Clinical Characteristics and Outcomes of Non-ICU Hospitalization for COVID-19 in a Nonepicenter, Centrally Monitored Healthcare System.

BACKGROUND: The clinical characteristics and outcomes associated with non-intensive care unit (non-ICU) hospitalizations for coronavirus disease 2019 (COVID-19) outside disease epicenters remain poorly characterized. METHODS: Systematic analysis of all non-ICU patient hospitalizations for COVID-19 completing discharge between March 13 and May 1, 2020, in a large US health care system utilizing off-site central monitoring. Variables of interest were examined in relation to a composite event rate of death, ICU transfer, or increased oxygen requirement to high-flow nasal cannula, noninvasive ventilation, or mechanical ventilation. RESULTS: Among 350 patients (age, 64 ± 16 years; 55% male), most (73%) required 3 L/min or less of supplemental oxygen during admission. Telemetry was widely utilized (79%) yet arrhythmias were uncommon (14%) and were predominantly (90%) among patients with abnormal troponin levels or known cardiovascular disease. Ventricular tachycardia was rare (5%), nonsustained, and not associated with hydroxychloroquine/azithromycin treatment. Adverse events occurred in 62 patients (18%), including 22 deaths (6%), 48 ICU transfers (14%), and 49 patients with increased oxygen requirement (14%) and were independently associated with elevated C-reactive protein (odds ratio, 1.09 per 1 mg/dL; 95% CI, 1.01-1.18; P = .04) and lactate dehydrogenase (OR, 1.006 per 1U/L; 95% CI, 1.001-1.012; P = .03) in multivariable analysis. CONCLUSION: Among non-critically ill patients hospitalized within a nonepicenter health care system, overall survival was 94% with the development of more severe illness or death independently associated with higher levels of C-reactive protein and lactate dehydrogenase on admission. Clinical decompensation was largely respiratory-related, while serious cardiac arrhythmias were rare, which suggests that telemetry can be prioritized for high-risk patients.

Indication-specific event rates among hospitalized patients undergoing continuous cardiac monitoring.

BACKGROUND: Cardiac telemetry monitoring is widely utilized for a variety of clinical indications, yet indication-specific event rates for monitored patients are seldomly reported. HYPOTHESIS: High-risk hospitalized patients for clinical deterioration can be identified using standardized telemetry monitoring indications. METHODS: Adjudicated data from events triggering emergency response team (ERT) activation were systematically characterized at the Cleveland Clinic from among standardized telemetry indications ordered over a 13-month period. RESULTS: Among 72 199 orders created for telemetry monitored patients, ERT activation occurred in 2677 patients (3.7%), of which 1326 (49.5%) were cardiac-related. Patients with deep venous thrombosis or pulmonary embolism (DVT/PE) demonstrated the highest overall event rate (ERT: n = 41 of 593 pts [6.9%]; 25/41 cardiac related [61%]). Cardiac-related events were proportionally highest among patients with coronary disease awaiting revascularization (ERT: n = 19 of 847 patients [2.2%]; 13/19 cardiac-related [68.4%]). Arrhythmia-specific events were highest among patients who underwent cardiac surgery (n = 78 of 193 cardiac-related ERT [40.4%]), and patients with known or suspected tachyarrhythmias (n = 318 of 788 cardiac-related ERT [40.4%]). Bubble plot analysis identified patients hospitalized with DVT/PE, drug or alcohol exposures, and acute coronary syndrome as among the highest overall and cardiac-related events while identifying patients with respiratory disorder monitoring indications as carrying the highest noncardiac event rate. CONCLUSION: High-risk hospitalized patients can be identified by telemetry indication and prioritized according to concerns for cardiac, arrhythmia-specific and noncardiac clinical deterioration. This is particularly useful when monitored bed resources are constrained.

Optimization of nonlinear hyperelastic coefficients for foot tissues using a magnetic resonance imaging deformation experiment.

Accurate prediction of plantar shear stress and internal stress in the soft tissue layers of the foot using finite element models would provide valuable insight into the mechanical etiology of neuropathic foot ulcers. Accurate prediction of the internal stress distribution using finite element models requires that realistic descriptions of the material properties of the soft tissues are incorporated into the model. Our investigation focused on the creation of a novel three-dimensional (3D) finite element model of the forefoot with multiple soft tissue layers (skin, fat pad, and muscle) and the development of an inverse finite element procedure that would allow for the optimization of the nonlinear elastic coefficients used to define the material properties of the skin muscle and fat pad tissue layers of the forefoot based on a Ogden hyperelastic constitutive model. Optimization was achieved by comparing deformations predicted by finite element models to those measured during an experiment in which magnetic resonance imaging (MRI) images were acquired while the plantar surface forefoot was compressed. The optimization procedure was performed for both a model incorporating all three soft tissue layers and one in which all soft tissue layers were modeled as a single layer. The results indicated that the inclusion of multiple tissue layers affected the deformation and stresses predicted by the model. Sensitivity analysis performed on the optimized coefficients indicated that small changes in the coefficient values (±10%) can have rather large impacts on the predicted nominal strain (differences up to 14%) in a given tissue layer.

