Characterisation of Canine and Feline Breast Tumours, Their Metastases, and Corresponding Primary Cell Lines Using LA-REIMS and DESI-MS Imaging.

Breast cancer, a complex disease with a significant prevalence to form metastases, necessitates novel therapeutic strategies to improve treatment outcomes. Here, we present the results of a comparative molecular study of primary breast tumours, their metastases, and the corresponding primary cell lines using Desorption Electrospray Ionisation (DESI) and Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS) imaging. Our results show that ambient ionisation mass spectrometry technology is suitable for rapid characterisation of samples, providing a lipid- and metabolite-rich spectrum within seconds. Our study demonstrates that the lipidomic fingerprint of the primary tumour is not significantly distinguishable from that of its metastasis, in parallel with the similarity observed between their respective primary cell lines. While significant differences were observed between tumours and the corresponding cell lines, distinct lipidomic signatures and several phospholipids such as PA(36:2), PE(36:1), and PE(P-38:4)/PE(O-38:5) for LA-REIMS imaging and PE(P-38:4)/PE(O-38:5), PS(36:1), and PI(38:4) for DESI-MSI were identified in both tumours and cells. We show that the tumours' characteristics can be found in the corresponding primary cell lines, offering a promising avenue for assessing tumour responsiveness to therapeutic interventions. A comparative analysis by DESI-MSI and LA-REIMS imaging revealed complementary information, demonstrating the utility of LA-REIMS in the molecular imaging of cancer.

Metabolomic profiling and accurate diagnosis of basal cell carcinoma by MALDI imaging and machine learning.

Basal cell carcinoma (BCC), the most common keratinocyte cancer, presents a substantial public health challenge due to its high prevalence. Traditional diagnostic methods, which rely on visual examination and histopathological analysis, do not include metabolomic data. This exploratory study aims to molecularly characterize BCC and diagnose tumour tissue by applying matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) and machine learning (ML). BCC tumour development was induced in a mouse model and tissue sections containing BCC (n = 12) were analysed. The study design involved three phases: (i) Model training, (ii) Model validation and (iii) Metabolomic analysis. The ML algorithm was trained on MS data extracted and labelled in accordance with histopathology. An overall classification accuracy of 99.0% was reached for the labelled data. Classification of unlabelled tissue areas aligned with the evaluation of a certified Mohs surgeon for 99.9% of the total tissue area, underscoring the model's high sensitivity and specificity in identifying BCC. Tentative metabolite identifications were assigned to 189 signals of importance for the recognition of BCC, each indicating a potential tumour marker of diagnostic value. These findings demonstrate the potential for MALDI-MSI coupled with ML to characterize the metabolomic profile of BCC and to diagnose tumour tissue with high sensitivity and specificity. Further studies are needed to explore the potential of implementing integrated MS and automated analyses in the clinical setting.

Borophene: Synthesis, Chemistry, and Electronic Properties.

As a neighbor of carbon in the periodic table, boron exhibits versatile structural and electronic configurations, with its allotropes predicted to possess intriguing structures and properties. Since the experimental realization of two-dimensional (2D) boron sheets (borophene) on Ag(111) substrates in 2015, the experimental study of the realization and characteristics of borophene has drawn increasing interest. In this review, we summarize the synthesis and properties of borophene, which are mainly based on experimental results. First, the synthesis of borophene on different substrates, as well as borophane and bilayer borophene, featuring unique phases and properties, are discussed. Next, the chemistry of borophene, such as oxidation, hydrogenation, and its integration into heterostructures with other materials, is summarized. We also mention a few works focused on the physical properties of borophene, specifically its electronic properties. Lastly, the brief outlook addresses challenges toward practical applications of borophene and possible solutions.

Cutaneous squamous cell carcinoma characterized by MALDI mass spectrometry imaging in combination with machine learning.

