients using a frailty instrument were included. The methodological quality of studies was assessed using the Newcastle-Ottawa Scale (NOS). Study demographic information, frailty instrument information (e.g., number of items, domains included), and clinical outcome measures (including mortality, readmissions, and length of stay) were collected and reported.

RESULTS

The initial search yielded 630 articles. Of these, 177 articles underwent full-text review; 82 articles were ultimately included and analyzed. The modified frailty index (mFI) was the most commonly used frailty instrument (38% of the studies used the mFI-11 [11-item mFI], and 24% of the studies used the mFI-5 [5-item mFI]), although a large variety of instruments were used (24 different instruments identified). Total joint arthroplasty (22%), hip fracture management (17%), and adult spinal deformity management (15%) were the most frequently studied procedures. Complications (71%) and mortality (51%) were the most frequently reported outcomes; 17% of studies reported on a functional outcome.

CONCLUSIONS

There is no consensus on the best approach to defining frailty among orthopaedic surgery patients, although instruments based on the accumulation-of-deficits model (such as the mFI) were the most common. Frailty was highly associated with adverse outcomes, but the majority of the studies were retrospective and did not identify frailty prospectively in a prediction model. Although many outcomes were described (complications and mortality being the most common), there was a considerable amount of heterogeneity in measurement strategy and subsequent strength of association. Future investigations evaluating the association between frailty and orthopaedic surgical outcomes should focus on prospective study designs, long-term outcomes, and assessments of patient-reported outcomes and/or functional recovery scores.

CLINICAL RELEVANCE

Preoperatively identifying high-risk orthopaedic surgery patients through frailty instruments has the potential to improve patient outcomes. Frailty screenings can create opportunities for targeted intervention efforts and guide patient-provider decision-making.