Should We Question the External Validity of Database Studies? A Comparative Analysis of Demographics

Characteristics of early complications in isolated primary anterior cruciate ligament reconstruction surgery

PURPOSE

The early complications of isolated anterior cruciate ligament reconstruction surgery (ACLR) have not been well characterized using large databases. This study aims to characterize incidence, impact, and risk factors for short-term operative complications following elective, isolated ACLR surgery. We hypothesize that demographic and perioperative factors may predict 30-day complications after isolated ACLR.

METHODS

This case-control analysis of the American College of Surgeons National Surgical Quality Improvement Program Database (2005-2017) used Current Procedural Terminology codes to identify elective, isolated ACLR patients. Patients undergoing concomitant procedures were excluded. Complications were analyzed using bivariate analysis against demographic variables. Multiple stepwise logistic regression was used to identify independent risk factors for morbidity after ACLR.

RESULTS

A total 12,790 patients (37.0% female, p = 0.674) were included with a mean age of 32.2 years old (SD 10.7 years, p < 0.001). Mean BMI was 27.8 kg/m2 (6.5) where 28.9% of patients had a BMI > 30 (p = 0.064). The most common complications were wound-related (0.57%). In cases with complications, there were higher rates of (1.3% vs 0.8%, p = 0.004) prolonged operation (> 1.5 h), higher rate (2.9% vs 1.8%, p = 0.004) of extended length of stay (≥ 1 day), unplanned reoperation (15.8% vs 0.3%, p < 0.001), and unplanned readmission (17.5% vs 0.3%, p < 0.001). Multivariate analysis showed prolonged operative time (p = 0.001), dyspnea (p = 0.008), and non-ambulatory surgery (p = 0.034) to be predictive of any complication. Dependent functional status (p = 0.091), mFI-5 > 0.2 (= 0.173), female sex (p = 0.191), obesity (p = 0.101), and smoking (p = 0.113) were not risk factors for complications.

CONCLUSION

ACLR is associated with low rates of morbidity and readmissions. The most common comorbidities, complications, and predictors of morbidities were identified to aid surgeons in further reducing adverse outcomes of ACLR. Operative time > 1.5 h, dyspnea, and non-ambulatory surgery are predictive of complications.

Factors associated with increased 30-day re-operation risk in anterior cruciate ligament reconstruction

BACKGROUND

Revision surgery following isolated anterior cruciate ligament reconstruction (ACLR) has often focused on mid- to long-term revisions due to re-rupture, while short-term 30-day revision is a rare, but underappreciated entity. This study aims to characterize incidence and risk factors for reoperations following isolated ACLR.

METHODS

This is a retrospective case-control analysis of the American College of Surgeons National Surgical Quality Improvement Program Database (NSQIP) database from 2005 to 2017. Current Procedural Terminology codes were used to identify elective isolated ACLR patients. Patients undergoing reoperations were analyzed using bivariate analysis against their respective perioperative variables. Multivariate stepwise logistic regression was used to identify independent risk factors for reoperations after ACLR.

RESULTS

12,790 patients were included in the study. 37.0% of patients were female. Mean age was 32.2+/-10.7 years and mean body mass index (BMI) was 27.8+/-6.5 kg/m2, with 28.9% of patients with BMI > 30. The most frequently reported reason for reoperation based on CPT and ICD-9/10 codes was postoperative infection (0.5%). Overall reoperation rate was approximately 0.5%. Multivariate analysis identified operative time >1.5 h (OR 2.6 [95% CI; 1.5-4.4]), dependent functional status (OR 14.0 [1.4-141.6]), and adjunctive anesthesia (OR 2.4 [95% CI; 1.1-5.0]) as independent risk factors for reoperation. Female sex was a protective factor against reoperations (OR 0.6 [0.3-0.98]).

CONCLUSION

Primary, isolated ACLR is associated with extremely low rates of short-term reoperations. Operative time >1.5 h, dependent functional status, and adjunctive anesthesia were independent risk factors for reoperation and female sex was a protective factor against reoperation.

LEVEL OF EVIDENCE

Level III. Retrospective cohort study.

Increased age and modified fragility index increases risk of short-term complications after anterior cruciate ligament reconstruction surgery

BACKGROUND

Large data analysis of anterior cruciate ligament reconstruction (ACLR) short-term complications on age will help surgeons stratify and counsel at-risk patients. The purpose of this study is to assess if older patients are at greater risk for short-term complications after ACLR.