Cutaneous squamous cell carcinoma (SCC) is an increasingly prevalent global health concern. Current diagnostic and surgical methods are reliable, but they require considerable resources and do not provide metabolomic insight. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables detailed, spatially resolved metabolomic analysis of tissue samples. Integrated with machine learning, MALDI-MSI could yield detailed information pertaining to the metabolic alterations characteristic for SCC. These insights have the potential to enhance SCC diagnosis and therapy, improving patient outcomes while tackling the growing disease burden. This study employs MALDI-MSI data, labelled according to histology, to train a supervised machine learning model (logistic regression) for the recognition and delineation of SCC. The model, based on data acquired from discrete tumor sections (n = 25) from a mouse model of SCC, achieved a predictive accuracy of 92.3% during cross-validation on the labelled data. A pathologist unacquainted with the dataset and tasked with evaluating the predictive power of the model in the unlabelled regions, agreed with the model prediction for over 99% of the tissue areas. These findings highlight the potential value of integrating MALDI-MSI with machine learning to characterize and delineate SCC, suggesting a promising direction for the advancement of mass spectrometry techniques in the clinical diagnosis of SCC and related keratinocyte carcinomas.

The Forensic Assessment for Immigration Relief (FAIR) clinic: A faculty-led, pediatric clinic model.

Since 2019, the number of children apprehended by the United States Custom and Border Patrol at the southern border continues to increase. Many of these children are fleeing violence and extreme poverty and qualify for several forms of humanitarian relief. Trained pediatric health professionals have an essential role to play in documenting evidence to support their petitions. The goal of a forensic medical and psychological evaluation is to establish the facts related to the reported incident(s), provide forensic evidence to support these claims, and provide an expert opinion on the degree to which a finding correlates with the client's reports through a written affidavit. Research studies have demonstrated a significant increase in asylum grant rate for cases that include an evaluation. As demand for forensic evaluations has grown, multiple clinic models have emerged, including volunteer networks, student-led clinics, and faculty-led clinics. The Forensic Assessment for Immigration Relief (FAIR) Clinic offers a sustainable infrastructure while emphasizing the training of pediatric healthcare professionals on the conduct of trauma-informed, culturally attuned, and developmentally appropriate forensic evaluations. This paper outlines the year-long process of developing and launching a clinic specializing in pediatric forensic medical and psychological evaluations as a blueprint for replication.

Extracellular vesicles as a promising source of lipid biomarkers for breast cancer detection in blood plasma.

Extracellular vesicles (EVs), including exosomes and microvesicles, mediate intercellular communication in cancer, from development to metastasis. EV-based liquid biopsy is a promising strategy for cancer diagnosis as EVs can be found in cancer patients' body fluids. In this study, the lipid composition of breast cancer-derived EVs was studied as well as the potential of blood plasma EVs for the identification of lipid biomarkers for breast cancer detection. Initially, an untargeted lipidomic analysis was carried out for a panel of cancerous and non-cancerous mammary epithelial cells and their secreted EVs. We found that breast cancer-derived EVs are enriched in sphingolipids and glycerophospholipids compared to their parental cells. The initial in vitro study showed that EVs and their parental cells can be correctly classified (100% accuracy) between cancerous and non-cancerous, as well as into their respective breast cancer subtypes, based on their lipid composition. Subsequently, an untargeted lipidomic analysis was carried out for blood plasma EVs from women diagnosed with breast cancer (primary or progressive metastatic breast cancer) as well as healthy women. Correspondingly, when blood plasma EVs were analysed, breast cancer patients and healthy women were correctly classified with an overall accuracy of 93.1%, based on the EVs' lipid composition. Similarly, the analysis of patients with primary breast cancer and healthy women showed an overall accuracy of 95% for their correct classification. Furthermore, primary and metastatic breast cancers were correctly classified with an overall accuracy of 89.5%. This reveals that the blood plasma EVs' lipids may be a promising source of biomarkers for detection of breast cancer. Additionally, this study demonstrates the usefulness of untargeted lipidomics in the study of EV lipid composition and EV-associated biomarker discovery studies. This is a proof-of-concept study and a starting point for further analysis on the identification of EV-based biomarkers for breast cancer.

Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies.

