Serious adverse events and 30-day hospital readmission rate following elective total knee arthroplasty: a systematic review and meta-analysis.

BACKGROUND: Elective total knee arthroplasty (TKA) is a common surgery which has evolved rapidly. However, there are no recent large systematic reviews of serious adverse event (SAE) rate and 30-day readmission rate (30-dRR) or an indication of whether surgical methods have improved. METHODS: To obtain a pooled estimate of SAE rate and 30-dRR following TKA, we searched Medline, Web of Science, Cochrane Library, and Google Scholar databases. Data were extracted by two authors following PRISMA guidelines. Eligibility criteria were defined prior to a comprehensive search. Studies were eligible if they were published in 2007 or later, described sequelae of TKA with patient N > 1000, and the SAE or 30-dRR rate could be calculated. SAEs included return to operating room, death or coma, venous thromboembolism (VTE), deep infection or sepsis, myocardial infarction, heart failure or cardiac arrest, stroke or cerebrovascular accident, or pneumonia. RESULTS: Of 248 references reviewed, 28 are included, involving 10,153,503 patients; this includes 9,483,387 patients with primary TKA (pTKA), and 670,116 patients with revision TKA (rTKA). For pTKA, the SAE rate was 5.7% (95% CI 4.4-7.2%, I2 = 100%), and the 30-dRR was 4.8% (95% CI 4.3-5.4%, I2 = 100%). For rTKA, the SAE rate was 8.5% (95% CI 8.3-8.7%, I2 = 77%), while the 30-dRR was 7.2% (95% CI 6.4-8.0%, I2 = 81%). Odds of 30-dRR following pTKA were about half that of rTKA (OR 0.57, 95% CI 0.53-0.62%, p < 0.001, I2 = 45%). Of patients who received pTKA, the commonest SAEs were VTE (1.22%; 95% CI 0.83-1.70%) and genitourinary complications including renal insufficiency or renal failure (1.22%; 95% CI 0.83-1.67%). There has been significant improvement in SAE rate and 30-dRR since 2010 (χ2 test < 0.001). CONCLUSIONS: TKA procedures have a relatively low complication rate, and there has been a significant improvement in SAE rate and 30-dRR over the past decade.

Delayed Healing in Metatarsal Fractures: Role of Low-Intensity Pulsed Ultrasound Treatment.

The most common fracture in primary care is metatarsal fracture, but it is controversial whether to treat this fracture conservatively or surgically. We performed a cohort study to contrast metatarsal fractures that heal normally with fractures that show delayed healing. We analyzed 5% Medicare Standard Analytic Files, selecting all metatarsal fractures in 2011 to 2013, excluding patients with multiple fractures. Delayed healing was defined as treatment >14 days postfracture with either low-intensity pulsed ultrasound or surgery. Treatment for delayed healing was identified using the Current Procedural Terminology and International Classification of Diseases, Revision 9, Clinical Modification codes. Among 9482 metatarsal fractures, 256 (2.7%) showed delayed healing. Patients with delayed healing were younger (p < .0001); more likely to receive specialist referral (p < .001); more likely to have obesity (p = .005), psychosis (p = .003), chronic lung disease (p = .012), or iron deficiency anemia (p = .016); and more likely to receive surgery before ultrasound (p < .0001). Patients more likely to be treated with surgery than ultrasound included younger patients (p < .0001), obese patients (p = .02), and patients who first see a specialist (p < .05).

Nonunion and Reoperation After Internal Fixation of Proximal Femur Fractures: A Systematic Review.

Nonunion after fixation of a proximal femur fracture is associated with increased disability, pain, and cost to both patient and health care system. Understanding the effect of fixation method and fracture pattern on healing is important to optimize healing. The authors evaluated surgical healing, nonunion rate, and reoperation rate after internal fixation of proximal femur fracture, especially since the year 2000. They performed a systematic review of all published records from PubMed, Embase, and the Cochrane Review system. The burden of proximal femoral fracture extends beyond acute disability, as it carries a high risk of long-term morbidity and mortality. Choice of fixation method for high-risk fractures is critical to reduce nonunion and reoperation rates. [Orthopedics. 2019; 42(2):e162-e171.].

Risk factors for nonunion of bone fracture in pediatric patients: An inception cohort study of 237,033 fractures.

