The association between vital signs and clinical outcomes in emergency department patients of different age categories

BACKGROUND

Appropriate interpretation of vital signs is essential for risk stratification in the emergency department (ED) but may change with advancing age. In several guidelines, risk scores such as the Systemic Inflammatory Response Syndrome (SIRS) and Quick Sequential Organ Failure Assessment (qSOFA) scores, commonly used in emergency medicine practice (as well as critical care) specify a single cut-off or threshold for each of the commonly measured vital signs. Although a single cut-off may be convenient, it is unknown whether a single cut-off for vital signs truly exists and if the association between vital signs and in-hospital mortality differs per age-category.

AIMS

To assess the association between initial vital signs and case-mix adjusted in-hospital mortality in different age categories.

METHODS

Observational multicentre cohort study using the Netherlands Emergency Department Evaluation Database (NEED) in which consecutive ED patients ≥18 years were included between 1 January 2017 and 12 January 2020. The association between vital signs and case-mix adjusted mortality were assessed in three age categories (18-65; 66-80; >80 years) using multivariable logistic regression. Vital signs were each divided into five to six categories, for example, systolic blood pressure (SBP) categories (≤80, 81-100, 101-120, 121-140, >140 mm Hg).

RESULTS

We included 101 416 patients of whom 2374 (2.3%) died. Adjusted ORs for mortality increased gradually with decreasing SBP and decreasing peripheral oxygen saturation (SpO₂). Diastolic blood pressure (DBP), mean arterial pressure (MAP) and heart rate (HR) had quasi-U-shaped associations with mortality. Mortality did not increase for temperatures anywhere in the range between 35.5°C and 42.0°C, with a single cut-off around 35.5°C below which mortality increased. Single cut-offs were also found for MAP <70 mm Hg and respiratory rate >22/min. For all vital signs, older patients had larger increases in absolute mortality compared with younger patients.

CONCLUSION

For SBP, DBP, SpO₂ and HR, no single cut-off existed. The impact of changing vital sign categories on prognosis was larger in older patients. Our results have implications for the interpretation of vital signs in existing risk stratification tools and acute care guidelines.

Reducing arthroplasty costs via vendor contracts

OBJECTIVE

To describe a method of reducing the costs of implants in hip and knee arthroplasty.

DESIGN

Implant costs were compared before and after the implementation of a 2-year contract with implant vendors, providing increased volume for decreased implant cost. An additional 20% of arthroplasties could be done outside the contract for research or special purposes.

SETTING

A regional health authority involving 2 acute care hospitals.

METHOD

Costs were obtained for 942 hip and knee arthroplasties performed in 1993/94 and compared with costs of 1656 hip and knee arthroplasties performed in 1996/97.

OUTCOME MEASURES

Implant cost and number of joint arthroplasty procedures performed.

RESULTS

A 40% decrease in the cost per implant for primary knee arthroplasty and an 18% decrease in the cost per implant for primary hip arthroplasty were achieved. A rebate, calculated as a percentage of volume used, was received from the vendor to support general orthopedic research and education. A new contract for 3 years has recently been signed with 3 vendors designated as primary vendors for 80% of the volume.

CONCLUSION

The vendor-contract economic strategy effectively reduced the cost of hip and knee arthroplasty and may be useful at other centres looking for cost reduction methods that maintain adequate patient care and support clinical research and education.

Artificial neural networks: application to electrical stimulation of the human nervous system

Artificial neural networks are used increasingly in applications such as graphic pattern recognition, which are difficult to address with conventional statistical methods. In the management of chronic pain, graphic methods are used routinely; patients describe their patterns of pain using “pain drawings.” The authors have previously reported an automated, computerized pain drawing methodology, which has been used by patients with implanted spinal cord stimulators to represent a technical goal of the procedure, the overlap of pain by stimulation paresthesias. Standard linear discriminant statistical methods have shown associations between stimulation parameters and electrode positions as independent variables and technical outcome and relief of pain as dependent variables.

The authors have applied artificial neural networks to the problem of optimizing implanted stimulator adjustment. A data set of 3000 electrode combinations obtained in 41 patients was used to develop a linear discriminant statistical model on a mainframe computer and to train artificial neural networks on a personal computer. The performance of these two systems on a new data set obtained in 10 patients was compared with that of human “experts.” The best neural network model was marginally better than the linear discriminant model; the variance in patient ratings was predicted by these models to a degree that the human experts were unable to predict. The authors anticipate expanding the role of these models and incorporating them into expert sytems for clinical use.