Cell-Based Therapies Induce Tolerance of Vascularized Composite Allotransplants: A Systematic Review.

INTRODUCTION: Vascularized composite allotransplantation (VCA) is the transplantation of multiple tissue types as a solution for devastating injuries. Despite the highly encouraging functional outcomes of VCA, the consequences of long-term immunosuppression remain the main obstacle in its application. In this review, we provide researchers and surgeons with a summary of the latest advances in the field of cell-based therapies for VCA tolerance. METHODS: Four electronic databases were searched: PubMed, Scopus, Cumulative Index to Nursing and Allied Health Literature , and Web of Science. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as the basis of our organization. RESULTS: Hematopoietic stem cells prolonged VCA survival. A combination of immature dendritic cells and tacrolimus was superior to tacrolimus alone. T cell Ig domain and mucin domain modified mature dendritic cells increased VCA tolerance. Bone marrow-derived mesenchymal stem cells prolonged survival of VCAs. A combination of adipose-derived mesenchymal stem cells, cytotoxic T-lymphocyte antigen 4 immunoglobulin, and antilymphocyte serum significantly improved VCA tolerance. Ex-vivo allotransplant perfusion with recipient's bone marrow-derived mesenchymal stem cells increased VCA survival. Recipient's adipose-derived mesenchymal stem cells and systemic immunosuppression prolonged VCA survival more than any of those agents alone. Additionally, a combination of peripheral blood mononuclear cells shortly incubated in mitomycin and cyclosporine significantly improved VCA survival. Finally, a combination of donor recipient chimeric cells, anti-αß-T cell receptor (TCR), and cyclosporine significantly prolonged VCA tolerance. CONCLUSIONS: Evidence from animal studies shows that cell-based therapies can prolong survival of VCAs. However, there remain many obstacles for these therapies, and they require rigorous clinical research given the rarity of the subjects and the complexity of the therapies. The major limitations of cell-based therapies include the need for conditioning with immunosuppressive drugs and radiation, causing significant toxicity. Safety concerns also persist as most research is on animal models. While completely replacing traditional immunosuppression with cell-based methods is unlikely soon, these therapies could reduce the need for high doses of immunosuppressants and improve VCA tolerance.

Evaluation of the Aging Effect on Peripheral Nerve Regeneration: A Systematic Review.

INTRODUCTION: Peripheral nerve injuries have been associated with increased healthcare costs and decreased patients' quality of life. Aging represents one factor that slows the speed of peripheral nervous system (PNS) regeneration. Since cellular homeostasis imbalance associated with aging lead to an increased failure in nerve regeneration in mammals of advanced age, this systematic review aims to determine the main molecular and cellular mechanisms involved in peripheral nerve regeneration in aged murine models after a peripheral nerve injuries. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a literature search of 4 databases was conducted in July 2022 for studies comparing the peripheral nerve regeneration capability between young and aged murine models. RESULTS: After the initial search yielded 744 publications, ten articles fulfilled the inclusion criteria. These studies show that age-related changes such as chronic inflammatory state, delayed macrophages' response to injury, dysfunctional Schwann Cells (SCs), and microenvironment alterations cause a reduction in the regenerative capability of the PNS in murine models. Furthermore, identifying altered gene expression patterns of SC after nerve damage can contribute to the understanding of physiological modifications produced by aging. CONCLUSIONS: The interaction between macrophages and SC plays a crucial role in the nerve regeneration of aged models. Therefore, studies aimed at developing new and promising therapies for nerve regeneration should focus on these cellular groups to enhance the regenerative capabilities of the PNS in elderly populations.

Severity of illness and risk of mortality in Mayo Clinic's virtual hybrid advanced care at home program: a retrospective cohort study.

