Risk Factors for Nerve Injury After Total Hip Arthroplasty: A Case-Control Study.

BACKGROUND: Postsurgical acute nerve injury is rare but potentially devastating following total hip arthroplasty (THA). Previous literature suggests a wide range of incidence from 0.1% to 7.6%. Confirmed risk factors for these injuries remain unclear. METHODS: THA patients at our institution who developed nerve injury during their admission for THA between January 1, 1998, and December 31, 2013, were systematically identified and matched with 2 control subjects by surgical date. Relevant patient and surgical data were obtained through review of patient charts and electronic health records. We identified potential risk factors and calculated odds ratios (OR) using a conditional logistic regression model with a parsimonious stepwise approach. RESULTS: We identified 93 nerve injuries in 43,761 THAs (0.21%). The mean age of cases was 63 years. Adjusting for other factors in the model, patients <45 years were found to be at increased risk of developing nerve injury (OR, 7.17; P = .033). Similarly, patients with a history of tobacco use (OR, 1.90; P = .030) and a history of spinal surgery or disease (OR, 10.06; P < .001) were also associated with increased risk of nerve injury. For every 30-minute increase in surgery time after 1 hour, risk of nerve injury risk increased (OR, 1.48; P = .034). Assignment as first operative case of the morning was associated with a decreased risk of nerve injury (OR, 0.37, P = .043). CONCLUSION: This study demonstrates that nerve injury is a rare complication following THA at our institution. We found risk factors that are possibly modifiable factors such as lumbar spine disease, smoking, and time of surgical scheduling.

Risk factors for acute nerve injury after total knee arthroplasty.

INTRODUCTION: In this we study identified potential risk factors for post-total knee arthroplasty (TKA) nerve injury, a catastrophic complication with a reported incidence of 0.3%-1.3%. METHODS: Patients who developed post-TKA nerve injury from 1998 to 2013 were identified, and each was matched with 2 controls. A multivariable logistic regression model was built to calculate odds ratios (ORs). RESULTS: Sixty-five nerve injury cases were identified in 39,990 TKAs (0.16%). Females (OR 3.28, P = 0.003) and patients with history of lumbar pathology (OR 6.12, P = 0.026) were associated with increased risk of nerve injury. Tourniquet pressure < 300 mm Hg and longer duration of anesthesia may also be risk factors. DISCUSSION: Surgical planning for females and patients with lumbar pathology should be modified to mitigate their higher risk of neurologic complications after TKA. Our finding that lower tourniquet pressure was associated with higher risk of nerve injury was unexpected and requires further investigation. Muscle Nerve 57: 946-950, 2018.

Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation.

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.

Proteomic signatures in plasma during early acute renal allograft rejection.

Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long term graft survival. Plasma biomarkers may offer an important option for post-transplant monitoring and permit timely and effective therapeutic intervention to minimize graft damage. This case-control discovery study (n = 32) used isobaric tagging for relative and absolute protein quantification (iTRAQ) technology to quantitate plasma protein relative concentrations in precise cohorts of patients with and without biopsy-confirmed acute rejection (BCAR). Plasma samples were depleted of the 14 most abundant plasma proteins to enhance detection sensitivity. A total of 18 plasma proteins that encompassed processes related to inflammation, complement activation, blood coagulation, and wound repair exhibited significantly different relative concentrations between patient cohorts with and without BCAR (p value <0.05). Twelve proteins with a fold-change >or=1.15 were selected for diagnostic purposes: seven were increased (titin, lipopolysaccharide-binding protein, peptidase inhibitor 16, complement factor D, mannose-binding lectin, protein Z-dependent protease and beta(2)-microglobulin) and five were decreased (kininogen-1, afamin, serine protease inhibitor, phosphatidylcholine-sterol acyltransferase, and sex hormone-binding globulin) in patients with BCAR. The first three principal components of these proteins showed clear separation of cohorts with and without BCAR. Performance improved with the inclusion of sequential proteins, reaching a primary asymptote after the first three (titin, kininogen-1, and lipopolysaccharide-binding protein). Longitudinal monitoring over the first 3 months post-transplant based on ratios of these three proteins showed clear discrimination between the two patient cohorts at time of rejection. The score then declined to baseline following treatment and resolution of the rejection episode and remained comparable between cases and controls throughout the period of quiescent follow-up. Results were validated using ELISA where possible, and initial cross-validation estimated a sensitivity of 80% and specificity of 90% for classification of BCAR based on a four-protein ELISA classifier. This study provides evidence that protein concentrations in plasma may provide a relevant measure for the occurrence of BCAR and offers a potential tool for immunologic monitoring.

Molecular signatures of end-stage heart failure.