With increased use of mass spectrometry imaging (MSI) in support of pharmaceutical research and development, there are opportunities to develop analytical pipelines that incorporate exploratory high-performance analysis with higher capacity and faster targeted MSI. Therefore, to enable faster MSI data acquisition we present analyte-targeted desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) utilizing a triple-quadrupole (TQ) mass analyzer. The evaluated platform configuration provided superior sensitivity compared to a conventional time-of-flight (TOF) mass analyzer and thus holds the potential to generate data applicable to pharmaceutical research and development. The platform was successfully operated with sampling rates up to 10 scans/s, comparing positively to the 1 scan/s commonly used on comparable DESI-TOF setups. The higher scan rate enabled investigation of the desorption/ionization processes of endogenous lipid species such as phosphatidylcholines and a co-administered cassette of four orally dosed drugs-erlotininb, moxifloxacin, olanzapine, and terfenadine. This was used to enable understanding of the impact of the desorption/ionization processes in order to optimize the operational parameters, resulting in improved compound coverage for olanzapine and the main olanzapine metabolite, hydroxy-olanzapine, in brain tissue sections compared to DESI-TOF analysis or matrix-assisted laser desorption/ionization (MALDI) platforms. The approach allowed reducing the amount of recorded information, thus reducing the size of datasets from up to 150 GB per experiment down to several hundred MB. The improved performance was demonstrated in case studies investigating the suitability of this approach for mapping drug distribution, spatially resolved profiling of drug-induced nephrotoxicity, and molecular-histological tissue classification of ovarian tumors specimens.

Lipidomic Profiling of Colorectal Lesions for Real-Time Tissue Recognition and Risk-Stratification Using Rapid Evaporative Ionization Mass Spectrometry.

OBJECTIVE: Rapid evaporative ionization mass spectrometry (REIMS) is a metabolomic technique analyzing tissue metabolites, which can be applied intraoperatively in real-time. The objective of this study was to profile the lipid composition of colorectal tissues using REIMS, assessing its accuracy for real-time tissue recognition and risk-stratification. SUMMARY BACKGROUND DATA: Metabolic dysregulation is a hallmark feature of carcinogenesis; however, it remains unknown if this can be leveraged for real-time clinical applications in colorectal disease. METHODS: Patients undergoing colorectal resection were included, with carcinoma, adenoma and paired-normal mucosa sampled. Ex vivo analysis with REIMS was conducted using monopolar diathermy, with the aerosol aspirated into a Xevo G2S QToF mass spectrometer. Negatively charged ions over 600 to 1000 m/z were used for univariate and multivariate functions including linear discriminant analysis. RESULTS: A total of 161 patients were included, generating 1013 spectra. Unique lipidomic profiles exist for each tissue type, with REIMS differentiating samples of carcinoma, adenoma, and normal mucosa with 93.1% accuracy and 96.1% negative predictive value for carcinoma. Neoplasia (carcinoma or adenoma) could be predicted with 96.0% accuracy and 91.8% negative predictive value. Adenomas can be risk-stratified by grade of dysplasia with 93.5% accuracy, but not histological subtype. The structure of 61 lipid metabolites was identified, revealing that during colorectal carcinogenesis there is progressive increase in relative abundance of phosphatidylglycerols, sphingomyelins, and mono-unsaturated fatty acid-containing phospholipids. CONCLUSIONS: The colorectal lipidome can be sampled by REIMS and leveraged for accurate real-time tissue recognition, in addition to riskstratification of colorectal adenomas. Unique lipidomic features associated with carcinogenesis are described.

Point-of-Care Diagnosis of Endometrial Cancer Using the Surgical Intelligent Knife (iKnife)-A Prospective Pilot Study of Diagnostic Accuracy.

Introduction: Delays in the diagnosis and treatment of endometrial cancer negatively impact patient survival. The aim of this study was to establish whether rapid evaporative ionisation mass spectrometry using the iKnife can accurately distinguish between normal and malignant endometrial biopsy tissue samples in real time, enabling point-of-care (POC) diagnoses. Methods: Pipelle biopsy samples were obtained from consecutive women needing biopsies for clinical reasons. A Waters G2-XS Xevo Q-Tof mass spectrometer was used in conjunction with a modified handheld diathermy (collectively called the 'iKnife'). Each tissue sample was processed with diathermy, and the resultant surgical aerosol containing ionic lipid species was then analysed, producing spectra. Principal component analyses and linear discriminant analyses were performed to determine variance in spectral signatures. Leave-one-patient-out cross-validation was used to test the diagnostic accuracy. Results: One hundred and fifty patients provided Pipelle biopsy samples (85 normal, 59 malignant, 4 hyperplasia and 2 insufficient), yielding 453 spectra. The iKnife differentiated between normal and malignant endometrial tissues on the basis of differential phospholipid spectra. Cross-validation revealed a diagnostic accuracy of 89% with sensitivity, specificity, positive predictive value and negative predictive value of 85%, 93%, 94% and 85%, respectively. Conclusions: This study is the first to use the iKnife to identify cancer in endometrial Pipelle biopsy samples. These results are highly encouraging and suggest that the iKnife could be used in the clinic to provide a POC diagnosis.

