Association between structural rib autograft and the rate of arthrodesis in children undergoing occiput-C2 instrumentation and fusion.

OBJECTIVE: The purpose of this study was to identify factors associated with fusion success among pediatric patients undergoing occiput-C2 rigid instrumentation and fusion. METHODS: The Pediatric Spine Study Group registry was queried to identify patients ≤ 21 years of age who underwent occiput-C2 posterior spinal rigid instrumentation and fusion and had a 2-year minimum clinical and radiographic (postoperative lateral cervical radiograph or CT scan) follow-up. Fusion failure was defined clinically if a patient underwent hardware revision surgery > 30 days after the index procedure or radiographically by the presence of hardware failure or screw haloing on the most recent follow-up imaging study. Univariate comparisons and multivariable logistic regression analyses were subsequently performed. RESULTS: Seventy-six patients met inclusion criteria. The median age at surgery was 9 years (range 1.5-17.2 years), and 51% of the cohort was male. Overall, 75% of patients had syndromic (n = 41) or congenital (n = 15) etiologies, with the most frequent diagnoses of Down syndrome (28%), Chiari malformation (13%), and Klippel-Feil syndrome (12%). Data were available to determine if there was a fusion failure in 97% (74/76) of patients. Overall, 38% (28/74) of patients had fusion failure (95% CI 27%-50%). Univariate analysis demonstrated that use of a rigid cervical collar postoperatively (p = 0.04) and structural rib autograft (p = 0.02) were associated with successful fusion. Multivariable logistic regression analysis determined that patients who had rib autograft used in surgery had a 73% decrease in the odds of fusion failure (OR 0.27, 95% CI 0.09-0.82; p = 0.02). Age, etiology including Down syndrome, instrumentation type, unilateral instrumentation, use of recombinant human bone morphogenetic protein, and other variables did not influence the risk for fusion failure. CONCLUSIONS: In this multicenter, multidisciplinary, international registry of children undergoing occiput-C2 instrumentation and fusion, fusion failure was seen in 38% of patients, a higher rate than previously reported in the literature. The authors' data suggest that postoperative immobilization in a rigid cervical collar may be beneficial, and the use of structural rib autograft should be considered, as rib autograft was associated with a 75% higher chance of successful fusion.

A Century of Evolution in Spine Surgery Publications: A Bibliometric Analysis of the Field From 1900 to 2023.

BACKGROUND AND OBJECTIVES: Spine surgery has advanced in concert with our deeper understanding of its elements. Narrowly focused bibliometric analyses have been conducted previously, but never on the entire corpus of the field. Using big data and bibliometrics, we appraised the entire corpus of spine surgery publications to study the evolution of the specialty as a scholarly field since 1900. METHODS: We queried Web of Science for all contents from 13 major publications dedicated to spine surgery. We next queried by topic [topic = (spine OR spinal OR vertebrae OR vertebral OR intervertebral OR disc OR disk)]; these results were filtered to include articles published by 49 other publications that were manually determined to contain pertinent articles. Articles, along with their metadata, were exported. Statistical and bibliometric analyses were performed using the Bibliometrix R package and various Python packages. RESULTS: Eighty-five thousand five hundred articles from 62 journals and 134 707 unique authors were identified. The annual growth rate of publications was 2.78%, with a surge after 1980, concurrent with the growth of specialized journals. International coauthorship, absent before 1970, increased exponentially with the formation of influential spine study groups. Reference publication year spectroscopy allowed us to identify 200 articles that comprise the historical roots of modern spine surgery and each of its subdisciplines. We mapped the emergence of new topics and saw a recent lexical evolution toward outcomes- and patient-centric terms. Female and minority coauthorship has increased since 1990, but remains low, and disparities across major publications persist. CONCLUSION: The field of spine surgery was borne from pioneering individuals who published their findings in a variety of journals. The renaissance of spine surgery has been powered by international collaboration and is increasingly outcomes focused. While spine surgery is gradually becoming more diverse, there is a clear need for further promotion and outreach to under-represented populations.

Developing an Automated Registry (Autoregistry) of Spine Surgery Using Natural Language Processing and Health System Scale Databases.

