PTEN Deletion in the Adult Dentate Gyrus Induces Epilepsy.

Embryonic and early postnatal promotor-driven deletion of the phosphatase and tensin homolog (PTEN) gene results in neuronal hypertrophy, hyperexcitable circuitry and development of spontaneous seizures in adulthood. We previously documented that focal, vector-mediated PTEN deletion in mature granule cells of adult dentate gyrus triggers dramatic growth of cell bodies, dendrites, and axons, similar to that seen with early postnatal PTEN deletion. Here, we assess the functional consequences of focal, adult PTEN deletion, focusing on its pro-epileptogenic potential. PTEN deletion was accomplished by injecting AAV-Cre either bilaterally or unilaterally into the dentate gyrus of double transgenic PTEN-floxed, ROSA-reporter mice. Hippocampal recording electrodes were implanted for continuous digital EEG with concurrent video recordings in the home cage. Electrographic seizures and epileptiform spikes were assessed manually by two investigators, and corelated with concurrent videos. Spontaneous electrographic and behavioral seizures appeared after focal PTEN deletion in adult dentate granule cells, commencing around 2 months post-AAV-Cre injection. Seizures occurred in the majority of mice with unilateral or bilateral PTEN deletion and led to death in several cases. PTEN-deletion provoked epilepsy was not associated with apparent hippocampal neuron death; supra-granular mossy fiber sprouting was observed in a few mice. In summary, focal, unilateral deletion of PTEN in the adult dentate gyrus suffices to provoke time-dependent emergence of a hyperexcitable circuit generating hippocampus-origin, generalizing spontaneous seizures, providing a novel model for studies of adult-onset epileptogenesis.

Hypoperfusion Intensity Ratio as an Indirect Imaging Surrogate in Patients With Anterior Circulation Large-Vessel Occlusion and Association of Baseline Characteristics With Poor Collateral Status.

BACKGROUND: Collateral status (CS) plays a crucial role in infarct growth rate, risk of postthrombectomy hemorrhage, and overall clinical outcomes in patients with acute ischemic stroke (AIS) secondary to anterior circulation large-vessel occlusions (LVOs). Hypoperfusion intensity ratio has been previously validated as an indirect noninvasive pretreatment imaging biomarker of CS. In addition to imaging, derangements in admission laboratory findings can also influence outcomes in patients with AIS-LVO. Therefore, our study aims to assess the relationship between admission laboratory findings, baseline characteristics, and CS, as assessed by hypoperfusion intensity ratio in patients with AIS-LVO. METHODS AND RESULTS: In this retrospective study, consecutive patients presenting with AIS secondary to anterior circulation LVO who underwent pretreatment computed tomography perfusion were included. The computed tomography perfusion data processed by RAPID (Ischema View, Menlo Park, CA) generated the hypoperfusion intensity ratio. Binary logistic regression models were used to assess the relationship between patients' baseline characteristics, admission laboratory findings, and poor CS. A total of 221 consecutive patients with AIS-LVO between January 2017 and September 2022 were included in our study (mean±SD age, 67.0±15.8 years; 119 men [53.8%]). Multivariable logistic regression showed that patients with AIS caused by cardioembolic and cryptogenic causes (adjusted odds ratio [OR], 2.67; 95% CI, 1.20-5.97; P=0.016), those who presented with admission National Institutes of Health Stroke Scale score ≥12 (adjusted OR, 3.12; 95% CI, 1.61-6.04; P=0.001), and male patients (adjusted OR, 2.06; 95% CI, 1.13-3.77; P=0.018) were associated with poor CS. CONCLUSIONS: Stroke caused by cardioembolic or cryptogenic causes, admission National Institutes of Health Stroke Scale score of ≥12, and male sex were associated with poor CS, as defined by hypoperfusion intensity ratio in the patients with AIS-LVO.

Early Complications of Planned Resection Versus Unplanned Excision of Sarcomas in the Distal Upper Extremity.