High Resolution Ambient MS Imaging of Biological Samples by Desorption Electro-Flow Focussing Ionization.

In this study, we examine the suitability of desorption electro-flow focusing ionization (DEFFI) for mass spectrometry imaging (MSI) of biological tissue. We also compare the performance of desorption electrospray ionization (DESI) with and without the flow focusing setup. The main potential advantages of applying the flow focusing mechanism in DESI is its rotationally symmetric electrospray jet, higher intensity, more controllable parameters, and better portability due to the robustness of the sprayer. The parameters for DEFFI have therefore been thoroughly optimized, primarily for spatial resolution but also for intensity. Once the parameters have been optimized, DEFFI produces similar images to the existing DESI. MS images for mouse brain samples, acquired at a nominal pixel size of 50 µm, are comparable for both DESI setups, albeit the new sprayer design yields better sensitivity. Furthermore, the two methods are compared with regard to spectral intensity as well as the area of the desorbed crater on rhodamine-coated slides. Overall, the implementation of a flow focusing mechanism in DESI is shown to be highly suitable for imaging biological tissue and has potential to overcome some of the shortcomings experienced with the current geometrical design of DESI.

Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning.

Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.

Enhanced triacylglycerol catabolism by carboxylesterase 1 promotes aggressive colorectal carcinoma.

The ability to adapt to low-nutrient microenvironments is essential for tumor cell survival and progression in solid cancers, such as colorectal carcinoma (CRC). Signaling by the NF-κB transcription factor pathway associates with advanced disease stages and shorter survival in patients with CRC. NF-κB has been shown to drive tumor-promoting inflammation, cancer cell survival, and intestinal epithelial cell (IEC) dedifferentiation in mouse models of CRC. However, whether NF-κB affects the metabolic adaptations that fuel aggressive disease in patients with CRC is unknown. Here, we identified carboxylesterase 1 (CES1) as an essential NF-κB-regulated lipase linking obesity-associated inflammation with fat metabolism and adaptation to energy stress in aggressive CRC. CES1 promoted CRC cell survival via cell-autonomous mechanisms that fuel fatty acid oxidation (FAO) and prevent the toxic build-up of triacylglycerols. We found that elevated CES1 expression correlated with worse outcomes in overweight patients with CRC. Accordingly, NF-κB drove CES1 expression in CRC consensus molecular subtype 4 (CMS4), which is associated with obesity, stemness, and inflammation. CES1 was also upregulated by gene amplifications of its transcriptional regulator HNF4A in CMS2 tumors, reinforcing its clinical relevance as a driver of CRC. This subtype-based distribution and unfavorable prognostic correlation distinguished CES1 from other intracellular triacylglycerol lipases and suggest CES1 could provide a route to treat aggressive CRC.

The Outcomes of Patients With Neck Pain Following ACDF: A Comparison of Patients With Radiculopathy, Myelopathy, or Mixed Symptomatology.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: The goal of the present study was to determine whether neck pain responds differently to anterior cervical discectomy and fusion (ACDF) between patients with cervical radiculopathy and/or cervical myelopathy. SUMMARY OF BACKGROUND DATA: Many patients who undergo ACDF because of radiculopathy/myelopathy also complain of neck pain. However, no studies have compared the response of significant neck pain to ACDF. METHODS: Patients undergoing one to three-level primary ACDF for radiculopathy and/or myelopathy with significant (Visual Analogue Scale [VAS] ≥ 3) neck pain and a minimum of 1-year follow-up were included. Based on preoperative symptoms patients were split into groups for analysis: radiculopathy (R group), myelopathy (M group), or both (MR group). Groups were compared for differences in Health Related Quality of Life outcomes: Physical Component Score-12, Mental Component Score (MCS)-12, Neck Disability Index, VAS neck, and VAS arm pain. RESULTS: Two hundred thirty-five patients met inclusion criteria. There were 117 patients in the R group, 53 in the M group, and 65 in the MR group. Preoperative VAS neck pain was found to be significantly higher in the R group versus M group (6.5 vs. 5.5; P = 0.046). Postoperatively, all cohorts experienced significant (P < 0.001) reduction in VAS neck pain, (ΔVAS neck; R group: -2.9, M: -2.5, MR: -2.5) with no significant differences between groups. However, myelopathic patients showed greater improvement in absolute MCS-12 scores (P = 0.011), RR (P = 0.006), and % minimum clinically important difference (P = 0.013) when compared with radiculopathy patients. This greater improvement remained following regression analysis (P = 0.025). CONCLUSION: Patients with substantial preoperative neck pain experienced significant reduction in their neck pain, disability, and physical function following ACDF, whether treated for radiculopathy or myelopathy. However, in this study, only myelopathy patients had significant improvements in their mental function as represented by MCS improvements. LEVEL OF EVIDENCE: 3.