BACKGROUND: In July 2020, Mayo Clinic launched Advanced Care at Home (ACH), a high-acuity virtual hybrid hospital-at-home model (HaH) of care at Mayo Clinic Florida and Northwest Wisconsin, an urban destination medical center and a rural community practice respectively. This study aims to describe demographic characteristics of ACH patients as well as their acuity of illness using severity of illness (SOI) and risk of mortality (ROM), to illustrate the complexity of patients in the program, taking into account the different diagnostic related groups. METHODS: Mayo Clinic uses All Patient Refined-Diagnosis Related Groups (APR-DRG) to calculate SOI and ROM on hospitalized patients. APR-DRG data, including SOI and ROM, were gathered from individual chart reviews from July 6, 2020, to March 31, 2022. RESULTS:  Out of 923 patients discharged from ACH, the average APR-DRG SOI was 2.89 (SD 0.81) and ROM was 2.73. (SD 0.92). Mean age was 70.88 (SD 14.46) years, 54.6% were male patients and the average length of stay was 4.10 days. The most frequent diagnosis was COVID-19 infection with 162 patients (17.6%), followed by heart failure exacerbation (12.7%) and septicemia (10.9%). The 30-day readmission rate after discharge from ACH was 11.2% (n = 103) and the 30-day mortality rate was 1.8% (n = 17). There were no in-program patient deaths. CONCLUSIONS: SOI and ROM from patients at the ACH program have been shown to be in the range of "moderate/major" according to the APR-DRG classification. The ACH program is capable of accepting and managing highly complex patients that require advanced therapeutic means. Furthermore, the ACH program has an in-program mortality rate of 0 to date. Therefore, ACH is rising as a capable alternative to the brick-and-mortar hospital.

Patient Satisfaction With a Multisite, Multiregional Remote Patient Monitoring Program for Acute and Chronic Condition Management: Survey-Based Analysis.

BACKGROUND: Remote patient monitoring (RPM) is an option for continuously managing the care of patients in the comfort of their homes or locations outside hospitals and clinics. Patient engagement with RPM programs is essential for achieving successful outcomes and high quality of care. When relying on technology to facilitate monitoring and shifting disease management to the home environment, it is important to understand the patients' experiences to enable quality improvement. OBJECTIVE: This study aimed to describe patients' experiences and overall satisfaction with an RPM program for acute and chronic conditions in a multisite, multiregional health care system. METHODS: Between January 1, 2021, and August 31, 2022, a patient experience survey was delivered via email to all patients enrolled in the RPM program. The survey encompassed 19 questions across 4 categories regarding comfort, equipment, communication, and overall experience, as well as 2 open-ended questions. Descriptive analysis of the survey response data was performed using frequency distribution and percentages. RESULTS: Surveys were sent to 8535 patients. The survey response rate was 37.16% (3172/8535) and the completion rate was 95.23% (3172/3331). Survey results indicated that 88.97% (2783/3128) of participants agreed or strongly agreed that the program helped them feel comfortable managing their health from home. Furthermore, 93.58% (2873/3070) were satisfied with the RPM program and ready to graduate when meeting the program goals. In addition, patient confidence in this model of care was confirmed by 92.76% (2846/3068) of the participants who would recommend RPM to people with similar conditions. There were no differences in ease of technology use according to age. Those with high school or less education were more likely to agree that the equipment and educational materials helped them feel more informed about their care plans than those with higher education levels. CONCLUSIONS: This multisite, multiregional RPM program has become a reliable health care delivery model for the management of acute and chronic conditions outside hospitals and clinics. Program participants reported an excellent overall experience and a high level of satisfaction in managing their health from the comfort of their home environment.

Avoiding Escalation to the Emergency Department by Activating an In-Home Rapid Response Team in the 30 Days After Hospital-at-Home Discharge.

BACKGROUND: Mayo Clinic's virtual hybrid hospital-at-home program, Advanced Care at Home (ACH) monitors acute and post-acute patients for signs of deterioration and institutes a rapid response (RR) system if detected. OBJECTIVE: This study aimed to describe Mayo Clinic's ACH RR team and its effect on emergency department (ED) use and readmission rates. METHODS: This was a retrospective review of all post-inpatient (restorative phase) ACH patients admitted from July 6, 2020 through June 30, 2021. If the restorative patient had a clinical decompensation, an RR was activated. All RR activations were analyzed for patient demographic characteristics, admitting and escalation diagnosis, time spent by virtual team on the RR, and whether the RR resulted in transport to the ED or hospital readmission. RESULTS: Three hundred and twenty patients were admitted to ACH during the study interval; 230 received restorative care. Seventy-two patients (31.3%) had events that triggered an RR. Fifty (69.4%) of the RR events were related to the admission diagnosis (p < 0.001; 95% CI 0.59-0.80). Twelve patients (16.7%) required transport to an ED for further treatment and were readmitted and 60 patients (83.3%) were able to be treated successfully in the home by the RR team (p < 0.001; 95% CI 0.08-0.25). CONCLUSIONS: The use of an ACH RR team was effective at limiting both escalations back to an ED and hospital readmissions, as 83% of deteriorating patients were successfully stabilized and managed in their homes. Implementing a hospital-at-home RR team can reduce the need for ED use by providing critical resources and carrying out required interventions to stabilize the patient's condition.