Purpose: Unplanned excisions are defined as excisions of malignant tumors performed without preoperative cross-sectional imaging or diagnostic biopsy, frequently resulting in residual disease and re-excision secondary to positive surgical margins. The purpose of this study was to compare the relative morbidity of planned versus unplanned upper-extremity sarcoma excisions. Methods: A single tertiary referral hospital pathology database was queried from January 2015 through 2022 for primary upper-extremity sarcomas (forearm, wrist, hand, and finger). Demographics, tumor features, survival characteristics, and outcomes were retrospectively reviewed. Results: Forty-two upper-extremity sarcoma patients were identified, two-thirds of whom had unplanned excisions. Those with unplanned excisions were more likely to be female (relative risk [RR]: 1.9; P = .002), undergo initial excision at a nonsarcoma center (RR: 14.0; P < .001), have masses distal to the forearm (RR: 1.6; P = .02), and have smaller masses (4.8 vs 7.4 cm, P = .03). 71.4% of tumors were high grade, and 60.7% less than 5 cm in size.Unplanned excisions had positive margins in 96.4% of cases and were more likely to undergo re-excision (odds ratio [OR]: 20.0; P = .001), more total resections (2.7 vs 1.4, P = .009), sacrifice of neurovascular structures (OR: 6.1; P = .04), adjuvant radiation therapy (OR: 4.5; P = .05), adjuvant systemic therapy (OR: 10.9; P = .03), or experience a complication (OR: 17.6; P = .002) at an average of 38.0 months of follow-up.Nearly half of all unplanned excision patients developed a local recurrence or metastatic disease. Six patients required an amputation versus one in the planned cohort (P = .17), and 26.5% of patients died at an average of 32.5 months from presentation. Conclusions: Distal upper-extremity sarcoma excisions are frequently unplanned, with high rates of morbidity compared with planned excisions. Surgeons should have a low threshold for cross-sectional imaging and core needle biopsy of atypical lesions, irrespective of size, with referral to a sarcoma center. Type of study/level of evidence: Prognostic IV.

Artificial intelligence-assisted grading for tear trough deformity.

BACKGROUND: Various classification systems for tear trough deformity (TTD) have been published; however, their complexity can pose challenges in clinical use, especially for less experienced surgeons. It is believed that artificial intelligence (AI) technology can address some of these challenges by reducing inadvertent errors and improving the accuracy of medical practice. In this study, we aimed to establish a reliable and precise digital image grading model for TTD using smartphone-based photography enhanced using AI deep learning technology. This model is designed to aid and guide surgeons, particularly those who are less experienced or from younger generations, during clinical examinations and in making decisions regarding further surgical interventions. MATERIALS AND METHODS: A total of 504 patients and 983 photos were included in the study. We adopted the Barton's grading system for TTD. All photos were taken using the same smartphone and processed and analyzed using the medical AI assistant (MAIA™) software. The photos were then randomly divided into two groups to establish training and testing models. RESULTS: The confusion matrix for the training model demonstrated a sensitivity of 56%, specificity of 87.3%, F1 score of 0.57, and an area under the curve (AUROC) of 0.85. For the testing group, the sensitivity was 49.3%, specificity was 85%, F1 score was 0.49, and AUROC was 0.83. Representative heatmaps were also generated. CONCLUSION: Our study is the first to demonstrate that tear trough deformities can be easily categorized using a built-in smartphone camera in conjunction with an AI deep learning program. This approach can reduce errors during clinical patient evaluations, particularly for less experienced practitioners.

Healthcare Utilization and Chronic Disease Management for Non-Medicaid-Eligible Patients in a City-Wide Safety-Net Healthcare Access Program.

BACKGROUND: In 2019, New York City (NYC) launched NYC Care (NYCC), a healthcare access program through NYC Health + Hospitals (H + H) for individuals who are ineligible for federally funded health insurance programs or cannot purchase insurance through the State Marketplace, predominantly undocumented individuals. OBJECTIVE: To examine the sociodemographic characteristics, healthcare use patterns, and chronic disease quality measures for diabetes mellitus (DM) and hypertension among NYCC patients compared with Medicaid patients seen at NYC H + H. DESIGN: Observational study. PARTICIPANTS: Adults aged 18 years and older enrolled in NYCC (N = 83,003) or Medicaid (N = 512,012) as of January 1, 2022. Patients were included if they had at least one visit between January 1, 2021, and December 31, 2021. MAIN MEASURES: Sociodemographic characteristics, healthcare use patterns, and quality measures for DM and hypertension. KEY RESULTS: NYCC patients (n = 83,003) were, on average, older, more likely to be Hispanic with Spanish as their preferred language, had more comorbidities, and had more primary care (adjusted incidence rate ratio 2.75 [95% confidence interval 2.71, 2.80]) and specialty care (2.22 [2.17, 2.26]) visits compared to Medicaid patients (n = 512,012). Rates of emergency department visits were similar between the two groups (1.02 [1.00, 1.04]), but NYCC patients had relatively fewer hospitalizations (0.64 [0.62, 0.67]). NYCC patients with DM or hypertension had higher rates of having a documented hemoglobin A1c or blood pressure in 2022, respectively, and clinically similar rates of chronic disease control (mean difference in hemoglobin A1c - 0.05 [- 0.09, - 0.01] in patients with DM and mean difference in blood pressure - 0.38 [- 0.67, - 0.10]/ - 0.64 [- 0.82, - 0.46]) compared with Medicaid patients. CONCLUSIONS: NYCC effectively enrolled a large number of uninsured participants and provided them with healthcare access similar to that of Medicaid patients. Future studies should evaluate the impact of NYCC enrollment on healthcare utilization and disease outcomes.