Adult fracture nonunion risk is related to injury severity and surgical technique, yet nonunion is not fully explained by these risk factors alone; biological risk factors are also important. We test a hypothesis that risk factors associated with pediatric fracture nonunion are similar to adult nonunion risk factors.Inception cohort study in a large payer database of pediatric fracture patients (0-17 years) in the United States in calendar year 2011. Continuous enrollment in the database was required for 12 months, to allow time to capture a nonunion diagnosis. The final database collated demographic descriptors, treatment procedures as per Current Procedural Terminology (CPT) codes, comorbidities as per International Statistical Classification of Diseases and Related Health Problems (ICD-9) codes, and drug prescriptions as per National Drug Code Directory (Red Book) codes. Logistic regression was used to calculate odds ratios (ORs) for variables associated with nonunion.Among 237,033 pediatric fractures in 18 bones, the nonunion rate was 0.85%. Increased nonunion risk was associated with increasing age, male gender, high body-mass index, severe fracture (e.g., open fracture, multiple fractures), and tobacco smoking (all, P < .0001). Nonunion rate varied with fracture location; scaphoid, neck of femur, and tibia/fibula were most likely to go to nonunion. Nonunion ORs were significantly increased for risk factors including; surgical procedure, cardiovascular disease, Vitamin D deficiency, osteoarthritis, osteoporosis, and opioid prescription (all, multivariable P < .001).Nonunion is rare in pediatric patients, but nonunion risk increases with increasing age. We confirm a hypothesis that risk factors for pediatric nonunion are similar to adult nonunion risk factors. Scaphoid fractures in adolescents have nearly the same risk of nonunion as in adults. Opioids should be used cautiously in pediatric patients, as they are associated with a significant and substantial elevation of nonunion risk. LEVEL OF EVIDENCE: Prognostic study, Retrospective, Level II.

Opioid exposure is associated with nonunion risk in a traumatically injured population: An inception cohort study.

INTRODUCTION: Certain common medications are associated with an elevated risk of fracture and recent data suggests that medications can also increase nonunion risk. Medication use is a modifiable nonunion risk factor, but it is unknown whether risk accrues solely to chronic medication use or whether there is also risk inherent to acute use. METHODS: Multivariate logistic regression was used in an inception cohort to calculate odds ratios (OR) for fracture nonunion associated with medication use, in context with other risk factors demonstrated to influence nonunion. Patient-level health claims for medical and drug expenses were compiled from a payer database. Patients were included if they had a fracture coded in 2011, with continuous enrollment for 1 month prior to and 12 months after fracture. The database contained demographic descriptors, treatment procedures per CPT codes, co-morbidities per ICD-9 codes, and prescriptions per National Drug Codes. Chronic medication use was defined as ≥30 days of prescription prior to fracture with ≥1 day afterward; acute use was any other prescription. RESULTS: Most non-analgesic medications were safe in acute or chronic use, but risk of nonunion was elevated for a wide range of analgesics. Overall, 45,085 fractures (14.6% of fractures) affected patients using chronic opioids. Nonunion OR was elevated for acute and chronic use of Schedule 2 opioids including acetaminophen/oxycodone, hydromorphone, oxycodone, and acetaminophen/hydrocodone bitartrate, as well as Schedule 3-5 opioids including tramadol (all, p < 0.0001). The highest ORs were associated with chronic administration of Schedule 2 opioids. DISCUSSION: Most medications do not increase nonunion risk, but acute and chronic use of NSAIDs or opioids was associated with impaired fracture healing. There is particular risk in prescribing opioid analgesics for fracture, though literature suggests that roughly half of opioid-naïve patients receive such a prescription. CONCLUSIONS: Patients evaluated in this study were not a random sample of Americans; they may approximate a random sample of the Emergency Department population in the United States. Thus, trauma patients may represent a population enriched for nonunion risk factors. Opioids impair recovery from injury; if they also predispose to injury, the ongoing opioid epidemic could presage an increase in nonunion prevalence.

Healing, nonunion, and re-operation after internal fixation of diaphyseal and distal femoral fractures: a systematic review and meta-analysis.