An MRI-compatible foot-loading device for assessment of internal tissue deformation.

It is well known that mechanical forces acting within the soft tissues of the foot can contribute to the formation of neuropathic ulcers in people with diabetes. Presently, only surface measurements of plantar pressure are used clinically to estimate risk status due to mechanical loading. It is currently not known how surface measurements relate to the three-dimensional (3-D) internal stress/strain state of the foot. This article describes the development of a foot-loading device that allows for the direct observation of the internal deformation of foot tissues under known forces. Ground reaction forces and plantar pressure distributions during normal walking were measured in ten healthy young adults. One instant in the gait cycle, when pressure under the metatarsal heads reached a peak, was extracted for simulation in an MR imager. T1-weighted 3-D gradient echo MRI sets were collected as the simulated walking ground reaction force was incrementally applied to the foot by the novel foot-loading device. The sub-metatarsal head soft-tissue thickness decreased rapidly at first and then reached a plateau. Peak plantar pressure measurements collected within the loading device (161+/-75kPa) were lower in magnitude and less focal than pressures measured during walking (492+/-91kPa). This finding implies that although the device successfully applied full peak walking ground reaction forces to the foot, they were not distributed in the same manner as during walking. Although not representative of gait, the data collected from this in vivo mechanical test are suitable for determination of foot tissue material properties or, when combined with finite element modeling, to examine the relationship between surface loading and internal stress.

Finite element modeling of the first ray of the foot: a tool for the design of interventions.

Disorders of the first ray of the foot (defined as the hard and soft tissues of the first metatarsal, the sesamoids, and the phalanges of the great toe) are common, and therapeutic interventions to address these problems range from alterations in footwear to orthopedic surgery. Experimental verification of these procedures is often lacking, and thus, a computational modeling approach could provide a means to explore different interventional strategies. A three-dimensional finite element model of the first ray was developed for this purpose. A hexahedral mesh was constructed from magnetic resonance images of the right foot of a male subject. The soft tissue was assumed to be incompressible and hyperelastic, and the bones were modeled as rigid. Contact with friction between the foot and the floor or footwear was defined, and forces were applied to the base of the first metatarsal. Vertical force was extracted from experimental data, and a posterior force of 0.18 times the vertical force was assumed to represent loading at peak forefoot force in the late-stance phase of walking. The orientation of the model and joint configuration at that instant were obtained by minimizing the difference between model predicted and experimentally measured barefoot plantar pressures. The model were then oriented in a series of postures representative of push-off, and forces and joint moments were decreased to zero simultaneously. The pressure distribution underneath the first ray was obtained for each posture to illustrate changes under three case studies representing hallux limitus, surgical arthrodesis of the first ray, and a footwear intervention. Hallux limitus simulations showed that restriction of metatarsophalangeal joint dorsiflexion was directly related to increase and early occurrence of hallux pressures with severe immobility increasing the hallux pressures by as much as 223%. Modeling arthrodesis illustrated elevated hallux pressures when compared to barefoot and was dependent on fixation angles. One degree change in dorsiflexion and valgus fixation angles introduced approximate changes in peak hallux pressure by 95 and 22 kPa, respectively. Footwear simulations using flat insoles showed that using the given set of materials, reductions of at least 18% and 43% under metatarsal head and hallux, respectively, were possible.

Reduction of plantar heel pressures: Insole design using finite element analysis.

Plantar heel pain is a common condition that is often exacerbated by the repetitive stresses of walking. Treatment usually includes an in-shoe intervention designed to reduce plantar pressure under the heel by using insoles and a variety of off-the-shelf products. The design process for these products is often intuitive in nature and does not always rely on scientifically derived guidelines. Finite element analysis provides an efficient computational framework to investigate the performance of a large number of designs for optimal plantar pressure reduction. In this study, we used two-dimensional plane strain finite element modeling to investigate 27 insole designs. Combinations of three insole conformity levels (flat, half conforming, full conforming), three insole thickness values (6.3, 9.5 and 12.7 mm) and three insole materials (Poron Cushioning, Microcel Puff Lite and Microcel Puff) were simulated during the early support phase of gait. Plantar pressures predicted by the model were validated by experimental trials conducted in the same subject whose heel was modeled by loading the bare foot on a rigid surface and on foam mats. Conformity of the insole was the most important design variable, whereas peak pressures were relatively insensitive to insole material selection. The model predicted a 24% relief in pressure compared to barefoot conditions when using flat insoles; the reduction increased up to 44% for full conforming insoles.