Stem cell therapeutics and gene therapy for neurologic disorders.

Rapid advances in biological knowledge and technological innovation have greatly advanced the fields of stem cell and gene therapies to combat a broad spectrum of neurologic disorders. Researchers are currently exploring a variety of stem cell types (e.g., embryonic, progenitor, induced pluripotent) and various transplantation strategies, each with its own advantages and drawbacks. Similarly, various gene modification techniques (zinc finger, TALENs, CRISPR-Cas9) are employed with various delivery vectors to modify underlying genetic contributors to neurologic disorders. While these two individual fields continue to blaze new trails, it is the combination of these technologies which enables genetically engineered stem cells and vastly increases investigational and therapeutic opportunities. The capability to culture and expand stem cells outside the body, along with their potential to correct genetic abnormalities in patient-derived cells or enhance cells with extra gene products, unleashes the full biological potential for innovative, multifaceted approaches to treat complex neurological disorders. In this review, we provide an overview of stem cell and gene therapies in the context of neurologic disorders, highlighting recent advances and current shortcomings, and discuss prospects for future therapies in clinical settings.

Call for Specialty-Specific Benchmarks for Cross-Specialty Quality Measures in the Quality Payment Program.

The introduction of the Quality Payment Program (QPP) by the Centers for Medicare & Medicaid Services (CMS) played a critical role in the process of transitioning U.S. healthcare from a pay-for-service to a pay-for-performance system. Physicians can participate in the QPP through one of three reporting methods: the traditional merit-based incentive payment system (MIPS), MIPS Value Pathways (MVPs), or Advanced Alternative Payment Models (APMs). These reporting methods require physicians to submit data on quality measures, which are averaged to determine a total quality performance score, which is weighted along with other QPP measures related to self-performance to provide an aggregate final performance score. This final score is used to determine either a negative, neutral, or positive percentage modifier for the physician's Medicare reimbursement payments, which applies to the fiscal year two years following the year of reporting. Quality measures are either specialty-specific or cross-specialty, meaning that they are reportable by any physician specialty. No studies have compared performance across physician specialty categories on these measures. Critics argue that CMS has not ensured equitable reporting of cross-specialty quality measures due to the difference in emphasis on aspects of care of different physician specialties, potentially advantaging some. For example, family medicine physicians may score higher on the blood pressure control quality measure due to its relevance in their practice. Significant performance differences could highlight areas of improvement for certain physicians in certain specialties and guide balanced measure development. The QPP currently uses non-specialty-specific historical quality performance scores as benchmarks to determine current-year quality measure scores, likely leading to unfair comparisons. Establishing specialty-specific benchmarks for cross-specialty measures would promote equitable evaluation and fair competition among all participating physicians.

Mechanisms of response and tolerance to active RAS inhibition in KRAS-mutant NSCLC.

Resistance to inactive state-selective RASG12C inhibitors frequently entails accumulation of RASGTP, rendering effective inhibition of active RAS potentially desirable. Here, we evaluated the anti-tumor activity of the RAS(ON) multi-selective tri-complex inhibitor RMC-7977 and dissected mechanisms of response and tolerance in KRASG12C-mutant NSCLC. Broad-spectrum, reversible RASGTP inhibition with or without concurrent covalent targeting of active RASG12C yielded superior and differentiated antitumor activity across diverse co-mutational KRASG12C-mutant NSCLC mouse models of primary or acquired RASG12C(ON) or (OFF) inhibitor resistance. Interrogation of time-resolved single cell transcriptional responses established an in vivo atlas of multi-modal acute and chronic RAS pathway inhibition in the NSCLC ecosystem and uncovered a regenerative mucinous transcriptional program that supports long-term tumor cell persistence. In patients with advanced KRASG12C-mutant NSCLC, the presence of mucinous histological features portended poor response to sotorasib or adagrasib. Our results have potential implications for personalized medicine and the development of rational RAS inhibitor-anchored therapeutic strategies.