Health Education Specialist Practice Analysis II 2020: Processes and Outcomes.

Introduction. The Health Education Specialist Practice Analysis II 2020 (HESPA II 2020) described the contemporary practice of health education specialists across work settings at entry and advanced levels. The purpose of the HESPA II 2020 manuscript was to report the research process and resulting data associated with the HESPA II 2020 and to provide recommendations for future practice analyses in health education. Method. Two data collection instruments were developed with the assistance of a 17-member Health Education Practice Panel to survey practicing health education specialists on the knowledge and skills needed in their ongoing roles. The instruments were designed to assess the degree to which the elements of the model had importance to practice (Importance), how often health education specialists performed the elements of the model (Frequency), and the point in time that health education specialists were expected to perform the various elements of the model (Performance Expectation). Composite scores for Sub-Competencies were calculated and subgroup comparisons were conducted to distinguish between levels of practice. Results. A total of 3,851 health education specialists provided usable responses. The final validated hierarchical model included eight Areas of Responsibility, 35 Competencies, and 193 Sub-Competencies. Of the Sub-Competencies, 114 were Entry level, 59 Advanced 1 level, and 20 Advanced 2 level. In addition, 145 knowledge items were verified. Discussion. HESPA II 2020 produced a validated hierarchical model descriptive of current practice of health education specialists across work settings. The results have implications for professional preparation, professional development, and certification.

De Novo Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma.

The incidence of esophageal adenocarcinoma is rising, survival remains poor, and new tools to improve early diagnosis and precise treatment are needed. Cancer phospholipidomes quantified with mass spectrometry imaging (MSI) can support objective diagnosis in minutes using a routine frozen tissue section. However, whether MSI can objectively identify primary esophageal adenocarcinoma is currently unknown and represents a significant challenge, as this microenvironment is complex with phenotypically similar tissue-types. Here, we used desorption electrospray ionization-MSI (DESI-MSI) and bespoke chemometrics to assess the phospholipidomes of esophageal adenocarcinoma and relevant control tissues. Multivariate models derived from phospholipid profiles of 117 patients were highly discriminant for esophageal adenocarcinoma both in discovery (AUC = 0.97) and validation cohorts (AUC = 1). Among many other changes, esophageal adenocarcinoma samples were markedly enriched for polyunsaturated phosphatidylglycerols with longer acyl chains, with stepwise enrichment in premalignant tissues. Expression of fatty acid and glycerophospholipid synthesis genes was significantly upregulated, and characteristics of fatty acid acyls matched glycerophospholipid acyls. Mechanistically, silencing the carbon switch ACLY in esophageal adenocarcinoma cells shortened glycerophospholipid chains, linking de novo lipogenesis to the phospholipidome. Thus, DESI-MSI can objectively identify invasive esophageal adenocarcinoma from a number of premalignant tissues and unveils mechanisms of phospholipidomic reprogramming. SIGNIFICANCE: These results call for accelerated diagnosis studies using DESI-MSI in the upper gastrointestinal endoscopy suite, as well as functional studies to determine how polyunsaturated phosphatidylglycerols contribute to esophageal carcinogenesis.

The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease.