METHODS

This retrospective cohort study included patients who underwent elective ACLR with or without concomitant meniscal procedures in the National Surgical Quality Improvement Program from 2005 to 2017. Patients were divided into age groups 16-30, 31-45, and > 45. Modified fragility index-5 (mFI-5), demographics and short-term outcomes were examined with bivariate and multivariate analysis to determine if age was a risk factor for complications.

RESULTS

A total of 23,581 patients (35.4% female) were included in this analysis. Mean age was 32.1 ± 10.8 years. Older patients had higher mFI-5 scores (p < 0.001), shorter operative times (p < 0.001), lower use of only general anesthesia (p < 0.001). The oldest patients had similar rates of complications as the two younger groups. Older age was an independent risk factor for VTE, but decreased risk of prolonged operations. A mFI-5 > 0 increased risk factors for readmission (Odds ratio 2.2, P = 0.006). Infection was the most common cause 30-day readmissions (40/135, 29.6%).

CONCLUSION

In the early postoperative period, older age is an independent risk factor for VTE and younger age is a significant factor for prolonged surgeries. Having an mFI-5 > 0 increased risk factors for readmission.

Impact of Large Database Studies on Orthopedic Surgery Literature: Are We Advancing the Field?

Background: While database studies have become more prevalent in the literature, there is concern over their value. In addition, the questions they are suitable to answer are limited. Questions/Purposes: We sought to determine the incidence of database studies in the orthopedic literature and in each subspecialty. In addition, we wanted to assess the impact of database studies on the literature by determining whether citations and Altmetric Attention Scores (AAS) varied by study type (studies using internal or external databases and those not using databases). Methods: We searched PubMed for articles published in impactful orthopedic surgery journals in the year 2018. All articles were discoverable on the Altmetric explorer portal database. Impact was determined by journal impact factor. Study design, subspecialty, number of citations, and AAS were obtained. Univariable analyses were conducted between study type, demographic variables, and the outcome of either citation count or AAS. Multivariable analyses were performed to identify independent predictors of the primary outcomes. Subgroup analyses were performed to differentiate the impact of external and internal database studies compared with non-database studies. Results: A total of 2684 total articles were eligible for inclusion. Of these, 366 studies (13.6%) were database studies. Hip and knee articles had the greatest incidence of database studies. Database studies had significantly more citations (5.9 vs 4.0) and significantly higher AAS (12.8 vs 11.3) compared with non-database studies. External database studies had significantly more citations (6.7 vs 4.8) and significantly higher AAS (14.0 vs 10.7) than internal database studies. Internal database studies had higher traditional citation counts but similar AAS to non-database studies. Conclusions: In 2018, database studies in well-reputed orthopedic journals had a greater number of citations but similar AAS compared with non-database studies. Further studies are warranted.

Association of patient characteristics with the receipt of regional anesthesia

BACKGROUND

Regional anesthesia (RA) may improve patient-related outcomes, including decreased operative complications, shortened recovery times, and lower hospital readmission rates. More analyses are needed using a diverse set of databases to examine characteristics associated with the receipt of RA.

METHODS

A national hospital database was queried for patients 18 years or older who underwent total shoulder arthroplasty (TSA), total knee arthroplasty (TKA), anterior cruciate ligament reconstruction (ACLR), carpal tunnel release, ankle open reduction, and internal fixation and arteriovenous fistula creation between January 2016 and June 2021. Regional techniques included neuraxial anesthesia and various upper and lower extremity peripheral nerve blocks to create a binary variable of RA receipt. Univariate statistics were used to compare characteristics associated based on RA receipt and multivariable regression identified factors associated with RA receipt.

RESULTS

A total of 51 776 patients were included in the analysis, of which 2111 (4.1%) received RA. Factors associated with decreased odds of RA receipt included black race (vs white race; OR 0.73, 95% CI 0.62 to 0.86), other non-white race (vs white race; OR 0.71, 95% CI 0.61 to 0.86), American Society of Anesthesiologists (ASA) class (vs ASA 1; OR 0.85, 95% CI 0.79 to 0.93), and Medicaid insurance (vs private insurance; OR 0.65, 95% CI 0.51 to 0.82) (all p<0.05). When compared with TKA, ACLR (OR 0.67, 95% CI 0.53 to 0.84), ankle open reduction and internal fixation (OR 0.68, 95% CI 0.58 to 0.81), and carpal tunnel release (OR 0.68, 95% CI 0.59 to 0.78) demonstrated lower odds of RA receipt, whereas TSA (OR 1.31, 95% CI 1.08 to 1.58) demonstrated higher odds of RA receipt (all p<0.05).