Prompt engineering on leveraging large language models in generating response to InBasket messages.

OBJECTIVES: Large Language Models (LLMs) have been proposed as a solution to address high volumes of Patient Medical Advice Requests (PMARs). This study addresses whether LLMs can generate high quality draft responses to PMARs that satisfies both patients and clinicians with prompt engineering. MATERIALS AND METHODS: We designed a novel human-involved iterative processes to train and validate prompts to LLM in creating appropriate responses to PMARs. GPT-4 was used to generate response to the messages. We updated the prompts, and evaluated both clinician and patient acceptance of LLM-generated draft responses at each iteration, and tested the optimized prompt on independent validation data sets. The optimized prompt was implemented in the electronic health record production environment and tested by 69 primary care clinicians. RESULTS: After 3 iterations of prompt engineering, physician acceptance of draft suitability increased from 62% to 84% (P <.001) in the validation dataset (N = 200), and 74% of drafts in the test dataset were rated as "helpful." Patients also noted significantly increased favorability of message tone (78%) and overall quality (80%) for the optimized prompt compared to the original prompt in the training dataset, patients were unable to differentiate human and LLM-generated draft PMAR responses for 76% of the messages, in contrast to the earlier preference for human-generated responses. Majority (72%) of clinicians believed it can reduce cognitive load in dealing with InBasket messages. DISCUSSION AND CONCLUSION: Informed by clinician and patient feedback synergistically, tuning in LLM prompt alone can be effective in creating clinically relevant and useful draft responses to PMARs.

The new frontier: utilizing ChatGPT to expand craniofacial research.

BACKGROUND: Due to the importance of evidence-based research in plastic surgery, the authors of this study aimed to assess the accuracy of ChatGPT in generating novel systematic review ideas within the field of craniofacial surgery. METHODS: ChatGPT was prompted to generate 20 novel systematic review ideas for 10 different subcategories within the field of craniofacial surgery. For each topic, the chatbot was told to give 10 "general" and 10 "specific" ideas that were related to the concept. In order to determine the accuracy of ChatGPT, a literature review was conducted using PubMed, CINAHL, Embase, and Cochrane. RESULTS: In total, 200 total systematic review research ideas were generated by ChatGPT. We found that the algorithm had an overall 57.5% accuracy at identifying novel systematic review ideas. ChatGPT was found to be 39% accurate for general topics and 76% accurate for specific topics. CONCLUSION: Craniofacial surgeons should use ChatGPT as a tool. We found that ChatGPT provided more precise answers with specific research questions than with general questions and helped narrow down the search scope, leading to a more relevant and accurate response. Beyond research purposes, ChatGPT can augment patient consultations, improve healthcare equity, and assist in clinical decisionmaking. With rapid advancements in artificial intelligence (AI), it is important for plastic surgeons to consider using AI in their clinical practice to improve patient-centered outcomes.

Hip Sideline Emergencies and Hip Injuries in Elite Athletes.

PURPOSE OF REVIEW: Hip injuries in elite athletes are an increasingly recognized problem and range from chronic overuse injuries, such as adductor strains and labral tears, to acute traumatic injuries such as hip dislocations. In this article, we review common hip pathology experienced by elite athletes and sideline management of emergent hip injuries. RECENT FINDINGS: Elite athletes are subject to unique physical and mental stresses and therefore must be evaluated and treated in a unique manner. Hip and groin injuries account for approximately 6% of sport injuries overall and 3-15% of all injuries in professional sports. Hip sideline emergencies were rare but can include hip dislocations, subluxations, and avulsion fractures. Hip and groin injuries represent an important subset of injuries which can greatly impact an athlete's ability to perform. Understanding the physiology and types of hip/groin injuries, which athletes are prone to injuries, the impact on recovery time, recurrence risk, and the potential need for surgery aid sports medicine physicians in decision-making.

Are tourniquets indicated in total knee arthroplasty in the era of tranexamic acid: A meta-analysis and systematic review.

