Patient-related risk factors for fracture-healing complications in the United Kingdom General Practice Research Database

Hernandez, Rohini K.; P., Thy; Critchlow, Cathy W.; Dent, Ricardo; Jick, Susan S.

doi:10.3109/17453674.2012.747054

Cited by 194 publications

(138 citation statements)

References 22 publications

(19 reference statements)

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“…Patients with type 2 diabetes also have delayed fracture healing, resulting in poorer outcomes after hip fracture (7). Reduced fracture healing in type 2 diabetes is attributable to decreased collagen content, defective cross-linking, alterations in collagen subtype ratios, and collagen defects due to accumulation of advanced glycation end products (8)(9)(10), which could impair osteoblast function.…”

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confidence: 99%

Pathophysiological Mechanism of Bone Loss in Type 2 Diabetes Involves Inverse Regulation of Osteoblast Function by PGC-1α and Skeletal Muscle Atrogenes: AdipoR1 as a Potential Target for Reversing Diabetes-Induced Osteopenia

et al. 2015

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Type 2 diabetes is associated with increased fracture risk and delayed facture healing; the underlying mechanism, however, remains poorly understood. We systematically investigated skeletal pathology in leptin receptor–deficient diabetic mice on a C57BLKS background (db). Compared with wild type (wt), db mice displayed reduced peak bone mass and age-related trabecular and cortical bone loss. Poor skeletal outcome in db mice contributed high-glucose– and nonesterified fatty acid–induced osteoblast apoptosis that was associated with peroxisome proliferator–activated receptor γ coactivator 1-α (PGC-1α) downregulation and upregulation of skeletal muscle atrogenes in osteoblasts. Osteoblast depletion of the atrogene muscle ring finger protein-1 (MuRF1) protected against gluco- and lipotoxicity-induced apoptosis. Osteoblast-specific PGC-1α upregulation by 6-C-β-d-glucopyranosyl-(2S,3S)-(+)-5,7,3′,4′-tetrahydroxydihydroflavonol (GTDF), an adiponectin receptor 1 (AdipoR1) agonist, as well as metformin in db mice that lacked AdipoR1 expression in muscle but not bone restored osteopenia to wt levels without improving diabetes. Both GTDF and metformin protected against gluco- and lipotoxicity-induced osteoblast apoptosis, and depletion of PGC-1α abolished this protection. Although AdipoR1 but not AdipoR2 depletion abolished protection by GTDF, metformin action was not blocked by AdipoR depletion. We conclude that PGC-1α upregulation in osteoblasts could reverse type 2 diabetes–associated deterioration in skeletal health.

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confidence: 99%

Pathophysiological Mechanism of Bone Loss in Type 2 Diabetes Involves Inverse Regulation of Osteoblast Function by PGC-1α and Skeletal Muscle Atrogenes: AdipoR1 as a Potential Target for Reversing Diabetes-Induced Osteopenia

et al. 2015

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“…Pro [32] NSAID use at admission Pro [13,27] Con [17,35] NSAID use at discharge Pro [13,27] Con [17,35] Opioid use at admission Pro [12] Opioid use at discharge Pro [12] Human immunodeficiency virus Pro [24] Con [20] Hepatitis C None Diabetes Pro [13,21,27] ASA score Pro [16] Smoking status Pro [13,21,31,36] Con [29,35] Alcohol use Pro [10,13,21] AO classification Pro [30] Con [2,22] ISS score Pro [30] TRISS score Pro [30] ICU days None * Pro articles support a correlation between nonunion and the variable; Con articles show that the variable has no correlation with nonunion; GSW = gunshot wound; NSAID = nonsteroidal anti-inflammatory drug; ASA = American Society of Anesthesiologists; AO = Arbeitsgemeinschaft für Osteosynthesefragen; ISS = Injury Severity Score; TRISS = Trauma and Injury Severity Score; ICU = intensive care unit.…”

Section: Compartment Syndromementioning

confidence: 99%

Will My Tibial Fracture Heal? Predicting Nonunion at the Time of Definitive Fixation Based on Commonly Available Variables

O’Halloran

Coale

Costales

et al. 2016

Clinical Orthopaedics &Amp; Related Research

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Background Accurate prediction of tibial nonunions has eluded researchers. Reliably predicting tibial nonunions at the time of fixation could change management strategies and stimulate further research. Questions/purposes We asked (1) whether data from medical records, fracture characteristics, and radiographs obtained at the time of fixation would identify features predictive of tibial fracture nonunion; and (2) whether this information could be used to create a model to assess the chance of nonunion at the time of intramedullary (IM) nail fixation of the tibia. Methods We retrospectively reviewed all tibial shaft fractures treated at our center from 2007 to 2014. We conducted a literature review and collected data on 35 factors theorized to contribute to delayed bone healing. Patients were followed to fracture healing or surgery for nonunion. Patients with planned prophylactic nonunion surgery were excluded because their nonunions were anticipated and our focus was on unanticipated nonunions. Our cohort consisted of 382 patients treated with IM nails for tibial shaft fractures (nonunion, 56; healed, 326). Bivariate and multivariate regression techniques and stepwise modeling approaches examined the relationship between variables available at definitive fixation. Factors were included in our model if they were identified as having a modest to large effect size (odds ratio [ 2) at the p \ 0.05 level. Results A multiple variable logistic regression model was developed, including seven factors (p \ 0.05; odds ratio [ 2.0). With these factors, we created the Nonunion Risk Determination (NURD) score. The NURD score assigns 5 points for flaps, 4 points for compartment syndrome, 3 points for chronic condition(s), 2 points for open fractures, 1 point for male gender, and 1 point per grade of American Society of Anesthesiologists Physical Status and percent cortical contact. One point each is subtracted for spiral fractures and for low-energy injuries, which were found to be predictive of union. A NURD score of 0 to 5 had a 2% chance of nonunion; 6 to 8, 22%; 9 to 11, 42%; and[12, 61%. Conclusions The proposed nonunion prediction model (NURDS) seems to have potential to allow clinicians to better determine which patients have a higher risk of nonunion. Future work should be directed at prospectively validating and enhancing this model. Level of Evidence Level III, diagnostic study.

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“…However, progression to nonunion is not fully explained by these factors alone. 6 Determination of the probability for and potential mitigation of nonunion risk is an important clinical objective because patients with nonunion can expect more long-term pain, physical disability, mental health problems, and medical treatment costs as well as a slower return to normal work productivity. 7 Herein, we describe the epidemiology of fracture nonunion in adults, with a focus on information available to the clinician at patient presentation.…”

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confidence: 99%

Epidemiology of Fracture Nonunion in 18 Human Bones

et al. 2016

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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. RESULTSThe 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).C...

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Patient-related risk factors for fracture-healing complications in the United Kingdom General Practice Research Database

Cited by 194 publications

References 22 publications

Pathophysiological Mechanism of Bone Loss in Type 2 Diabetes Involves Inverse Regulation of Osteoblast Function by PGC-1α and Skeletal Muscle Atrogenes: AdipoR1 as a Potential Target for Reversing Diabetes-Induced Osteopenia

Pathophysiological Mechanism of Bone Loss in Type 2 Diabetes Involves Inverse Regulation of Osteoblast Function by PGC-1α and Skeletal Muscle Atrogenes: AdipoR1 as a Potential Target for Reversing Diabetes-Induced Osteopenia

Will My Tibial Fracture Heal? Predicting Nonunion at the Time of Definitive Fixation Based on Commonly Available Variables

Epidemiology of Fracture Nonunion in 18 Human Bones

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