Smartphones and Threshold-Based Monitoring Methods Effectively Detect Falls Remotely: A Systematic Review.

In the US, at least one fall occurs in at least 28.7% of community-dwelling seniors 65 and older each year. Falls had medical costs of USD 51 billion in 2015 and are projected to reach USD 100 billion by 2030. This review aims to discuss the extent of smartphone (SP) usage in fall detection and prevention across a range of care settings. A computerized search was conducted on six electronic databases to investigate the use of remote sensing technology, wireless technology, and other related MeSH terms for detecting and preventing falls. After applying inclusion and exclusion criteria, 44 studies were included. Most of the studies targeted detecting falls, two focused on detecting and preventing falls, and one only looked at preventing falls. Accelerometers were employed in all the experiments for the detection and/or prevention of falls. The most frequent course of action following a fall event was an alarm to the guardian. Numerous studies investigated in this research used accelerometer data analysis, machine learning, and data from previous falls to devise a boundary and increase detection accuracy. SP was found to have potential as a fall detection system but is not widely implemented. Technology-based applications are being developed to protect at-risk individuals from falls, with the objective of providing more effective and efficient interventions than traditional means. Successful healthcare technology implementation requires cooperation between engineers, clinicians, and administrators.

Perceived Age as a Mortality and Comorbidity Predictor: A Systematic Review.

INTRODUCTION: Perceived age is defined as how old a person looks to external evaluators. It reflects the underlying biological age, which is a measure based on physical and physiological parameters reflecting a person's aging process more accurately than chronological age. People with a higher biological age have shorter lives compared to those with a lower biological age with the same chronological age. Our review aims to find whether increased perceived age is a risk factor for overall mortality risk or comorbidities. METHODS: A literature search of three databases was conducted following the PRISMA guidelines for studies analyzing perceived age or isolated facial characteristics of old age and their relationship to mortality risk or comorbidity outcomes. Data on the number of patients, type and characteristics of evaluation methods, evaluator characteristics, mean chronologic age, facial characteristics studied, measured outcomes, and study results were collected. RESULTS: Out of 977 studies, 15 fulfilled the inclusion criteria. These studies found an increase in mortality risk of 6-51% in older-looking people compared to controls (HR 1.06-1.51, p < 0.05). In addition, perceived age and some facial characteristics of old age were also associated with cardiovascular risk and myocardial infarction, cognitive function, bone mineral density, and chronic obstructive pulmonary disease (COPD). CONCLUSION: Perceived age promises to be a clinically useful predictor of overall mortality and cardiovascular, pulmonary, cognitive, and osseous comorbidities. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

High Satisfaction With a Virtual Assistant for Plastic Surgery Frequently Asked Questions.

BACKGROUND: Most of a surgeon's office time is dedicated to patient education, preventing an appropriate patient-physician relationship. Telephone-accessed artificial intelligent virtual assistants (AIVAs) that simulate a human conversation and answer preoperative frequently asked questions (FAQs) can be effective solutions to this matter. An AIVA capable of answering preoperative plastic surgery-related FAQs has previously been described by the authors. OBJECTIVES: The aim of this paper was to determine patients' perception and satisfaction with an AIVA. METHODS: Twenty-six adult patients from a plastic surgery service answered a 3-part survey consisting of: (1) an evaluation of the answers' correctness, (2) their agreement with the feasibility, usefulness, and future uses of the AIVA, and (3) a section on comments. The first part made it possible to measure the system's accuracy, and the second to evaluate perception and satisfaction. The data were analyzed with Microsoft Excel 2010 (Microsoft Corporation, Redmond, WA). RESULTS: The AIVA correctly answered the patients' questions 98.5% of the time, and the topic with the lowest accuracy was "nausea." Additionally, 88% of patients agreed with the statements of the second part of the survey. Thus, the patients' perception was positive and overall satisfaction with the AIVA was high. Patients agreed the least with using the AIVA to select their surgical procedure. The comments provided improvement areas for subsequent stages of the project. CONCLUSIONS: The results show that patients were satisfied and expressed a positive experience with using the AIVA to answer plastic surgery FAQs before surgery. The system is also highly accurate.

