Eldaly, Abdullah

AbstractBackgroundAortic stenosis (AS) is associated with myocardial ischemia through different mechanisms and may impair coronary arterial flow. However, data on the impact of moderate AS in patients with acute myocardial infarction (MI) is limited.AimsThis study aimed to investigate the impact of moderate AS in patients presenting with acute myocardial infarction (MI).MethodsWe conducted a retrospective analysis of all patients who presented with acute MI to all Mayo Clinic hospitals, using the Enterprise Mayo PCI Database from 2005 to 2016. Patients were stratified into two groups: moderate AS and mild/no AS. The primary outcome was all cause mortality.ResultsThe moderate AS group included 183 (13.3%) patients, and the mild/no AS group included 1190 (86.7%) patients. During hospitalization, there was no difference between both groups in mortality. Patients with moderate AS had higher in‐hospital congestive heart failure (CHF) (8.2% vs. 4.4%, p = 0.025) compared with mild/no AS patients. At 1‐year follow‐up, patients with moderate AS had higher mortality (23.9% vs. 8.1%, p < 0.001) and higher CHF hospitalization (8.3% vs. 3.7%, p = 0.028). In multivariate analysis, moderate AS was associated with higher mortality at 1‐year (odds ratio 2.4, 95% confidence interval [1.4–4.1], p = 0.002). In subgroup analyses, moderate AS increased all‐cause mortality in STEMI and NSTEMI patients.ConclusionThe presence of moderate AS in acute MI patients was associated with worse clinical outcomes during hospitalization and at 1‐year follow‐up. These unfavorable outcomes highlight the need for a close follow‐up of these patients and for timely therapeutic strategies to best manage these coexisting conditions.

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.

Chronically ill patients with superimposed acute illness requiring hospitalization are more likely to develop an extended length of stay, hospital-acquired infections, and adverse events throughout their hospitalization. An excellent alternative to managing this population of patients in the traditional bricks-and-mortal (BAM) hospital is the hospital-at-home (HaH) model. The Advanced Care at Home (ACH) program is Mayo Clinic’s HaH model that provides acute and postacute care to high-acuity patients in their homes rather than in the traditional hospital and skilled nursing facility. We report a case of postoperative care through the ACH program of a patient suffering from short gut syndrome, high-output ileostomy, and severe protein-calorie malnutrition in the setting of previously diagnosed triple-negative invasive ductal carcinoma (IDC) of the right breast complicated by lung and brain metastasis. The patient had multiple complications that required repeated scare escalations directed by a multidisciplinary virtual care. Despite these complications, the ACH model of care was able to keep the patient in the home setting the majority of the time, limiting BAM hospital days, and eliminating the need to use the emergency department for acute escalation for 3 months. The patient was able to recover during this time period and proceed to successful take-down of the ileostomy. This case highlights the benefits of the ACH program by offering high-acuity hospital-level care to severely ill patients in the comfort of their homes. Highly qualified providers paired with curated technology in the home allowed for prompt identification of patient decompensation and timely initiation of treatment while avoiding institutionalization.

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.