Clearance of surgical margins in cervical cancer prevents the need for adjuvant chemoradiation and allows fertility preservation. In this study, we determined the capacity of the rapid evaporative ionization mass spectrometry (REIMS), also known as intelligent knife (iKnife), to discriminate between healthy, preinvasive, and invasive cervical tissue. Cervical tissue samples were collected from women with healthy, human papilloma virus (HPV) ± cervical intraepithelial neoplasia (CIN), or cervical cancer. A handheld diathermy device generated surgical aerosol, which was transferred into a mass spectrometer for subsequent chemical analysis. Combination of principal component and linear discriminant analysis and least absolute shrinkage and selection operator was employed to study the spectral differences between groups. Significance of discriminatory m/z features was tested using univariate statistics and tandem MS performed to elucidate the structure of the significant peaks allowing separation of the two classes. We analyzed 87 samples (normal = 16, HPV ± CIN = 50, cancer = 21 patients). The iKnife discriminated with 100% accuracy normal (100%) vs. HPV ± CIN (100%) vs. cancer (100%) when compared to histology as the gold standard. When comparing normal vs. cancer samples, the accuracy was 100% with a sensitivity of 100% (95% CI 83.9 to 100) and specificity 100% (79.4 to 100). Univariate analysis revealed significant MS peaks in the cancer-to-normal separation belonging to various classes of complex lipids. The iKnife discriminates healthy from premalignant and invasive cervical lesions with high accuracy and can improve oncological outcomes and fertility preservation of women treated surgically for cervical cancer. Larger in vivo research cohorts are required to validate these findings.

The Impact of Multiple Comorbid Mental Health Disorders on Health-related Quality of Life Following ACDF.

STUDY DESIGN: Retrospective comparative study. OBJECTIVE: The goal was to determine whether comorbid depression and/or anxiety influence outcomes after anterior cervical discectomy and fusion (ACDF) for patients with degenerative cervical pathology. BACKGROUND DATA: The role preoperative mental health has on patient reported outcomes after ACDF surgery is not well understood. METHODS: Patients undergoing elective ACDF for degenerative cervical pathology were identified. Patients were grouped based on their preoperative mental health comorbidities, including patients with no history, depression, anxiety, and those with both depression and anxiety. All preoperative medical treatment for depression and/or anxiety was identified. Outcomes including Physical Component Score (PCS-12), Mental Component Score (MCS-12), Neck Disability Index (NDI), Visual Analogue Scale neck pain score (VAS Neck ), and Visual Analogue Scale arm pain score (VAS Arm) were compared between groups from baseline to postoperative measurements using multiple linear regression analysis-controlling for factors such as age, sex, and body mass index, etc. A P-value <0.05 was considered statistically significant. RESULTS: A total of 264 patients were included in the analysis, with an average age of 53 years and mean follow-up of 19.8 months (19.0-20.6). All patients with a diagnosis of depression or anxiety also reported medical treatment for the disease. The group with no depression or anxiety had significantly less baseline disability than the group with 2 mental health diagnoses, in MCS-12 (P=0.009), NDI (P<0.004), VAS Neck (P=0.003), and VAS Arm (P=0.001) scores. Linear regression analysis demonstrated that increasing occurrence of mental health disorders was not a significant predictor of change over time for any of the outcome measures included in the analysis. CONCLUSIONS: Despite more severe preoperative symptoms, patients with a preoperative mental health disorder(s) demonstrated significant improvement in postoperative outcomes after ACDF. No differences were identified in postoperative outcomes between each of the groups. LEVEL OF EVIDENCE: Level III.

Proton Pump Inhibitor Use Affects Pseudarthrosis Rates and Influences Patient-Reported Outcomes.

