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.

Demographic Characteristics Influence Treatment Costs of Invasive Melanoma in Florida.

BACKGROUND: Demographic characteristics are known to influence the treatment and outcomes of patients with invasive melanoma. Whether these characteristics influence treatment costs is unknown. We aimed to analyze whether patient demographics and tumor characteristics influence treatment costs for patients with invasive cutaneous melanoma in Florida. METHODS: This was a cross-sectional study in which the Florida Inpatient and Outpatient Dataset of the Agency for Health Care Administration was analyzed for patients with a diagnosis of invasive melanoma between January 1, 2013 and December 31, 2018. Categorical variables were assessed using Pearson χ2 tests, and continuous variables were evaluated using Kruskal-Wallis tests. Logistic regression analysis was conducted to identify the association between patient demographics and total costs. All analyses were done using SAS 9.4 statistical software (SAS Institute, Inc). RESULTS: Multivariate analysis showed that sex (P < 0.001), hospital setting (P < 0.001), race/ethnicity (P < 0.01), patient region (P < 0.01), Elixhauser Comorbidity Index score (P < 0.001), presence of metastasis (P < 0.01), total number of procedures (P < 0.001), and length of stay (P < 0.001) were correlated with the cost of treatment of invasive cutaneous melanoma. After stratification, the association between cost and race/ethnicity disappeared for inpatients but remained for Black patients in the outpatient setting (P < 0.001). The association between cost and patient residence regions also differed when the cohort was stratified. CONCLUSIONS: Strategies addressing disparities in treatment cost of invasive melanoma should differ, depending on the hospital setting where the patient is being treated.

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.

Perceived Age in Patients Exposed to Distinct UV Indexes: A Systematic Review.

Photodamage is caused by chronic sun exposure and ultraviolet radiation and presents as wrinkles, sagging, and pigmented spots. An increase in the ultraviolet index can increase a person's perceived age by worsening skin photodamage. However, since the ultraviolet index varies considerably between geographical regions, perceived age might vary substantially among them. This review aims to describe the differences in chronological and perceived age in regions of the world with different ultraviolet indexes. A literature search of three databases was conducted for studies analyzing perceived age and its relationship to sun exposure. Ultraviolet indexes from the included studies were retrieved from the National Weather Service and the Tropospheric Emission Monitoring Internet Service. Out of 104 studies, seven fulfilled the inclusion criteria. Overall, 3,352 patients were evaluated for perceived age. All studies found that patients with the highest daily sun exposures had the highest perceived ages for their chronological age ( p < 0.05). People with high sun exposure behaviors living in regions with high ultraviolet indexes will look significantly older than same-aged peers living in lower ultraviolet index regions.

In Vitro Enhanced Osteogenic Potential of Human Mesenchymal Stem Cells Seeded in a Poly (Lactic-co-Glycolic) Acid Scaffold: A Systematic Review.

Study Design: Human bone marrow stem cells (hBMSCs) and human adipose-derived stem cells (hADSCs) have demonstrated the capability to regenerate bone once they have differentiated into osteoblasts. Objective: This systematic review aimed to evaluate the in vitro osteogenic differentiation potential of these cells when seeded in a poly (lactic-co-glycolic) acid (PLGA) scaffold. Methods: A literature search of 4 databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted in January 2021 for studies evaluating the osteogenic differentiation potential of hBMSCs and hADSCs seeded in a PLGA scaffold. Only in vitro models were included. Studies in languages other than English were excluded. Results: A total of 257 studies were identified after the removal of duplicates. Seven articles fulfilled our inclusion and exclusion criteria. Four of these reviews used hADSCs and three used hBMSCs in the scaffold. Upregulation in osteogenic gene expression was seen in all the cells seeded in a 3-dimensional scaffold compared with 2-dimensional films. High angiogenic gene expression was found in hADSCs. Addition of inorganic material to the scaffold material affected cell performance. Conclusions: Viability, proliferation, and differentiation of cells strongly depend on the environment where they grow. There are several factors that can enhance the differentiation capacity of stem cells. A PLGA scaffold proved to be a biocompatible material capable of boosting the osteogenic differentiation potential and mineralization capacity in hBMSCs and hADSCs.

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 Impact of Digital Health Solutions on Bridging the Health Care Gap in Rural Areas: A Scoping Review.

Digital health tools can improve health care access and outcomes for individuals with limited access to health care, particularly those residing in rural areas. This scoping review examines the existing literature on using digital tools in patients with limited access to health care in rural areas. It assesses their effectiveness in improving health outcomes. The review adopts a comprehensive search strategy to identify relevant studies from electronic databases, and the selected studies are analyzed descriptively. The findings highlight the advantages and barriers of digital health interventions in rural populations. The advantages include increased access to health care practitioners through teleconsultations, improved health care outcomes through remote monitoring, better disease management through mobile health applications and wearable devices, and enhanced access to specialized care and preventive programs. However, limited internet connectivity and a lack of familiarity with digital tools are barriers that must be addressed to ensure equitable access to digital health interventions in rural areas. Overall, digital tools improve health outcomes for individuals with limited health care access in rural areas.

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.

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.

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.

Benefits and Challenges of Remote Patient Monitoring as Perceived by Health Care Practitioners: A Systematic Review.