CONCLUSION

RA use varies with respect to race, insurance status, and type of surgery.

Reporting of and explanations for under-recruitment and over-recruitment in pragmatic trials: a secondary analysis of a database of primary trial reports published from 2014 to 2019

OBJECTIVES

To describe the extent to which pragmatic trials underachieved or overachieved their target sample sizes, examine explanations and identify characteristics associated with under-recruitment and over-recruitment.

STUDY DESIGN AND SETTING

Secondary analysis of an existing database of primary trial reports published during 2014-2019, registered in ClinicalTrials.gov, self-labelled as pragmatic and with target and achieved sample sizes available.

RESULTS

Of 372 eligible trials, the prevalence of under-recruitment (achieving <90% of target sample size) was 71 (19.1%) and of over-recruitment (>110% of target) was 87 (23.4%). Under-recruiting trials commonly acknowledged that they did not achieve their targets (51, 71.8%), with the majority providing an explanation, but only 11 (12.6%) over-recruiting trials acknowledged recruitment excess. The prevalence of under-recruitment in individually randomised versus cluster randomised trials was 41 (17.0%) and 30 (22.9%), respectively; prevalence of over-recruitment was 39 (16.2%) vs 48 (36.7%), respectively. Overall, 101 025 participants were recruited to trials that did not achieve at least 90% of their target sample size. When considering trials with over-recruitment, the total number of participants recruited in excess of the target was a median (Q1-Q3) 319 (75-1478) per trial for an overall total of 555 309 more participants than targeted. In multinomial logistic regression, cluster randomisation and lower journal impact factor were significantly associated with both under-recruitment and over-recruitment, while using exclusively routinely collected data and educational/behavioural interventions were significantly associated with over-recruitment; we were unable to detect significant associations with obtaining consent, publication year, country of recruitment or public engagement.

CONCLUSIONS

A clear explanation for under-recruitment or over-recruitment in pragmatic trials should be provided to encourage transparency in research, and to inform recruitment to future trials with comparable designs. The issues and ethical implications of over-recruitment should be more widely recognised by trialists, particularly when designing cluster randomised trials.

Imageless Computer Navigation Reduces 5-Year All-Cause Revision Rates After Primary Total Knee Arthroplasty

BACKGROUND

The use of surgical navigation has been shown to reduce revision rates after total knee arthroplasty (TKA) in patients <65 years of age. It is unknown if this benefit extends to older patients. We hypothesized that the use of surgical navigation would reduce rates of all-cause revision in patients of all ages.

METHODS

In this cohort study, we queried the Truven MarketScan all-payer database to identify patients who underwent TKA from 2007 to 2015. Current Procedural Terminology codes were used to create 2 groups based on whether intraoperative navigation was used. Demographics, comorbidities, complications, and revision rates were determined. International Classification of Diseases codes were used to determine reasons for revision.

RESULTS

The conventional TKA cohort included 312,173 patients. The navigation cohort included 20,881 patients. There were not any clinically significant differences in demographics between the cohorts. All-cause revision rates were lower in the navigation cohort at 1 year (0.4% vs 0.5%, P = .04), 2 years (0.7% vs 0.9%, P = .003), and 5 years (0.9% vs 1.3%, P < .001) of follow-up. Revisions for mechanical loosening were more common in the conventional cohort (30.8% vs 21.9%, P = .009). Rates of revision for other causes, including infection, did not differ between groups, with the numbers available.

CONCLUSION

The use of surgical navigation yielded a 30.7% reduction in the all-cause revision rate at 5-year follow-up compared to conventional TKA. This benefit increased as follow-up duration increased. Increased usage of this inexpensive technology, from the current 6.3% in this US cohort, may reduce healthcare costs.

LEVEL OF EVIDENCE

III.

Reporting and Analyzing Race and Ethnicity in Orthopaedic Clinical Trials: A Systematic Review

BACKGROUND

The distinction between race and ethnicity should be carefully understood and described for demographic data collection. Racial healthcare differences have been observed across many orthopaedic subspecialties. However, the frequency of reporting and analyzing race and ethnicity in orthopaedic clinical trials has not been determined. Therefore, the primary purpose of this systematic review was to determine how frequently race and ethnicity are reported and analyzed in orthopaedic clinical trials.