STUDY DESIGN: Retrospective cohort review. OBJECTIVES: Cervical pseudarthrosis is a frequent cause of need for revision anterior cervical discectomy and fusion (ACDF) and may lead to worse patient-reported outcomes. The effect of proton pump inhibitors on cervical fusion rates are unknown. The purpose of this study was to determine if patients taking PPIs have higher rates of nonunion after ACDF. METHODS: A retrospective cohort review was performed to compare patients who were taking PPIs preoperatively with those not taking PPIs prior to ACDF. Patients younger than 18 years of age, those with less than 1-year follow-up, and those undergoing surgery for trauma, tumor, infection, or revision were excluded. The rates of clinically diagnosed pseudarthrosis and radiographic pseudarthrosis were compared between PPI groups. Patient outcomes, pseudarthrosis rates, and revision rates were compared between PPI groups using either multiple linear or logistic regression analysis, controlling for demographic and operative variables. RESULTS: Out of 264 patients, 58 patients were in the PPI group and 206 were in the non-PPI group. A total of 23 (8.71%) patients were clinically diagnosed with pseudarthrosis with a significant difference between PPI and non-PPI groups (P = .009). Using multiple linear regression, PPI use was not found to significantly affect any patient-reported outcome measure. However, based on logistic regression, PPI use was found to increase the odds of clinically diagnosed pseudarthrosis (odds ratio 3.552, P = .014). Additionally, clinically diagnosed pseudarthrosis negatively influenced improvement in PCS-12 scores (P = .022). CONCLUSIONS: PPI use was found to be a significant predictor of clinically diagnosed pseudarthrosis following ACDF surgery. Furthermore, clinically diagnosed pseudarthrosis negatively influenced improvement in PCS-12 scores.

Does an Uninstrumented Level Increase the Rate of Revision Surgery in a Multilevel Posterior Cervical Decompression and Fusion?

STUDY DESIGN: This was a retrospective cohort study. OBJECTIVE: The goal of this study is to determine if skipping a single level affects the revision rate for patients undergoing multilevel posterior cervical decompression and fusion (PCDF). SUMMARY OF BACKGROUND DATA: A multilevel PCDF is a common procedure for patients with cervical spondylotic myelopathy. With advanced pathology, it can be difficult to safely place screw instrumentation at every level increasing the risk of intraoperative and perioperative morbidity. It is unclear whether skipping a level during PCDF affects fusion and revision rates. PATIENTS AND METHODS: A cervical spine surgeries database at a single institution was used to identify patients who underwent ≥3 levels of PCDF. Inclusion criteria consisted of patients who had screws placed at every level or if they had a single level without screws bilaterally. Patients were excluded if the surgery was performed for tumor, trauma, or infection, and age below 18 years, or if there was <1 year of follow-up. RESULTS: A total of 157 patients met inclusion criteria, with 86 undergoing a PCDF with instrumentation at all levels and 71 that had a single uninstrumented level. Overall mean follow-up was 46.5±22.8 months. In patients with or without a skipped level, the revision rate was 25% and 26%, respectively (P<1.00). Univariate regression analysis demonstrated that proximal fixation level in the upper cervical region, having the fusion end at C7, prior surgery, and myelopathy were significant predictors of revision. Skipping a single level, however, was not predictive of revision. CONCLUSIONS: When performing a multilevel PCDF, there is no increase in the rate of revision surgery if a single level is uninstrumented. Conversely, other surgical factors, including the cranial and caudal levels, affect revision rates. In contrast to other reports, the C2 sagittal vertical axis did not affect reoperation rates. LEVEL OF EVIDENCE: Level IV.

Effects of Operating Room Size on Surgical Site Infection Following Lumbar Fusion Surgery.

BACKGROUND: Surgical site infections (SSIs) represent a devastating complication after spine surgery. Many factors have been identified, but the influence of operating room (OR) size on infection rate has not been assessed. METHODS: Two thousand five hundred and twenty-three patients who underwent open lumbar spine fusion at a single institution between 2010 and 2016 were included. Patients were dichotomized into large versus small groups based on OR volume. Bivariate logistic regression and a final multivariate model following a multicollinearity check were used to calculate odds of infection for all variables. RESULTS: A total of 63 patients (2.5%) developed SSIs with 46 (73%) in the larger OR group and 17 (27%) in the smaller OR group. The rate of SSIs in larger ORs was 3.02% compared with 1.81% in smaller ORs. Significant parameters impacting SSI in bivariate analysis included an earlier year of surgery, BMI > 30, more comorbidities, more levels decompressed and fused, smoking, and larger OR volumes. Multivariate analysis identified BMI > 30, Elixhauser scores, smoking, and increasing levels decompressed as significant predictors. Topical vancomycin was found to significantly decrease rate of infection in both analyses. CONCLUSIONS: OR size (large versus small) was ultimately not a significant predictor of infection related to rates of SSIs, although it did show a clinical trend toward significance, suggesting association. Future prospective analysis is warranted. LEVEL OF EVIDENCE: 3.