Simulation and Artificial Intelligence in Rhinoplasty: A Systematic Review.

BACKGROUND: Rhinoplasty is one of the most popular cosmetic procedures. The complexity of the nasal structure and the substantial aesthetic and functional impact of the operation make rhinoplasty very challenging. The past few years have witnessed an increasing implementation of artificial intelligence (AI) and simulation systems into plastic surgery practice. This review explores the potential uses of AI and simulation models in rhinoplasty. METHODS: Five electronic databases were searched: PubMed, CINAHL, EMBASE, Scopus, and Web of Science. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. RESULTS: Several simulation models were described to predict the nasal shape that aesthetically matches the patient's face, indicate the implant size in augmentation rhinoplasty and construct three-dimensional (3D) facial images from two-dimensional images. Machine learning was used to learn surgeons' rhinoplasty styles and accurately simulate the outcomes. Deep learning was used to predict rhinoplasty status accurately and analyze the factors associated with increased facial attractiveness after rhinoplasty. Finally, a deep learning model was used to predict patients' age before and after rhinoplasty proving that the procedure made the patients look younger. CONCLUSION: 3D simulation models and AI models can revolutionalize the practice of functional and aesthetic rhinoplasty. Simulation systems can be beneficial in preoperative planning, intra-operative decision making, and postoperative evaluation. In addition, AI models can be trained to carry out tasks that are either challenging or time-consuming for surgeons. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

A narrative review of telemedicine and its adoption across specialties.

Background and Objective: Telemedicine and video consultation are crucial advancements in healthcare, allowing remote delivery of care. Telemedicine, encompassing various technologies like wearable devices, mobile health, and telemedicine, plays a significant role in managing illnesses and promoting wellness. The corona virus disease 2019 (COVID-19) pandemic accelerated the adoption of telemedicine, ensuring convenient access to medical services while maintaining physical distance. Legislation has supported its integration into clinical practice and addressed compensation issues. However, ensuring clinical appropriateness and sustainability of telemedicine post-expansion has gained attention. We south to identify the most friendly and resistant specialties to telemedicine and to understand areas of interest within those specialties to grasp potential barriers to its use. Methods: We aimed to identify articles that incorporated telemedicine in any medical or surgical specialty and determine the adoption rate and intent of this new form of care. Additionally, a secondary search within these databases was conducted to analyze the advantages, disadvantages, and implementation of telemedicine in the healthcare system. Non-English articles and those without full text were excluded. The study selection and data collection process involved using search terms such as "medicine", "surgery", "specialties", "telemedicine", and "telemedicine". Key Content and Findings: Telemedicine adoption varies among specialties. The pandemic led to increased usage, with telemedicine consultations comprising 30.1% of all visits, but specialties like mental health, gastroenterology, and endocrinology showed higher rates of adoption compared to optometry, physical therapy, and orthopedic surgery. Conclusions: The data shows that telemedicine uptake varies by specialty and condition due to the need for physical exams. In-person visits still dominate new patient visits despite increased telemedicine use. Telemedicine cannot fully replace in-person care but has increased visit volume and is secure. The adoption of telemedicine is higher in medical practices than in surgical practices, with neurosurgery and urology leading. Further research is needed to assess telemedicine's suitability and effectiveness in different specialties and conditions.

Machine Learning Algorithms Predict Long-Term Postoperative Opioid Misuse: A Systematic Review.