PURPOSE: Nonunion is a highly morbid complication that exacerbates the pain, disability and financial burden of distal and diaphyseal femur fractures. This study examined the modern rates of healing, nonunion, and other complications requiring reoperation of different fixation methods for distal and diaphyseal femur fractures. METHODS: A systematic review and meta-analysis of all records from PubMed, Embase and the Cochrane Review system was performed. Included studies had >20 acute, non-pathologic distal or diaphyseal femur fractures treated with primary internal fixation. Excluded were studies on abnormal patient/fracture populations, external fixation, or cement/bone graft use. RESULTS: Thirty-eight studies with 2,829 femoral shaft fractures and 11 studies with 505 distal femur fractures were included. Distal fractures had a lower healing rate (86.6% vs. 93.7%) and a higher re-operation rate (13.4% vs 6.1%) than shaft fractures (p < 0.00001), primarily due to higher rates of mechanical failure (p < 0.00001). Nonunion was the most frequent complication, occurring in 4.7% of distal fractures and 2.8% of shaft fractures. There was no difference between plate and nail fixation of distal fractures in healing, nonunion, or other causes of re-operation. Shaft fractures developed nonunion in 6.6% of unreamed nails and 2.1% of reamed nails (p = 0.002). Nonunion occurred in 2.3% of antegrade nailed fractures and 1.5% of retrograde nailed fractures (p = 0.66). CONCLUSIONS: Approximately one out of every eight distal fractures and one of every 16 shaft fractures requires re-operation. The most common cause of fixation failure is nonunion. Further research is needed to improve outcomes, particularly in distal femur fractures.

Healing of fracture nonunions treated with low-intensity pulsed ultrasound (LIPUS): A systematic review and meta-analysis.

INTRODUCTION: Bone fractures fail to heal and form nonunions in roughly 5% of cases, with little expectation of spontaneous healing thereafter. We present a systematic review and meta-analysis of published papers that describe nonunions treated with low-intensity pulsed ultrasound (LIPUS). METHODS: Articles in PubMed, Ovid MEDLINE, CINAHL, AMED, EMBASE, Cochrane Library, and Scopus databases were searched, using an approach recommended by the Methodological Index for Non-Randomized Studies (MINORS), with a Level of Evidence rating by two reviewers independently. Studies are included here if they reported fractures older than 3 months, presented new data with a sample N≥12, and reported fracture outcome (Heal/Fail). RESULTS: Thirteen eligible papers reporting LIPUS treatment of 1441 nonunions were evaluated. The pooled estimate of effect size for heal rate was 82% (95% CI: 77-87%), for any anatomical site and fracture age of at least 3 months, with statistical heterogeneity detected across all primary studies (Q=41.2 (df=12), p<0.001, Tau2=0.006, I2=71). With a stricter definition of nonunion as fracture age of at least 8 months duration, the pooled estimate of effect size was 84% (95% CI: 77%-91.6%; heterogeneity present: Q=21 (df=8), p<0.001, Tau2=0.007, I2=62). Hypertrophic nonunions benefitted more than biologically inactive atrophic nonunions. An interval without surgery of <6months prior to LIPUS was associated with a more favorable result. Stratification of nonunions by anatomical site revealed no statistically significant differences between upper and lower extremity long bone nonunions. CONCLUSIONS: LIPUS treatment can be an alternative to surgery for established nonunions. Given that no spontaneous healing of established nonunions is expected, and that it is challenging to test the efficacy of LIPUS for nonunion by randomized clinical trial, findings are compelling. LIPUS may be most useful in patients for whom surgery is high risk, including elderly patients at risk of delirium, or patients with dementia, extreme hypertension, extensive soft-tissue trauma, mechanical ventilation, metabolic acidosis, multiple organ failure, or coma. With an overall average success rate for LIPUS >80% this is comparable to the success of surgical treatment of non-infected nonunions.

An inception cohort analysis to predict nonunion in tibia and 17 other fracture locations.