BACKGROUND AND OBJECTIVES: Clinical registries are critical for modern surgery and underpin outcomes research, device monitoring, and trial development. However, existing approaches to registry construction are labor-intensive, costly, and prone to manual error. Natural language processing techniques combined with electronic health record (EHR) data sets can theoretically automate the construction and maintenance of registries. Our aim was to automate the generation of a spine surgery registry at an academic medical center using regular expression (regex) classifiers developed by neurosurgeons to combine domain expertise with interpretable algorithms. METHODS: We used a Hadoop data lake consisting of all the information generated by an academic medical center. Using this database and structured query language queries, we retrieved every operative note written in the department of neurosurgery since our transition to EHR. Notes were parsed using regex classifiers and compared with a random subset of 100 manually reviewed notes. RESULTS: A total of 31 502 operative cases were downloaded and processed using regex classifiers. The codebase required 5 days of development, 3 weeks of validation, and less than 1 hour for the software to generate the autoregistry. Regex classifiers had an average accuracy of 98.86% at identifying both spinal procedures and the relevant vertebral levels, and it correctly identified the entire list of defined surgical procedures in 89% of patients. We were able to identify patients who required additional operations within 30 days to monitor outcomes and quality metrics. CONCLUSION: This study demonstrates the feasibility of automatically generating a spine registry using the EHR and an interpretable, customizable natural language processing algorithm which may reduce pitfalls associated with manual registry development and facilitate rapid clinical research.

Health system-scale language models are all-purpose prediction engines.

Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by forecasting clinical and operational events. Existing structured data-based clinical predictive models have limited use in everyday practice owing to complexity in data processing, as well as model development and deployment1-3. Here we show that unstructured clinical notes from the electronic health record can enable the training of clinical language models, which can be used as all-purpose clinical predictive engines with low-resistance development and deployment. Our approach leverages recent advances in natural language processing4,5 to train a large language model for medical language (NYUTron) and subsequently fine-tune it across a wide range of clinical and operational predictive tasks. We evaluated our approach within our health system for five such tasks: 30-day all-cause readmission prediction, in-hospital mortality prediction, comorbidity index prediction, length of stay prediction, and insurance denial prediction. We show that NYUTron has an area under the curve (AUC) of 78.7-94.9%, with an improvement of 5.36-14.7% in the AUC compared with traditional models. We additionally demonstrate the benefits of pretraining with clinical text, the potential for increasing generalizability to different sites through fine-tuning and the full deployment of our system in a prospective, single-arm trial. These results show the potential for using clinical language models in medicine to read alongside physicians and provide guidance at the point of care.

Racial and ethnic disparities in a real-world precision oncology data registry.

Biorepositories enable precision oncology research by sharing clinically annotated genomic data, but it remains unknown whether these data registries reflect the true distribution of cancers in racial and ethnic minorities. Our analysis of Project Genomics Evidence Neoplasia Information Exchange (GENIE), a real-world cancer data registry designed to accelerate precision oncology discovery, indicates that minorities do not have sufficient representation, which may impact the validity of studies directly comparing mutational profiles between racial/ethnic groups and limit generalizability of biomarker discoveries to all populations.

Methods and Impact for Using Federated Learning to Collaborate on Clinical Research.

BACKGROUND: The development of accurate machine learning algorithms requires sufficient quantities of diverse data. This poses a challenge in health care because of the sensitive and siloed nature of biomedical information. Decentralized algorithms through federated learning (FL) avoid data aggregation by instead distributing algorithms to the data before centrally updating one global model. OBJECTIVE: To establish a multicenter collaboration and assess the feasibility of using FL to train machine learning models for intracranial hemorrhage (ICH) detection without sharing data between sites. METHODS: Five neurosurgery departments across the United States collaborated to establish a federated network and train a convolutional neural network to detect ICH on computed tomography scans. The global FL model was benchmarked against a standard, centrally trained model using a held-out data set and was compared against locally trained models using site data. RESULTS: A federated network of practicing neurosurgeon scientists was successfully initiated to train a model for predicting ICH. The FL model achieved an area under the ROC curve of 0.9487 (95% CI 0.9471-0.9503) when predicting all subtypes of ICH compared with a benchmark (non-FL) area under the ROC curve of 0.9753 (95% CI 0.9742-0.9764), although performance varied by subtype. The FL model consistently achieved top three performance when validated on any site's data, suggesting improved generalizability. A qualitative survey described the experience of participants in the federated network. CONCLUSION: This study demonstrates the feasibility of implementing a federated network for multi-institutional collaboration among clinicians and using FL to conduct machine learning research, thereby opening a new paradigm for neurosurgical collaboration.