INTRODUCTION: A steadily rising opioid pandemic has left the US suffering significant social, economic, and health crises. Machine learning (ML) domains have been utilized to predict prolonged postoperative opioid (PPO) use. This systematic review aims to compile all up-to-date studies addressing such algorithms' use in clinical practice. METHODS: We searched PubMed/MEDLINE, EMBASE, CINAHL, and Web of Science using the keywords "machine learning," "opioid," and "prediction." The results were limited to human studies with full-text availability in English. We included all peer-reviewed journal articles that addressed an ML model to predict PPO use by adult patients. RESULTS: Fifteen studies were included with a sample size ranging from 381 to 112898, primarily orthopedic-surgery-related. Most authors define a prolonged misuse of opioids if it extends beyond 90 days postoperatively. Input variables ranged from 9 to 23 and were primarily preoperative. Most studies developed and tested at least two algorithms and then enhanced the best-performing model for use retrospectively on electronic medical records. The best-performing models were decision-tree-based boosting algorithms in 5 studies with AUC ranging from .81 to .66 and Brier scores ranging from .073 to .13, followed second by logistic regression classifiers in 5 studies. The topmost contributing variable was preoperative opioid use, followed by depression and antidepressant use, age, and use of instrumentation. CONCLUSIONS: ML algorithms have demonstrated promising potential as a decision-supportive tool in predicting prolonged opioid use in post-surgical patients. Further validation studies would allow for their confident incorporation into daily clinical practice.

The usefulness of artificial intelligence in breast reconstruction: a systematic review.

BACKGROUND: Artificial Intelligence (AI) offers an approach to predictive modeling. The model learns to determine specific patterns of undesirable outcomes in a dataset. Therefore, a decision-making algorithm can be built based on these patterns to prevent negative results. This systematic review aimed to evaluate the usefulness of AI in breast reconstruction. METHODS: A systematic review was conducted in August 2022 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. MEDLINE, EMBASE, SCOPUS, and Google Scholar online databases were queried to capture all publications studying the use of artificial intelligence in breast reconstruction. RESULTS: A total of 23 studies were full text-screened after removing duplicates, and twelve articles fulfilled our inclusion criteria. The Machine Learning algorithms applied for neuropathic pain, lymphedema diagnosis, microvascular abdominal flap failure, donor site complications associated to muscle sparing Transverse Rectus Abdominis flap, surgical complications, financial toxicity, and patient-reported outcomes after breast surgery demonstrated that AI is a helpful tool to accurately predict patient results. In addition, one study used Computer Vision technology to assist in Deep Inferior Epigastric Perforator Artery detection for flap design, considerably reducing the preoperative time compared to manual identification. CONCLUSIONS: In breast reconstruction, AI can help the surgeon by optimizing the perioperative patients' counseling to predict negative outcomes, allowing execution of timely interventions and reducing the postoperative burden, which leads to obtaining the most successful results and improving patient satisfaction.

Development and evaluation of best practice advisory alert for patient eligibility in a hospital-at-home program: A multicenter retrospective study.

BACKGROUND: Hospital-at-home (HaH) is a growing model of care that has been shown to improve patient outcomes, satisfaction, and cost-effectiveness. However, selecting appropriate patients for HaH is challenging, often requiring burdensome manual screening by clinicians. To facilitate HaH enrollment, electronic health record (EHR) tools such as best practice advisories (BPAs) can be used to alert providers of potential HaH candidates. OBJECTIVE: To describe the development and implementation of a BPA for identifying HaH eligible patients in Mayo Clinic's Advanced Care at Home (ACH) program, and to evaluate the provider response and the patient characteristics that triggered the BPA. DESIGN, SETTING, AND PARTICIPANTS: We conducted a retrospective multicenter study of hospitalized patients who triggered the BPA notification for ACH eligibility between March and December 2021 at Mayo Clinic in Jacksonville, FL and Mayo Clinic Health System in Eau Claire, WI. We extracted demographic and diagnosis data from the patients as well as characteristics of the providers who received the BPA notification. INTERVENTION: The BPA was developed based on the ACH inclusion and exclusion criteria, which were derived from clinical guidelines, literature review, and expert consensus. The BPA was integrated into the EHR and displayed a pop-up message to the provider when a patient met the criteria for ACH eligibility. The provider could choose to refer the patient to ACH, dismiss the notification, or defer the decision. MAIN OUTCOMES AND MEASURES: The main outcomes were the number and proportion of BPA notifications that resulted in a referral to ACH, and the number and proportion of referrals that were accepted by the ACH clinical team and transferred to ACH. We also analyzed the factors associated with the provider's decision to refer or not refer the patient to ACH, such as the provider's role, location, and specialty. RESULTS: During the study period, 8962 notifications were triggered for 2847 patients. Providers opted to refer 711 (11.4%) of the total notifications linked to 324 unique patients. After review by the ACH clinical team, 31 of the 324 referrals (9.6%) met clinical and social criteria and were transferred to ACH. In multivariable analysis, Wisconsin nurses, physician assistants, and in-training personnel had lower odds of referring the patients to ACH when compared to attending physicians.