INTRODUCTION: The epidemiology of fracture nonunion has been characterized so it is potentially possible to predict nonunion using patient-related risk factors. However, prediction models are currently too cumbersome to be useful. We test a hypothesis that nonunion can be predicted with ≤10 variables, retaining the predictive accuracy of a full model with 42 variables. METHODS: We sought to predict nonunion with prospectively-acquired inception cohort data for 18 different bones, using the smallest possible number of variables that did not substantially decrease prediction accuracy. An American nationwide claims database of ∼90.1 million participants was used, which included medical and drug expenses for 2011-2012. Continuous enrollment was required for 12 months after fracture, to allow sufficient time to capture a nonunion diagnosis. Health claims were evaluated for 309,330 fractures. A training dataset used a random subset of 2/3 of these fractures, while the remaining fractures formed a validation dataset. Multivariate logistic regression and stepwise logistic regression were used to identify variables predictive of nonunion. P value and the Akaike Information Criterion (AIC) were used to select variables for reduced models. Area-under-the-curve (AUC) was calculated to characterize the success of prediction. RESULTS: Nonunion rate in 18 fracture locations averaged 4.93%. Algorithms to predict nonunion in 18 locations in the full-model validation set had average AUC=0.680 (±0.034). In the reduced models, average validation set AUC=0.680 (±0.033) and the average number of risk factors required for prediction was 7.6. There was agreement across training set, validation set, and reduced set; in tibia, reduced model validation AUC=0.703, while the full-model validation AUC=0.709. Certain risk factors were important for predicting nonunion in ≥10 bones, including open fracture, multiple fracture, osteoarthritis, surgical treatment, and use of certain medications, including anticoagulants, anticonvulsants, or analgesics. DISCUSSION: Nonunion can be predicted in 18 fracture locations using parsimonious models with <10 patient demography-related risk factors. The model reduction approach used results in simplified models that have nearly the same AUC as the full model. Reduced algorithms can predict nonunion because risk factors important in the full models remain important in the reduced models. This prognostic inception cohort study provides Level I evidence.

When Is a Fracture Not "Fresh"? Aligning Reimbursement With Patient Outcome After Treatment With Low-Intensity Pulsed Ultrasound.

OBJECTIVE: The clinical value of low-intensity pulsed ultrasound (LIPUS) for fresh fracture is known. Yet, in the absence of a definition of what "fresh" is, payers have adopted study inclusion criteria drawn from randomized clinical trials as de facto definitions of which patients should be treated, with "fresh" defined as <1 week old. Patients with fracture may thus be ineligible for LIPUS treatment after week 1, which potentially denies access to patients who could benefit from LIPUS. We seek to characterize the inflection point at which heal rate declines. DESIGN: Prospective cohort. SETTING: Food and Drug Administration-mandated nationwide postmarketing surveillance registry. PATIENTS: Observational cohort of 5983 registry enrollees. INTERVENTION: LIPUS, 20 min/d. MAIN OUTCOME MEASURE: Fracture heal rate. Logistic regression was used to model the odds ratio of nonunion from week 1 to week 12. Covariates in the model included age, gender, body mass index, open fracture, and smoking. RESULTS: We estimated the time point at which a fracture responds to LIPUS as well as during the first week after fracture. There was significant bone-to-bone variation; metatarsal was "fresh" until week 7, ankle until week 9, humerus until week 10, and femur and radius until week 12. Healing was significantly impacted by patient age, body mass index, and open fracture (all, P ≤ 0.02). CONCLUSIONS: Our results suggest that fractures of the metatarsal, femur, humerus, ankle, and radius respond to LIPUS treatment, as if they were still fresh at least 6 weeks longer than the eligibility allowed under current coverage policies. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Bone fracture nonunion rate decreases with increasing age: A prospective inception cohort study.

BACKGROUND: Fracture nonunion risk is related to severity of injury and type of treatment, yet fracture healing is not fully explained by these factors alone. We hypothesize that patient demographic factors assessable by the clinician at fracture presentation can predict nonunion. METHODS: A prospective cohort study design was used to examine ~2.5 million Medicare patients nationwide. Patients making fracture claims in the 5% Medicare Standard Analytic Files in 2011 were analyzed; continuous enrollment for 12months after fracture was required to capture the ICD-9-CM nonunion diagnosis code (733.82) or any procedure codes for nonunion repair. A stepwise regression analysis was used which dropped variables from analysis if they did not contribute sufficient explanatory power. In-sample predictive accuracy was assessed using a receiver operating characteristic (ROC) curve approach, and an out-of-sample comparison was drawn from the 2012 Medicare 5% SAF files. RESULTS: Overall, 47,437 Medicare patients had 56,492 fractures and 2.5% of fractures were nonunion. Patients with healed fracture (age 75.0±12.7SD) were older (p<0.0001) than patients with nonunion (age 69.2±13.4SD). The death rate among all Medicare beneficiaries was 4.8% per year, but fracture patients had an age- and sex-adjusted death rate of 11.0% (p<0.0001). Patients with fracture in 14 of 18 bones were significantly more likely to die within one year of fracture (p<0.0001). Stepwise regression yielded a predictive nonunion model with 26 significant explanatory variables (all, p≤0.003). Strength of this model was assessed using an area under the curve (AUC) calculation, and out-of-sample AUC=0.710. CONCLUSIONS: A logistic model predicted nonunion with reasonable accuracy (AUC=0.725). Within the Medicare population, nonunion patients were younger than patients who healed normally. Fracture was associated with increased risk of death within 1year of fracture (p<0.0001) in 14 different bones, confirming that geriatric fracture is a major public health issue. Comorbidities associated with increased risk of nonunion include past or current smoking, alcoholism, obesity or morbid obesity, osteoarthritis, rheumatoid arthritis, type II diabetes, and/or open fracture (all, multivariate p<0.001). Nonunion prediction requires knowledge of 26 patient variables but predictive accuracy is currently comparable to the Framingham cardiovascular risk prediction.