A patient-driven clinicogenomic partnership for metastatic prostate cancer.

Molecular profiling studies have enabled discoveries for metastatic prostate cancer (MPC) but have predominantly occurred in academic medical institutions and involved non-representative patient populations. We established the Metastatic Prostate Cancer Project (MPCproject, mpcproject.org), a patient-partnered initiative to involve patients with MPC living anywhere in the US and Canada in molecular research. Here, we present results from our partnership with the first 706 MPCproject participants. While 41% of patient partners live in rural, physician-shortage, or medically underserved areas, the MPCproject has not yet achieved racial diversity, a disparity that demands new initiatives detailed herein. Among molecular data from 333 patient partners (572 samples), exome sequencing of 63 tumor and 19 cell-free DNA (cfDNA) samples recapitulated known findings in MPC, while inexpensive ultra-low-coverage sequencing of 318 cfDNA samples revealed clinically relevant AR amplifications. This study illustrates the power of a growing, longitudinal partnership with patients to generate a more representative understanding of MPC.

CREB5 reprograms FOXA1 nuclear interactions to promote resistance to androgen receptor-targeting therapies.

Metastatic castration-resistant prostate cancers (mCRPCs) are treated with therapies that antagonize the androgen receptor (AR). Nearly all patients develop resistance to AR-targeted therapies (ARTs). Our previous work identified CREB5 as an upregulated target gene in human mCRPC that promoted resistance to all clinically approved ART. The mechanisms by which CREB5 promotes progression of mCRPC or other cancers remains elusive. Integrating ChIP-seq and rapid immunoprecipitation and mass spectroscopy of endogenous proteins, we report that cells overexpressing CREB5 demonstrate extensive reprogramming of nuclear protein-protein interactions in response to the ART agent enzalutamide. Specifically, CREB5 physically interacts with AR, the pioneering actor FOXA1, and other known co-factors of AR and FOXA1 at transcription regulatory elements recently found to be active in mCRPC patients. We identified a subset of CREB5/FOXA1 co-interacting nuclear factors that have critical functions for AR transcription (GRHL2, HOXB13) while others (TBX3, NFIC) regulated cell viability and ART resistance and were amplified or overexpressed in mCRPC. Upon examining the nuclear protein interactions and the impact of CREB5 expression on the mCRPC patient transcriptome, we found that CREB5 was associated with Wnt signaling and epithelial to mesenchymal transitions, implicating these pathways in CREB5/FOXA1-mediated ART resistance. Overall, these observations define the molecular interactions among CREB5, FOXA1, and pathways that promote ART resistance.

Molecular features of exceptional response to neoadjuvant anti-androgen therapy in high-risk localized prostate cancer.

High-risk localized prostate cancer (HRLPC) is associated with a substantial risk of recurrence and disease mortality. Recent clinical trials have shown that intensifying anti-androgen therapies administered before prostatectomy can induce pathologic complete responses or minimal residual disease, called exceptional response, although the molecular determinants of these clinical outcomes are largely unknown. Here, we perform whole-exome and transcriptome sequencing on pre-treatment multi-regional tumor biopsies from exceptional responders (ERs) and non-responders (NRs, pathologic T3 or lymph node-positive disease) to intensive neoadjuvant anti-androgen therapies. Clonal SPOP mutation and SPOPL copy-number loss are exclusively observed in ERs, while clonal TP53 mutation and PTEN copy-number loss are exclusively observed in NRs. Transcriptional programs involving androgen signaling and TGF-ß signaling are enriched in ERs and NRs, respectively. These findings may guide prospective validation studies of these molecular features in large HRLPC clinical cohorts treated with neoadjuvant anti-androgens to improve patient stratification.

Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology.