BACKGROUND: To date, gene expression studies related to chronic heart failure (CHF) have mainly involved microarray analysis of myocardial tissues. The potential utility of blood to infer the etiology, pathogenesis, and course of CHF remains unclear. Further, the use of proteomic and metabolomic platforms for molecular profiling of CHF is relatively unexplored. METHODS: Microarray genomic, iTRAQ proteomic, and nuclear magnetic resonance metabolomic analyses were carried out on blood samples from 29 end-stage CHF patients (16 ischemic heart disease [IHD], 13 nonischemic cardiomyopathy [NICM]), and 20 normal cardiac function (NCF) controls. Robust statistical tests and bioinformatical tools were applied to identify and compare the molecular signatures among these subject groups. RESULTS: No genes or proteins, and only two metabolites, were differentially expressed between IHD and NICM patients at end stage. However, CHF versus NCF comparison revealed differential expression of 7,426 probe sets, 71 proteins, and 8 metabolites. Functional enrichment analyses of the CHF versus NCF results revealed several in-common biological themes and potential mechanisms underlying advanced heart failure. CONCLUSION: Multiple "-omic" analyses support the convergence of dramatic changes in molecular processes underlying IHD and NICM at end stage.

Incidence and Risk of Severe Ileus After Orthopedic Surgery: A Case-Control Study.

BACKGROUND: Post-operative ileus (POI) is common and can be associated with significant morbidity. QUESTIONS/PURPOSES: We aimed to identify the incidence of and risk factors associated with severe post-operative ileus (SPOI) after elective orthopedic surgery. METHODS: We conducted a retrospective case-control study of patients undergoing elective orthopedic procedures at a single musculoskeletal specialty hospital. SPOI cases matched 1:2 to non-POI controls. International Classification of Diseases, Ninth Revision (ICD-9), codes were used to identify patients who were coded as having an episode of POI. After chart review, a subset was classified as clinical SPOI cases, based on set criteria. Regression models were constructed to identify variables associated with SPOI. RESULTS: Of 273 POI cases, 77 (28.2%) were classified as SPOI. Overall rates of SPOI were 2.74/1000 orthopedic discharges, with SPOI most common in spine surgeries (9.07/1000 spine procedure discharges). Hypothesis-generating multivariable conditional logistic regression suggested that, for hip and knee cases, not being on a full diet by post-operative day (POD) 2 posed an increased risk of SPOI. For spine cases, not being on a full diet on POD 2 and longer surgery times were associated with risk of SPOI. CONCLUSIONS: In this retrospective case-control study, patients undergoing elective orthopedic procedures who had not progressed to full diet by POD 2 and spine patients with longer operative times were most at risk for SPOI. These data can be used clinically by peri-operative physicians to stratify patients according to risk.

Postoperative delirium after major orthopedic surgery.

BACKGROUND: Postoperative delirium (POD) is one of the most common complications in older adult patients undergoing elective surgery. Few studies have compared, within the same institution, the type of surgery, risk factors and type of anesthesia and analgesia associated with the development of POD. AIM: To investigate the following three questions: (1) What is the incidence of POD after non-ambulatory orthopedic surgery at a high-volume orthopedic specialty hospital? (2) Does surgical procedure influence incidence of POD after non-ambulatory orthopedic surgery? And (3) For POD after non-ambulatory orthopedic surgery, what are modifiable risk factors? METHODS: A retrospective cohort study was conducted of all non-ambulatory orthopedic surgeries at a single orthopedic specialty hospital between 2009 and 2014. Patients under 18 years were excluded from the cohort. Patient characteristics and medical history were obtained from electronic medical records. Patients with POD were identified using International Classification of Diseases, 9th Revision (ICD-9) codes that were not present on admission. For incidence analyses, the cohort was grouped into total hip arthroplasty (THA), bilateral THA, total knee arthroplasty (TKA), bilateral TKA, spine fusion, other spine procedures, femur/pelvic fracture, and other procedures using ICD-9 codes. For descriptive and regression analyses, the cohort was grouped, using ICD-9 codes, into THA, TKA, spinal fusions, and all procedures. RESULTS: Of 78492 surgical inpatient surgeries, the incidence from 2009 to 2014 was 1.2% with 959 diagnosed with POD. The incidence of POD was higher in patients undergoing spinal fusions (3.3%) than for patients undergoing THA (0.8%); THA patients had the lowest incidence. Also, urgent and/or emergent procedures, defined by femoral and pelvic fractures, had the highest incidence of POD (7.2%) than all other procedures. General anesthesia was not seen as a significant risk factor for POD for any procedure type; however, IV patient-controlled analgesia was a significant risk factor for patients undergoing THA [Odds ratio (OR) = 1.98, 95% confidence interval (CI): 1.19 to 3.28, P = 0.008]. Significant risk factors for POD included advanced age (for THA, OR = 4.9, 95%CI: 3.0-7.9, P < 0.001; for TKA, OR = 2.16, 95%CI: 1.58-2.94, P < 0.001), American Society of Anesthesiologists score of 3 or higher (for THA, OR = 2.01, 95%CI: 1.33-3.05, P < 0.001), multiple medical comorbidities, hyponatremia (for THA, OR = 2.36, 95%CI: 1.54 to 3.64, P < 0.001), parenteral diazepam (for THA, OR = 5.05, 95%CI: 1.5-16.97, P = 0.009; for TKA, OR = 4.40, 95%CI: 1.52-12.75, P = 0.007; for spine fusion, OR = 2.17, 95%CI: 1.19-3.97, P = 0.01), chronic opioid dependence (for THA, OR = 7.11, 95%CI: 3.26-15.51, P < 0.001; for TKA, OR = 2.98, 95%CI: 1.38-6.41, P = 0.005) and alcohol dependence (for THA, OR = 5.05, 95%CI: 2.72-9.37, P < 0.001; for TKA, OR = 6.40, 95%CI: 4.00-10.26, P < 0.001; for spine fusion, OR = 6.64, 95%CI: 3.72-11.85, P < 0.001). CONCLUSION: POD is lower (1.2%) than previously reported; likely due to the use of multi-modal regional anesthesia and early ambulation. Both fixed and modifiable factors are identified.

