Citations

In 2020, Mayo Clinic established an Advanced Care at Home (ACH) program. ACH is a virtual hybrid hospital-at-home (HaH) program that combines telemedicine with in-home care services by utilizing a state that is software-driven, vendor-mediate medical supply chain. The program initially focused on acute medical diagnosis but has expanded to oversee surgical and postsurgical patients with continued inpatient needs. Here, we report the first case of a small bowel obstruction (SBO) managed under a HaH program. A 52-year-old lady presented to the emergency department with symptoms suggestive of mechanical SBO. The diagnosis was confirmed with an abdominopelvic computed tomography (CT) scan, and the patient was admitted to the hospital. Based on the patient’s presentation and laboratory results, the care team proceeded with conservative treatment including nasogastric tube (NG) placement and suctioning, intravenous (IV) fluid replacement, and daily laboratory studies. She spent the first hospital day in the physical hospital ward so that the surgical team could ensure stability clinically and no urgent need for surgical intervention. On hospital day two, she was transferred home with ACH where the NG suctioning and IV replacement therapy could continue, while the medical team conducted daily virtual visits to ensure continued improvement. Additionally, a paramedic and a nurse performed an in-person, head-to-toe assessment and administered medications to the patient twice daily. She spent 5 days in ACH getting acute care and then was discharged into a postacute phase equivalent to outpatient monitoring called the restorative phase. She was monitored remotely for the duration of the restorative phase for 10 more days, and then she recovered fully. This case highlights that high-acuity patients with SBO can receive invasive treatments like NG tube suction as well as be appropriately monitored for clinical decompensation by a virtual hybrid home hospital program which combines virtual care providers with an in-home vendor-mediated supply chain.

Upper and lower limb amputations are frequently associated with phantom limb pain (PLP). Recently, virtual reality (VR) and augmented reality (AR) have been reported as a potential therapy of PLP. We have conducted a systematic review of literature to evaluate the efficacy of VR and AR in managing PLP. Four databases were searched: PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, and Web of Science. We utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for our organization. The initial search resulted in 164 results. After title, abstract, and full-text screening, 9 studies were included. One study was of good quality and 8 studies were of fair to poor quality. Seven studies utilized VR and 2 studies utilized AR. The number of treatment sessions ranged from 1 to 28 and the duration ranged from 10 minutes to 2 hours. Several pain scales were used to evaluate PLP pre- and postintervention including Numeric Rating Scale, Pain Rating Index, McGill Pain Questionnaire, and Visual Analog Scale. All the studies reported improvement of PLP on one or more of pain scales after one or more sessions of VR or AR. Despite the promising results reported by literature, we cannot recommend using VR or AR for PLP. Most of the studies are of poor design and have limited sample size with high bias levels. Therefore, no substantial evidence can be derived from them. However, we do believe further research with high-quality randomized controlled trials should take place to increase the knowledge of the potential advantages.

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 potentials 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, 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 to SLNB requires more substantial evidence from large randomized trials.

An 85-year-old male presented to the podiatry clinic following a 1st to 5th left toe amputation as a complication of severe peripheral arterial disease and nonhealing wound despite endovascular intervention with an angiogram. At the visit, cellulitis with gangrene of the surgical site was noted. The patient was admitted to the brick and mortar (BAM) hospital and taken to surgery for a transmetatarsal amputation of the left limb. In the immediate postoperative period, the incisional margins appeared dusky creating concern for flap viability. The medical team recommended a vascular bypass versus a below-knee amputation. However, given the age, comorbidities, and nutritional status, the family refused further surgical intervention. As such, Mayo Clinic’s home hospital program, Advanced Care at Home (ACH), was consulted for continued nonsurgical acute management at home. The patient was transferred to ACH and transported home three days after BAM admission to continue IV antibiotic therapy and wound care. Discharge from ACH occurred 11 days after admission to the BAM hospital. This case highlights the importance of developing health care alternatives to traditional hospitalization and demonstrates that ACH can manage highly complex, elder postoperative patients from the comfort of their homes.