METHODS

The top 10 journals by impact factor in the field of orthopaedics were manually screened from 2015 to 2019. All randomized controlled trials related to orthopaedics and assessing clinical outcomes were included. Eligible studies were evaluated for bias using the Cochrane risk-of-bias tool and for whether the trial reported and analyzed several demographics, including age, sex, height, weight, race, and ethnicity. The frequency of reporting and analyzing by each demographic was accessed. In addition, comparisons of reporting and analyzing race/ethnicity were made based on orthopaedic subspecialty and journal of publication.

RESULTS

A total of 15,488 publications were screened and 482 met inclusion criteria. Of these 482 trials, 460 (95.4%) reported age and 456 (94.6%) reported sex, whereas 35 (7.3%) reported race and 15 (3.1%) reported ethnicity for the randomized groups; 79 studies (16.4%) analyzed age and 72 studies (14.9%) analyzed sex, whereas 6 studies (1.2%) analyzed race and 1 study (0.2%) analyzed ethnicity. The orthopaedic subspecialty of spine was found to report race (23.5%) and ethnicity (17.6%) more frequently than all the other subspecialties, whereas sports medicine reported race and/or ethnicity in only 3 of 150 trials (2.0%).

CONCLUSIONS

Race and ethnicity are not frequently reported or analyzed in orthopaedic randomized controlled trials. Social context, personal challenges, and economic challenges should be considered while analyzing the effect of race and ethnicity on outcomes.

Editorial Commentary: Big Databases Are Not All Created Equal: Interpret Their Studies With Caution

"Big Data" studies are extremely important in orthopedic research, as randomized controlled trials with extremely large sample sizes are nearly impossible to perform. But, as always, the devil is in the details. Databases are only as good as the information that is put into them. And when evaluating these studies, let's not forget how to interpret them. Many factors-patient insurance status, age, socioeconomic status, ethnicity, and comorbidities; regional variations; hospital status (inpatient/outpatient); clerical errors, recording biases, and omission of relevant orthopedic outcome measures; temporal changes in billing codes; payer mix; population demographics and catchment area; and data collection methodology-mean that the results of a specific big data study may or may not be generalizable to other populations.

Institutional databases may underestimate the risk factors for 30-day unplanned readmissions compared to national databases

OBJECTIVE

The National Surgical Quality Improvement Program (NSQIP) and National Readmissions Database (NRD) are two widely used databases for research studies. However, they may not provide generalizable information in regard to individual institutions. Therefore, the objective of the present study was to evaluate 30-day readmissions following anterior cervical discectomy and fusion (ACDF) and posterior lumbar fusion (PLF) procedures by using these two national databases and an institutional cohort.

METHODS

The NSQIP and NRD were queried for patients undergoing elective ACDF and PLF, with the addition of an institutional cohort. The outcome of interest was 30-day readmissions following ACDF and PLF, which were unplanned and related to the index procedure. Subsequently, univariable and multivariable analyses were conducted to determine the predictors of 30-day readmissions by using both databases and the institutional cohort.

RESULTS

Among all identified risk factors, only hypertension was found to be a common risk factor between NRD and the institutional cohort following ACDF. NSQIP and the institutional cohort both showed length of hospital stay to be a significant predictor for 30-day related readmission following PLF. There were no overlapping variables among all 3 cohorts for either ACDF or PLF. Additionally, the national databases identified a greater number of risk factors for 30-day related readmissions than did the institutional cohort for both procedures.

CONCLUSIONS

Overall, significant differences were seen among all 3 cohorts with regard to top predictors of 30-day unplanned readmissions following ACDF and PLF. The higher quantity of significant predictors found in the national databases may suggest that looking at single-institution series for such analyses may result in underestimation of important variables affecting patient outcomes, and that big data may be helpful in addressing this concern.

Editorial Commentary: "Mo' Data, Mo' Problems"? "Big Data" From National Database Studies in Orthopaedic Research and Concerns Over Generalizability

Publications referencing patient information from national databases such as the National Surgical Quality Improvement Program continue to become more prevalent in the orthopaedic literature. Although there is great value in some of the outcome variables provided by these data sets, concern remains regarding the generalizability of these "big data" studies because patient demographic characteristics such as age, sex, body mass index, and race often differ significantly with high-volume orthopaedic practices, and this may confound the conclusions made. As these national databases continue to be used, we have a responsibility to be critical and analytical in our translation of their findings to daily practice.