Epidemiology of Fracture Nonunion in 18 Human Bones.

Importance: Failure of bone fracture healing occurs in 5% to 10% of all patients. Nonunion risk is associated with the severity of injury and with the surgical treatment technique, yet progression to nonunion is not fully explained by these risk factors. Objective: To test a hypothesis that fracture characteristics and patient-related risk factors assessable by the clinician at patient presentation can indicate the probability of fracture nonunion. Design, Setting, and Participants: An inception cohort study in a large payer database of patients with fracture in the United States was conducted using patient-level health claims for medical and drug expenses compiled for approximately 90.1 million patients in calendar year 2011. The final database collated demographic descriptors, treatment procedures as per Current Procedural Terminology codes; comorbidities as per International Classification of Diseases, Ninth Revision codes; and drug prescriptions as per National Drug Code Directory codes. Logistic regression was used to calculate odds ratios (ORs) for variables associated with nonunion. Data analysis was performed from January 1, 2011, to December 31, 2012. Exposures: Continuous enrollment in the database was required for 12 months after fracture to allow sufficient time to capture a nonunion diagnosis. Results: The final analysis of 309 330 fractures in 18 bones included 178 952 women (57.9%); mean (SD) age was 44.48 (13.68) years. The nonunion rate was 4.9%. Elevated nonunion risk was associated with severe fracture (eg, open fracture, multiple fractures), high body mass index, smoking, and alcoholism. Women experienced more fractures, but men were more prone to nonunion. The nonunion rate also varied with fracture location: scaphoid, tibia plus fibula, and femur were most likely to be nonunion. The ORs for nonunion fractures were significantly increased for risk factors, including number of fractures (OR, 2.65; 95% CI, 2.34-2.99), use of nonsteroidal anti-inflammatory drugs plus opioids (OR, 1.84; 95% CI, 1.73-1.95), operative treatment (OR, 1.78; 95% CI, 1.69-1.86), open fracture (OR, 1.66; 95% CI, 1.55-1.77), anticoagulant use (OR, 1.58; 95% CI, 1.51-1.66), osteoarthritis with rheumatoid arthritis (OR, 1.58; 95% CI, 1.38-1.82), anticonvulsant use with benzodiazepines (OR, 1.49; 95% CI, 1.36-1.62), opioid use (OR, 1.43; 95% CI, 1.34-1.52), diabetes (OR, 1.40; 95% CI, 1.21-1.61), high-energy injury (OR, 1.38; 95% CI, 1.27-1.49), anticonvulsant use (OR, 1.37; 95% CI, 1.31-1.43), osteoporosis (OR, 1.24; 95% CI, 1.14-1.34), male gender (OR, 1.21; 95% CI, 1.16-1.25), insulin use (OR, 1.21; 95% CI, 1.10-1.31), smoking (OR, 1.20; 95% CI, 1.14-1.26), benzodiazepine use (OR, 1.20; 95% CI, 1.10-1.31), obesity (OR, 1.19; 95% CI, 1.12-1.25), antibiotic use (OR, 1.17; 95% CI, 1.13-1.21), osteoporosis medication use (OR, 1.17; 95% CI, 1.08-1.26), vitamin D deficiency (OR, 1.14; 95% CI, 1.05-1.22), diuretic use (OR, 1.13; 95% CI, 1.07-1.18), and renal insufficiency (OR, 1.11; 95% CI, 1.04-1.17) (multivariate P < .001 for all). Conclusions and Relevance: The probability of fracture nonunion can be based on patient-specific risk factors at presentation. Risk of nonunion is a function of fracture severity, fracture location, disease comorbidity, and medication use.