Introduction: There is conflicting evidence in the literature regarding the clinical utility of tourniquets in total knee arthroplasty (TKA), specifically in regards to perioperative blood loss. In this meta-analysis and systematic review, we aim to evaluate the clinical advantages and disadvantages associated with tourniquet use in the setting of TKA. Methods: A systematic review was conducted through April 2017 using keywords: "tourniquet" and "total knee arthroplasty" or "total knee replacement". Perioperative variables including TXA use, blood loss, incidence of venous thromboembolism (VTE), and wound complications were either extracted from the studies or corresponding authors were contacted. A sub-analysis was conducted to evaluate the effects of TXA on intraoperative and total blood loss (TBL), and VTE incidence. Results: After review of 558 articles, 19 studies reporting outcomes in 1094 patients were analyzed. Intraoperative blood loss was significantly lower in the tourniquet cohorts compared to non-tourniquet (p < 0.01). TBL was reduced in tourniquet groups but not significantly (p = 0.08). In contrast, calculated blood loss was greater in tourniquet groups, but this difference was not significant (p = 0.43). There was a greater likelihood for wound complications and VTE among tourniquet assisted TKA, albeit only significant for the former (p = 0.01). TXA sub-analysis demonstrated intraoperative blood loss was significantly reduced with tourniquet use regardless of TXA implementation (p < 0.01). In studies without TXA, tourniquet patients were at greater risk of developing VTE (p = 0.08). These risks decreased with TXA administration. Conclusion: This meta-analysis demonstrates that tourniquets prevent intraoperative blood loss, yet within the postoperative period, there is no significant difference in TBL between tourniquet and non-tourniquet assisted TKA. Level of evidence: Level II; Systematic Review and Meta-Analysis.

Combined inhibition of KRASG12C and mTORC1 kinase is synergistic in non-small cell lung cancer.

Current KRASG12C (OFF) inhibitors that target inactive GDP-bound KRASG12C cause responses in less than half of patients and these responses are not durable. A class of RASG12C (ON) inhibitors that targets active GTP-bound KRASG12C blocks ERK signaling more potently than the inactive-state inhibitors. Sensitivity to either class of agents is strongly correlated with inhibition of mTORC1 activity. We have previously shown that PI3K/mTOR and ERK-signaling pathways converge on key cellular processes and that inhibition of both pathways is required for inhibition of these processes and for significant antitumor activity. We find here that the combination of a KRASG12C inhibitor with a selective mTORC1 kinase inhibitor causes synergistic inhibition of Cyclin D1 expression and cap-dependent translation. Moreover, BIM upregulation by KRASG12C inhibition and inhibition of MCL-1 expression by the mTORC1 inhibitor are both required to induce significant cell death. In vivo, this combination causes deep, durable tumor regressions and is well tolerated. This study suggests that the ERK and PI3K/mTOR pathways each mitigate the effects of inhibition of the other and that combinatorial inhibition is a potential strategy for treating KRASG12C-dependent lung cancer.

Emergent coronary revascularization with percutaneous coronary intervention and coronary artery bypass grafting in patients receiving extracorporeal cardiopulmonary resuscitation.

OBJECTIVES: Extracorporeal cardiopulmonary resuscitation (ECPR) has emerged as a rescue for refractory cardiac arrest, of which acute coronary syndrome is a common cause. Data on the coronary revascularization strategy in patients receiving ECPR remain limited. METHODS: The ECPR databases from two referral hospitals were screened for patients who underwent emergent revascularization. The baseline characteristics were matched 1:1 using propensity score between patients who underwent coronary artery bypass grafting (CABG) and those who received percutaneous coronary intervention (PCI). Outcomes, including success rate of weaning from extracorporeal membrane oxygenation (ECMO), hospital survival, and midterm survival in hospital survivors, were compared between CABG and PCI. RESULTS: After matching, most of the patients (95%) had triple vessel disease. Compared with PCI (n = 40), emergent CABG (n = 40) had better early outcomes, in terms of the rates of successful ECMO weaning (71.1% vs 48.7%, P = 0.05) and hospital survival (56.4% versus 32.4%, P = 0.04). After a mean follow-up of 2 years, both revascularization strategies were associated with favourable midterm survival among hospital survivors (75.3% after CABG vs 88.9% after PCI, P = 0.49), with a trend towards fewer reinterventions in patients who underwent CABG (P = 0.07). CONCLUSIONS: In patients who received ECPR because of triple vessel disease, the hospital outcomes were better after emergent CABG than after PCI. More evidence is required to determine the optimal revascularization strategy for patients who receive ECPR.

The SWELL1 Channel Promotes Ischemic Brain Damage by Mediating Neuronal Swelling and Glutamate Toxicity.