BACKGROUND: Remote patient monitoring (RPM), or telemonitoring, offers ways for health care practitioners to gather real-time information on the physiological conditions of patients. As telemedicine, and thus telemonitoring, is becoming increasingly relevant in today's society, understanding the practitioners' opinions is crucial. This systematic review evaluates the perspectives and experiences of health care practitioners with telemonitoring technologies. METHODS: A database search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for the selection of articles measuring health care practitioners' perspectives and experiences with RPM technologies published between 2017 and 2021. Only articles written in English were included. No statistical analysis was performed and thus this is a qualitative review. RESULTS: A total of 1605 studies were identified after the initial search. After applying the inclusion and exclusion criteria of this review's authors, 13 articles were included in this review. In all, 2351 practitioners' perspectives and experience utilizing RPM technology in a variety of medical specialties were evaluated through close- and open-ended surveys. Recurring themes emerged for both the benefits and challenges. Common benefits included continuous monitoring of patients to provide prompt care, improvement of patient self-care, efficient communication, increased patient confidence, visualization of health trends, and greater patient education. Challenges comprised increased workload, higher patient anxiety, data inaccuracy, disorienting technology, financial issues, and privacy concerns. CONCLUSION: Health care practitioners generally believe that RPM is feasible for application. Additionally, there is a consensus that telemonitoring strategies will become increasingly relevant. However, there are still drawbacks to the technology that need to be considered.

The Role of Telemedicine in Prehospital Traumatic Hand Injury Evaluation.

Unnecessary ED visits and transfers to hand clinics raise treatment costs and patient burden at trauma centers. In the present COVID-19 pandemic, needless transfers can increase patients' risk of viral exposure. Therefore, this review analyzes different aspects of the remote diagnosis and triage of traumatic hand injuries. The most common file was photography, with the most common devices being cell phone cameras. Treatment, triage, diagnosis, cost, and time outcomes were assessed, showing concordance between teleconsultation and face-to-face patient evaluations. We conclude that photography and video consultations are feasible surrogates for ED visits in patients with traumatic hand injuries. These technologies should be leveraged to decrease treatment costs and potentially decrease the time to definitive treatment after initial evaluation.

Impact of an Acquisition Advanced Practice Provider on Home Hospital Patient Volumes and Length of Stay.

In July 2020, Mayo Clinic introduced a hospital-at-home program, known as Advanced Care at Home (ACH) as an alternate option for clinically stable medical patients requiring hospital-level care. This retrospective cohort study evaluates the impact of the addition of a dedicated ACH patient acquisition Advanced Practice Provider (APP) on average length of stay (ALOS) and the number of patients admitted into the program between in Florida and Wisconsin between 6 July 2020 and 31 January 2022. Patient volumes and ALOS of 755 patients were analyzed between the two sites both before and after a dedicated acquisition APP was added to the Florida site on 1 June 2021. The addition of a dedicated acquisition APP did not affect the length of time a patient was in the emergency department or hospital ward prior to ACH transition (2.91 days [Florida] vs. 2.59 days [Wisconsin], p = 0.22), the transition time between initiation of the ACH consult to patient transfer home (0.85 days [Florida] vs. 1.16 days [Wisconsin], p = 0.28), or the total ALOS (6.63 days [Florida] vs. 6.34 days [Wisconsin], p = 0.47). The average number of patients acquired monthly was significantly increased in Florida (38.3 patients per month) compared with Wisconsin (21.6 patients per month) (p < 0.01). The addition of a dedicated patient acquisition APP resulted in significantly higher patient volumes but did not affect transition time or ALOS. Other hospital-at-home programs may consider the addition of an acquisition APP to maximize patient volumes.

A Review of Voice-Based Pain Detection in Adults Using Artificial Intelligence.

Pain is a complex and subjective experience, and traditional methods of pain assessment can be limited by factors such as self-report bias and observer variability. Voice is frequently used to evaluate pain, occasionally in conjunction with other behaviors such as facial gestures. Compared to facial emotions, there is less available evidence linking pain with voice. This literature review synthesizes the current state of research on the use of voice recognition and voice analysis for pain detection in adults, with a specific focus on the role of artificial intelligence (AI) and machine learning (ML) techniques. We describe the previous works on pain recognition using voice and highlight the different approaches to voice as a tool for pain detection, such as a human effect or biosignal. Overall, studies have shown that AI-based voice analysis can be an effective tool for pain detection in adult patients with various types of pain, including chronic and acute pain. We highlight the high accuracy of the ML-based approaches used in studies and their limitations in terms of generalizability due to factors such as the nature of the pain and patient population characteristics. However, there are still potential challenges, such as the need for large datasets and the risk of bias in training models, which warrant further research.

Artificial Intelligence Models in Health Information Exchange: A Systematic Review of Clinical Implications.

Electronic health record (EHR) systems collate patient data, and the integration and standardization of documents through Health Information Exchange (HIE) play a pivotal role in refining patient management. Although the clinical implications of AI in EHR systems have been extensively analyzed, its application in HIE as a crucial source of patient data is less explored. Addressing this gap, our systematic review delves into utilizing AI models in HIE, gauging their predictive prowess and potential limitations. Employing databases such as Scopus, CINAHL, Google Scholar, PubMed/Medline, and Web of Science and adhering to the PRISMA guidelines, we unearthed 1021 publications. Of these, 11 were shortlisted for the final analysis. A noticeable preference for machine learning models in prognosticating clinical results, notably in oncology and cardiac failures, was evident. The metrics displayed AUC values ranging between 61% and 99.91%. Sensitivity metrics spanned from 12% to 96.50%, specificity from 76.30% to 98.80%, positive predictive values varied from 83.70% to 94.10%, and negative predictive values between 94.10% and 99.10%. Despite variations in specific metrics, AI models drawing on HIE data unfailingly showcased commendable predictive proficiency in clinical verdicts, emphasizing the transformative potential of melding AI with HIE. However, variations in sensitivity highlight underlying challenges. As healthcare's path becomes more enmeshed with AI, a well-rounded, enlightened approach is pivotal to guarantee the delivery of trustworthy and effective AI-augmented healthcare solutions.