PGCA: An algorithm to link protein groups created from MS/MS data.

The quantitation of proteins using shotgun proteomics has gained popularity in the last decades, simplifying sample handling procedures, removing extensive protein separation steps and achieving a relatively high throughput readout. The process starts with the digestion of the protein mixture into peptides, which are then separated by liquid chromatography and sequenced by tandem mass spectrometry (MS/MS). At the end of the workflow, recovering the identity of the proteins originally present in the sample is often a difficult and ambiguous process, because more than one protein identifier may match a set of peptides identified from the MS/MS spectra. To address this identification problem, many MS/MS data processing software tools combine all plausible protein identifiers matching a common set of peptides into a protein group. However, this solution introduces new challenges in studies with multiple experimental runs, which can be characterized by three main factors: i) protein groups' identifiers are local, i.e., they vary run to run, ii) the composition of each group may change across runs, and iii) the supporting evidence of proteins within each group may also change across runs. Since in general there is no conclusive evidence about the absence of proteins in the groups, protein groups need to be linked across different runs in subsequent statistical analyses. We propose an algorithm, called Protein Group Code Algorithm (PGCA), to link groups from multiple experimental runs by forming global protein groups from connected local groups. The algorithm is computationally inexpensive and enables the connection and analysis of lists of protein groups across runs needed in biomarkers studies. We illustrate the identification problem and the stability of the PGCA mapping using 65 iTRAQ experimental runs. Further, we use two biomarker studies to show how PGCA enables the discovery of relevant candidate protein group markers with similar but non-identical compositions in different runs.

Plasma protein biosignatures for detection of cardiac allograft vasculopathy.

BACKGROUND: Coronary angiography remains the most widely used tool for routine screening and diagnosis of cardiac allograft vasculopathy (CAV), a major pathologic process that develops in 50% of cardiac transplant recipients beyond the first year after transplant. Given the invasiveness, expense, discomfort, and risk of complications associated with angiography, a minimally invasive alternative that is sensitive and specific would be highly desirable for monitoring CAV in patients. METHODS: Plasma proteomic analysis using isobaric tags for relative and absolute quantitation-matrix-assisted laser desorption ionization double time-of-flight mass spectrometry was carried out on samples from 40 cardiac transplant patients (10 CAV, 9 non-significant CAV, 21 possible CAV). Presence of CAV was defined as left anterior descending artery diameter stenosis ≥ 40% by digital angiography and quantitatively measured by blinded expert appraisal. Moderated t-test robust-linear models for microarray data were used to identify biomarkers that are significantly differentially expressed between patient samples with CAV and with non-significant CAV. A proteomic panel for diagnosis of CAV was generated using the Elastic Net classification method. RESULTS: We identified an 18-plasma protein biomarker classifier panel that was able to classify and differentiate patients with angiographically significant CAV from those without significant CAV, with an 80% sensitivity and 89% specificity, while providing insight into the possible underlying immune and non-alloimmune contributory mechanisms of CAV. CONCLUSION: Our results support of the potential utility of proteomic biomarker panels as a minimally invasive means to identify patients with significant, angiographically detectable coronary artery stenosis in the cardiac allograft, in the context of post-cardiac transplantation monitoring and screening for CAV. The potential biologic significance of the biomarkers identified may also help improve our understanding of CAV pathophysiology.

Comparison of free light chain removal by four blood purification methods.

Renal failure is a frequent complication in patients with multiple myeloma. Immunoglobulin free light chains (FLCs) form casts in the distal tubules, resulting in renal obstruction, and are also directly toxic to proximal renal tubules. Removal of FLCs contributes to renal recovery. High cut-off (HCO) membrane Theralite2100, protein leaking dialyzer PES210Dα, plasma separator Evacure1A20 and ß(2) microglobulin adsorption column LixelleS-35 were compared in their FLC removal rate. Dialysis using Theralite2100 or Evacure1A20, diafiltration using PES210Dα and adsorption using LixelleS-35 were performed in an in vitro circuit. The highest removal rate was obtained by Theralite2100 dialysis among the four blood purification methods. Albumin loss was also the greatest in Theralite2100 dialysis. The removal content of FLCs per 1 g albumin loss was better in PES210Dα diafiltration. The removal rate of FLCs by Evacure EC1A-20 dialysis was the third highest. Adsorption of FLCs by the ß(2) microglobulin adsorption column Lixelle S-35 was confirmed. In conclusion, Theralite2100 dialysis was the best in removal of FLCs. PES210Dα diafiltration can remove FLCs with smaller loss of albumin.