Tumor molecular profiling of single gene-variant ('first-order') genomic alterations informs potential therapeutic approaches. Interactions between such first-order events and global molecular features (for example, mutational signatures) are increasingly associated with clinical outcomes, but these 'second-order' alterations are not yet accounted for in clinical interpretation algorithms and knowledge bases. We introduce the Molecular Oncology Almanac (MOAlmanac), a paired clinical interpretation algorithm and knowledge base to enable integrative interpretation of multimodal genomic data for point-of-care decision making and translational-hypothesis generation. We benchmarked MOAlmanac to a first-order interpretation method across multiple retrospective cohorts and observed an increased number of clinical hypotheses from evaluation of molecular features and profile-to-cell line matchmaking. When applied to a prospective precision oncology trial cohort, MOAlmanac nominated a median of two therapies per patient and identified therapeutic strategies administered in 47% of patients. Overall, we present an open-source computational method for integrative clinical interpretation of individualized molecular profiles.

Mistrust and inconsistency during COVID-19: considerations for resource allocation guidelines that prioritise healthcare workers.

As the USA contends with another surge in COVID-19 cases, hospitals may soon need to answer the unresolved question of who lives and dies when ventilator demand exceeds supply. Although most triage policies in the USA have seemingly converged on the use of clinical need and benefit as primary criteria for prioritisation, significant differences exist between institutions in how to assign priority to patients with identical medical prognoses: the so-called 'tie-breaker' situations. In particular, one's status as a frontline healthcare worker (HCW) has been a proposed criterion for prioritisation in the event of a tie. This article outlines two major grounds for reconsidering HCW prioritisation. The first recognises trust as an indispensable element of clinical care and mistrust as a hindrance to any public health strategy against the virus, thus raising concerns about the outward appearance of favouritism. The second considers the ways in which proponents of HCW prioritisation deviate from the very 'ethics frameworks' that often preface triage policies and serve to guide resource allocation-a rhetorical strategy that may undermine the very ethical foundations on which triage policies stand. By appealing to trust and consistency, we re-examine existing arguments in favour of HCW prioritisation and provide a more tenable justification for adjudicating on tie-breaker events during crisis standards of care.

Embryonic skin development and repair.

Fetal cutaneous wounds have the unique ability to completely regenerate wounded skin and heal without scarring. However, adult cutaneous wounds heal via a fibroproliferative response which results in the formation of a scar. Understanding the mechanism(s) of scarless wound healing leads to enormous clinical potential in facilitating an environment conducive to scarless healing in adult cutaneous wounds. This article reviews the embryonic development of the skin and outlines the structural and functional differences in adult and fetal wound healing phenotypes. A review of current developments made towards applying this clinical knowledge to promote scarless healing in adult wounds is addressed.

An Improved Humanized Mouse Model for Excisional Wound Healing Using Double Transgenic Mice.

Objective: Splinting full-thickness cutaneous wounds in mice has allowed for a humanized model of wound healing. Delineating the epithelial edge and assessing time to closure of these healing wounds via macroscopic visualization have remained a challenge. Approach: Double transgenic mice were created by crossbreeding K14-Cre and ROSAmT/mG reporter mice. Full-thickness excisional wounds were created in K14-Cre/ROSAmT/mG mice (n = 5) and imaged using both normal and fluorescent light on the day of surgery, and every other postoperative day (POD) until wound healing was complete. Ten blinded observers analyzed a series of images from a single representative healing wound, taken using normal or fluorescent light, to decide the POD when healing was complete. K14-Cre/ROSAmT/mG mice (n = 4) were subsequently sacrificed at the four potential days of rated wound closure to accurately determine the histological point of wound closure using microscopic fluorescence imaging. Results: Average time to wound closure was rated significantly longer in the wound series images taken using normal light, compared with fluorescent light (mean POD 13.6 vs. 11.6, *p = 0.008). Fluorescence imaging of histological samples indicated that reepithelialization was complete at 12 days postwounding. Innovation: We describe a novel technique, using double transgenic mice K14-Cre/ROSAmT/mG and fluorescence imaging, to more accurately determine the healing time of wounds in mice upon macroscopic evaluation. Conclusion: The accuracy by which wound healing can be macroscopically determined in vivo in mouse models of wound healing is significantly enhanced using K14-Cre/ROSAmT/mG double transgenic mice and fluorescence imaging.