Evaluating the exoscope as an alternative to the operating microscope in plastic surgery.

BACKGROUND: Microsurgery is most commonly used in the anastomosis of vessels, flap harvesting, lymphedema, and nerve reconstruction, among others. During the 1920s the first microscope was invented by Nylen and Holmgren, quickly becoming the gold standard for microsurgery. However, technological advances have come forth in the form of exoscopes. METHODS: A search for full-text articles where using an exoscope was compared with a traditional operating microscope was conducted on the databases PubMed, Scopus, Web of Science, and Embase. The following terms were used to guide our search: Microscope AND exoscope AND plastic surgery; Microscope AND exoscope AND microvascular surgery. RESULTS: Our search yielded 69 studies, of which 12 were included. Five exoscope systems were used by the authors. All studies reported the exoscope as a valid alternative to the standard operating microscope. The exoscope was reported as non-inferior to the operating microscope. Although some studies reported lower quality of image, this did not seem to influence the outcome of surgeries. Newer models may have bridged the gap between the operating microscope's image quality and the exoscope. Superior ergonomics was always reported among the included studies. CONCLUSION: Based on our search, we conclude that the exoscope is a safe and valid alternative to the operating microscope in plastic surgery. As newer models are now commercially available, these have overcome difficulties in image quality and zoom capabilities, responsible for the main drawbacks of the first exoscope systems.

Radiomics and Artificial Intelligence in Predicting Axillary Lymph Node Metastasis in Breast Cancer: A Systematic Review.

BACKGROUND: Breast cancer is the most common malignancy and the second most common cause of death in women worldwide. Axillary lymph node metastasis (ALNM) is the most significant prognostic factor in breast cancer. Under the current guidelines, sentinel lymph node biopsy (SLNB) is the standard of axillary staging in patients with clinically-node negative breast cancer. Despite the minimally invasive nature of SLNB, it can cause short and long-term morbidities, including pain, sensory impairment, and upper limb motor dysfunction. However, lymphedema remains the most feared adverse event, and it affects 7% of patients within 36 months of follow-up. Recently, we have witnessed the implication of radiomics and artificial intelligence domains in the diagnosis and follow-up of many malignancies with promising results. Therefore, we have conducted a systematic search to investigate the potential of radiomics and artificial intelligence in predicting ALNM. METHODS: Four electronic databases were searched: PubMed, Scopus, CINAHL, and Web of Science. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as our basis of organization. RESULTS: For radiomics, the area under the curve (AUC) for the included studies ranged from 0.715 to 0.93. Accuracy ranged from 67.7% to 98%. Sensitivity and specificity ranged from 70.3% to 97.8% and 58.4% to 98.2%, respectively. For other artificial intelligence methods, AUC ranged from 0.68 to 0.98, while accuracy ranged from 55% to 89%. CONCLUSION: The results of radiomics and artificial intelligence in predicting ALNM are promising. However, validation as a substitute for SLNB requires more substantial evidence from large randomized trials.

A Review on the Management of Peripheral Neuropathic Pain Following Breast Cancer.