Cytotoxic neuronal swelling and glutamate excitotoxicity are two hallmarks of ischemic stroke. However, the underlying molecular mechanisms are not well understood. Here, it is reported that SWELL1, the essential subunit of the volume-regulated anion channel (VRAC), plays a dual role in ischemic injury by promoting neuronal swelling and glutamate excitotoxicity. SWELL1 expression is upregulated in neurons and astrocytes after experimental stroke in mice. The neuronal SWELL1 channel is activated by intracellular hypertonicity, leading to Cl- influx-dependent cytotoxic neuronal swelling and subsequent cell death. Additionally, the SWELL1 channel in astrocytes mediates pathological glutamate release, indicated by increases in neuronal slow inward current frequency and tonic NMDAR current. Pharmacologically, targeting VRAC with a new inhibitor, an FDA-approved drug Dicumarol, attenuated cytotoxic neuronal swelling and cell death, reduced astrocytic glutamate release, and provided significant neuroprotection in mice when administered either before or after ischemia. Therefore, these findings uncover the pleiotropic effects of the SWELL1 channel in neurons and astrocytes in the pathogenesis of ischemic stroke and provide proof of concept for therapeutically targeting it in this disease.

Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.

Purpose: Automated machine learning (AutoML) has emerged as a novel tool for medical professionals lacking coding experience, enabling them to develop predictive models for treatment outcomes. This study evaluated the performance of AutoML tools in developing models predicting the success of pneumatic retinopexy (PR) in treatment of rhegmatogenous retinal detachment (RRD). These models were then compared with custom models created by machine learning (ML) experts. Design: Retrospective multicenter study. Participants: Five hundred and thirty nine consecutive patients with primary RRD that underwent PR by a vitreoretinal fellow at 6 training hospitals between 2002 and 2022. Methods: We used 2 AutoML platforms: MATLAB Classification Learner and Google Cloud AutoML. Additional models were developed by computer scientists. We included patient demographics and baseline characteristics, including lens and macula status, RRD size, number and location of breaks, presence of vitreous hemorrhage and lattice degeneration, and physicians' experience. The dataset was split into a training (n = 483) and test set (n = 56). The training set, with a 2:1 success-to-failure ratio, was used to train the MATLAB models. Because Google Cloud AutoML requires a minimum of 1000 samples, the training set was tripled to create a new set with 1449 datapoints. Additionally, balanced datasets with a 1:1 success-to-failure ratio were created using Python. Main Outcome Measures: Single-procedure anatomic success rate, as predicted by the ML models. F2 scores and area under the receiver operating curve (AUROC) were used as primary metrics to compare models. Results: The best performing AutoML model (F2 score: 0.85; AUROC: 0.90; MATLAB), showed comparable performance to the custom model (0.92, 0.86) when trained on the balanced datasets. However, training the AutoML model with imbalanced data yielded misleadingly high AUROC (0.81) despite low F2-score (0.2) and sensitivity (0.17). Conclusions: We demonstrated the feasibility of using AutoML as an accessible tool for medical professionals to develop models from clinical data. Such models can ultimately aid in the clinical decision-making, contributing to better patient outcomes. However, outcomes can be misleading or unreliable if used naively. Limitations exist, particularly if datasets contain missing variables or are highly imbalanced. Proper model selection and data preprocessing can improve the reliability of AutoML tools. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Advancing Lifestyle Medicine in New York City's Public Health Care System.

Chronic diseases are the leading cause of death and disability in the United States, and much of this burden can be attributed to lifestyle and behavioral risk factors. Lifestyle medicine is an approach to preventing and treating lifestyle-related chronic disease using evidence-based lifestyle modification as a primary modality. NYC Health + Hospitals, the largest municipal public health care system in the United States, is a national pioneer in incorporating lifestyle medicine systemwide. In 2019, a pilot lifestyle medicine program was launched at NYC Health + Hospitals/Bellevue to improve cardiometabolic health in high-risk patients through intensive support for evidence-based lifestyle changes. Analyses of program data collected from January 29, 2019 to February 26, 2020 demonstrated feasibility, high demand for services, high patient satisfaction, and clinically and statistically significant improvements in cardiometabolic risk factors. This pilot is being expanded to 6 new NYC Health + Hospitals sites spanning all 5 NYC boroughs. As part of the expansion, many changes have been implemented to enhance the original pilot model, scale services effectively, and generate more interest and incentives in lifestyle medicine for staff and patients across the health care system, including a plant-based default meal program for inpatients. This narrative review describes the pilot model and outcomes, the expansion process, and lessons learned to serve as a guide for other health systems.