How Stigma Distorts Justice: the Exile and Isolation of Leprosy Patients in Hawai`i.

Leprosy has taken on many names throughout human history. But none of its nomenclature has adequately captured the essence of what it has historically meant to live with the disease like the Hawaiian term ma`i ho`oka`awale, or "the separating sickness." The appropriateness of this term is twofold: on the one hand, it accurately reflects the physical isolation imposed on leprosy patients as a result of stigmatization and quarantine policies; on the other, it seems fitting to use the language of the culture and race that leprosy so disproportionately affected in nineteenth and twentieth century Hawai`i. This essay offers an ethical analysis of the treatment of leprosy patients in Hawai`i to identify mistakes made in the sphere of public health to better guide the management of infectious diseases today. It provides an historical overview of leprosy in order to contextualize its journey to the Hawaiian Islands, with a particular focus on the horrific century-long isolation of leprosy patients to the remote Kalaupapa settlement. It then presents two contrasting normative claims about the banishment and isolation practices by using two different theories of justice: utilitarianism and Rawls' justice as fairness. In doing so, this essay illustrates the ways in which stigmatization and racism could likely affect the abhorrent treatment of leprosy patients by disproportionately appealing to the "greater good." However, I contend that this dichotomization of justice brings us to a moral impasse in the context of public health. Rather, considering infectious diseases with a "patient as victim and vector" (PVV) approach may prove more beneficial, especially in tandem with a schema of justice that promotes self-respect as a primary good to combat the deleterious effects of stigma. This historical reflection may thus allow medical professionals and policy makers alike to draw upon valuable ethical lessons for contemporary initiatives in public health.

Sanativo Wound Healing Product Does Not Accelerate Reepithelialization in a Mouse Cutaneous Wound Healing Model.

BACKGROUND: Sanativo is an over-the-counter Brazilian product derived from Amazon rainforest plant extract that is purported to improve the healing of skin wounds. Two experimental studies have shown accelerated closure of nonsplinted excisional wounds in rat models. However, these models allow for significant contraction of the wound and do not approximate healing in the tight skin of humans. METHODS: Full-thickness excisional wounds were created on the dorsal skin of mice and were splinted with silicone rings, a model that forces the wound to heal by granulation and reepithelialization. Sanativo or a control solution was applied either daily or every other day to the wounds. Photographs were taken every other day, and the degree of reepithelialization of the wounds was determined. RESULTS: With both daily and every-other-day applications, Sanativo delayed reepithelialization of the wounds. Average time to complete healing was faster with control solution versus Sanativo in the daily application group (9.4 versus 15.2 days; p < 0.0001) and the every-other-day application group (11 versus 13 days; p = 0.017). The size of visible scar at the last time point of the study was not significantly different between the groups, and no differences were found on histologic examination. CONCLUSIONS: Sanativo wound healing compound delayed wound reepithelialization in a mouse splinted excisional wound model that approximates human wound healing. The size of visible scar after complete healing was not improved with the application of Sanativo. These results should cast doubt on claims that this product can improve wound healing in humans.

Creation of Abdominal Adhesions in Mice.

Abdominal adhesions consist of fibrotic tissue that forms in the peritoneal space in response to an inflammatory insult, typically surgery or intraabdominal infection. The precise mechanisms underlying adhesion formation are poorly understood. Many compounds and physical barriers have been tested for their ability to prevent adhesions after surgery with varying levels of success. The mouse and rat are important models for the study of abdominal adhesions. Several different techniques for the creation of adhesions in the mouse and rat exist in the literature. Here we describe a protocol utilizing abrasion of the cecum with sandpaper and sutures placed in the right abdominal sidewall. The mouse is anesthetized and the abdomen is prepped. A midline laparotomy is created and the cecum is identified. Sandpaper is used to gently abrade the surface of the cecum. Next, several figure-of-eight sutures are placed into the peritoneum of the right abdominal sidewall. The abdominal cavity is irrigated, a small amount of starch is applied, and the incision is closed. We have found that this technique produces the most consistent adhesions with the lowest mortality rate.