Postmastectomy pain syndrome (PMPS) is a common and debilitating form of postsurgical pain with neuropathic characteristics, presenting as burning, stabbing, or pulling sensations after mastectomy, lumpectomy, or other breast procedures. With a prevalence of 31%, the risk factors for PMPS include younger age, psychosocial factors, radiotherapy, axillary lymph node dissection, and a history of chronic pain. This review evaluates the pharmacological and surgical options for managing PMPS. Pharmacological treatment options include antidepressants, gabapentinoids, levetiracetam, capsaicin, and topical lidocaine. Procedural and surgical options include fat grafting, nerve blocks, radiofrequency ablation, peripheral nerve surgery, serratus plane block, and botulinum toxin injections. Despite the variety of therapeutic options available for patients, further randomized trials are required to conclude whether these treatments reduce the intensity of neuropathic pain in patients with PMPS. In particular, comparative studies and the inclusion of patients across a range of pain intensities will be essential to developing a treatment algorithm for PMPS. In conclusion, current management for these patients should be tailored to their individual requirements.

Technical consideration for breast reconstruction in patients requiring neoadjuvant or adjuvant radiotherapy: a narrative review.

Background and Objective: Surgical considerations for breast reconstruction (BR) in patients requiring neoadjuvant radiotherapy (NART) or adjuvant radiotherapy (ART) cannot be understated. The management of irradiated tissue leads surgeons to face several challenges. Therefore, it is essential to comprehensively understand the proper patient selection and preoperative planning to ensure the best outcomes and minimize the risk of complications. This narrative review aims to provide an update and summary of the most important technical considerations every breast surgeon must contemplate reconstructing the irradiated breast. Methods: The search strategy was performed on January 10th, 2023. The PubMed, Embase, Cochrane Library, and Web of Science databases were queried to capture all publications regarding surgical considerations in BR of patients undergoing NART and ART. Key Content and Findings: This review shows that the effects of radiotherapy (RT) on BR are still being studied. RT represents an essential factor for overall patient survival, and its use is increasing. However, the range of RT treatments across different cancer centers complicates the creation of a single treatment protocol. BR improves women's quality of life, so finding the proper integration of BR and RT is essential. When deciding on the reconstructive method, there are several factors to consider, such as the patient's body characteristics, tumor stage, RT protocol, and chemotherapy. To achieve the best surgical results and the most satisfied patient, using less aggressive and safer RT methods in the treatment sequence is recommended. Conclusions: The timing of the radiation will influence the selection of the best reconstructive methods to be employed in the breast cancer patient. However, there is clear evidence of preference for immediate autologous-based BR in cases due to the low rate of complications in the long term. But patient individualization is the key. Therefore, the benefits and risks of immediate versus delayed and autologous versus implant-based reconstruction must be weighed in every single case.

A Virtual Hybrid Care Hotel Model Supports the Recovery of Post-procedural Patients with Mild to Severe Systemic Diseases.

BACKGROUND: Patients with mild to severe chronic systemic disease undergoing low-risk procedures are often hospitalized for observation. The Care Hotel is a novel virtual medicine hybrid model of care that offers patients a comfortable, out of hospital environment where they can receive both in-person and virtual care after a surgery or procedure. This study aimed to analyze if virtual hybrid post-procedure care in a hotel could be both conducted on and accepted by patients, even those with moderate to severe chronic diseases. METHODS: This retrospective cohort study was conducted between July 23, 2020 and June 4, 2021 at Mayo Clinic in Florida, a 306-bed community academic hospital. We collected the sex, age, race, ethnicity, acceptance rate, ASA score, and primary procedure of patients using the Care Hotel. RESULTS: Out of 392 patients, 272 (69.4%) opted for care in the program. Median patient age was 61.5 years, 59.56% were males, and 86.40% were white. We found that 50.37% had an ASA score of 2 and 43.4% had an ASA score of 3. Ten different surgical specialties were able to utilize the Care Hotel for care in 47 different procedure types. Urology had the most patients (n=70, 25.7%). Post-electrophysiologic procedures were the most common procedures (n=39, 14.3%). CONCLUSION: Our virtual hybrid Care Hotel program was widely accepted by patients and could care for a multitude of post-operative procedures. Additionally, this novel program can care for patients with both mild and severe systemic diseases.

Treatment of a high healthcare utilizer with sepsis in a virtual hybrid hospital-at-home program.

High healthcare utilizers are often chronically ill patients who require aggressive hospital and outpatient care. We describe a patient with septic shock who was stabilized in the intensive care unit, then transitioned to a virtual hybrid hospital-at-home to complete both inpatient care as well as outpatient wound and rehabilitation therapy.