Heal rate of metatarsal fractures: A propensity-matching study of patients treated with low-intensity pulsed ultrasound (LIPUS) vs. surgical and other treatments.

INTRODUCTION: Whether to treat metatarsal fractures conservatively or surgically is controversial. We test a hypothesis that metatarsal fractures treated conservatively with non-invasive low-intensity pulsed ultrasound (LIPUS) obtain heal rates comparable to current surgical techniques. PATIENTS AND METHODS: This is a retrospective observational cohort study, using patient outcomes from a prospectively-collected LIPUS registry required by the U.S. Food & Drug Administration. Registry data were collected over a 5-year period and were reviewed and validated by a registered nurse. Data required for analysis were days-to-treatment (DTT) with LIPUS and a dichotomous outcome of healed versus failed, as assessed by clinical and radiographic criteria. Registry patients (DTT<365days) were propensity-matched to metatarsal fracture patients from a health claims database that includes medical and drug expenses for ∼90.1 million patients. The propensity match was based on patient demographic data (age, gender, body weight, fracture severity, and smoking status). RESULTS: A total of 594 metatarsal fractures were treated with LIPUS, including 161 Jones fractures. Compared to patients in the claims database, LIPUS-treated patients were more likely to: be overweight or obese; be male; have open fracture; and smoke (all, P<0.0001), suggesting that these variables were perceived as nonunion risk factors by prescribing physicians. After propensity-matching, none of these differences between the registry and the health claims database remained significant. The heal rate with LIPUS treatment was 97.3%, comparable to the heal rate of 95.3% among claims patients in 2011 who did not receive LIPUS (P=0.0654). When fresh fractures (0-90days) and delayed unions (91-365days) were analyzed separately, the LIPUS fresh fracture heal rate was superior to claims patients (P=0.0381), and the delayed union heal rate was comparable. After exclusion of registry patients who received surgery, heal rate with LIPUS alone (97.4%) was significantly better (P<0.0097) than the heal rate for matched patients in 2011 (94.2%). CONCLUSIONS: LIPUS significantly improved the heal rate of metatarsal fractures <1year old without surgery (P=0.0097). Metatarsal fractures treated with LIPUS alone have a heal rate comparable to fractures treated by surgical intervention.

Biological Risk Factors for Nonunion of Bone Fracture.

Many risk factors for fracture nonunion are well supported in the orthopaedic literature, including location of the fracture site, surgical treatment, bone displacement, type of fixation, treatment delay, comminution, inadequate treatment, and wound infection. However, evidence from a systematic review suggests that patient-related or biological causes of nonunion may not be as well understood. Understanding the biological causes of nonunion is important for several reasons. Risk factors might identify patients prone to nonunion who could benefit from more aggressive intervention, and a clear idea of nonunion risk could be important when choosing between competing therapeutic options. Risk factors also can inform the design of clinical trials and clarify patient inclusion and exclusion criteria, so that small studies can yield more definitive answers. Finally, an understanding of patient risk profiles may enable clinicians to counsel patients more effectively and to set appropriate expectations for success. Patient age appears to be a strong risk factor for nonunion in some bones, a weak risk factor for nonunion in other bones, and perhaps not a significant risk factor for nonunion in certain bones. This observation suggests that there can be substantial bone-to-bone variation in nonunion risk. Age also may be a surrogate for the prevalence of risk factors that potentially increase with age, such as smoking, diabetes, obesity, or nonsteroidal anti-inflammatory drug (NSAID) use. Smoking has been replicated as a risk factor for nonunion only in retrospective studies involving the humerus and tibia. Smoking appears to have an important effect on nonunion, yet the incremental risk may be rather small, except in context with additional risk factors. Diabetes has been confirmed as a risk factor for nonunion only in retrospective studies involving the foot and ankle. Nonunion risk from diabetes alone may be small and the context of additional risk factors crucial; this could account for why it has been so difficult to predict nonunion in the individual patient. Prediction of fracture nonunion in the individual patient is a difficult problem. Fracture nonunion may be influenced by complex interactions between biological and surgical risk factors, and the nonunion rate varies from bone to bone. A randomized clinical trial may not appropriately control for all potential correlates and confounders and may require impractical sample sizes. A large claims-based study of real-world fracture-healing outcomes is needed to provide guidance for randomized clinical trials that can test risk factors more rigorously.