Major Lower Limb Amputations and Amputees in an Aging Population in Southwest Finland 2007-2017

Purpose

The aim of the present study was to describe and analyze changes in the incidences of lower extremity amputations (LEAs), patient characteristics, vascular history of amputees and survival in Southwest Finland.

Patients and Methods

This is a retrospective patient study in the Hospital District of Southwest Finland. All consecutive patients with atherosclerosis and diabetes-caused LEA, between 1st January 2007 and 31st December 2017, were included. The annual incidences of major LEA patients were statistically standardized. Patients' diagnoses, functional status, previous revascularizations and minor amputations were recorded, and survival was analyzed.

Results

During the 11-year-period major LEAs were performed on 891 patients, 118 (13.2%) were urgent operations. The overall incidence of major LEA was 17.2/100 000 and was age-dependent (3.1 for ≤64 years, 34.3 for 65-74 years, 81.5 for 75-84 years, 216 for ≥85 years). A decrease in incidence was detected in the <65 year-age-group (incidence 4.98 in 2007 and 1.88 in 2017; p = 0.0018). Among older age groups, there was no significant change. Half (50.6%) of all amputees were diabetics. Altogether, 472 patients (53.0%) had a history of revascularization before LEA. 80.1% of index amputations were transfemoral and 19.9% transtibial. Re-surgery was performed on 94 (10.5%) patients. The 1-, 3- and 5-year overall survival were 56%, 30%, and 18%, respectively.

Conclusion

Our results suggest that in an aging population, despite good availability of vascular services, a significant number of patients are not fit for active revascularization, and LEA is the only feasible treatment for critical limb ischemia.

Alcohol intoxication and lack of helmet use are common in electric scooter-related traumatic brain injuries: a consecutive patient series from a tertiary university hospital

PURPOSE

Clinicians have increasingly encountered traumatic brain injuries (TBI) related to electric scooter (ES) accidents. In this study, we aim to identify the modifiable risk factors for ES-related TBIs.

METHODS

A retrospective cohort of consecutive patients treated for ES-related traumatic brain injuries in a tertiary university hospital between May 2019 and September 2021 was identified and employed for the study. The characteristics of the accidents along with the clinical and imaging findings of the injuries were collected from the patient charts.

RESULTS

During the study period, 104 TBIs related to ES accidents were identified. There was a high occurrence of accidents late at night and on Saturdays. In four cases, the patient's helmet use was mentioned (3.8%). Seventy-four patients (71%) were intoxicated. At the scene of the accident, seventy-seven (74%) of the patients had a Glasgow Coma Scale score of 13-15, three patients (3%) had a score of 9-12, and two patients (2%) had a score of 3-8. The majority (83%) of TBIs were diagnosed as concussions. Eighteen patients had evidence of intracranial injuries in the imagining. Two patients required neurosurgical procedures. The estimated population standardized incidence increased from 7.0/100,000 (95% CI 3.5-11/100,000) in 2019 to 27/100,000 (95% CI 20-34/100,000) in 2021.

CONCLUSIONS

Alcohol intoxication and the lack of a helmet were common in TBIs caused by ES accidents. Most of the accidents occurred late at night. Targeting these modifiable factors could decrease the incidence of ES-related TBIs.

CHRONIC LIMB THREATENING ISCHEMIA AND DIABETES MELLITUS: THE SEVERITY OF TIBIAL ATHEROSCLEROSIS AND OUTCOME AFTER INFRAPOPLITEAL REVASCULARIZATION

Background and objective:

Diabetes mellitus associates with poor outcomes in chronic limb threatening ischemia but data on different hypoglycemic regimens and outcomes are lacking. We analyzed insulin-treated diabetes mellitus, non-insulin-treated diabetes mellitus, and patients without diabetes mellitus.

Methods:

All patients with peripheral artery disease and/or diabetes mellitus and infrapopliteal revascularization in the Department of Vascular Surgery, Turku University Hospital during 2007–2015 were included. Tibial atherosclerosis was categorized into crural index classes of I–IV.

Results:

Of the 497 patients, 180 were insulin-treated diabetes mellitus, 94 non-insulin-treated diabetes mellitus, and 223 patients without diabetes mellitus groups (diabetes mellitus 55.1%). Insulin-treated diabetes mellitus was the most ill, youngest (insulin-treated diabetes mellitus—median: 72.4, interquartile range: 64.0–79.5 versus non-insulin-treated diabetes mellitus—76.0, interquartile range: 67.9–83.6 versus patients without diabetes mellitus—77.3, interquartile range: 68.5–83.7, p < 0.001), had the highest body mass index (insulin-treated diabetes mellitus—median: 27.7, interquartile range: 24.0–31.8 versus non-insulin-treated diabetes mellitus—26.3, interquartile range: 23.2–30.3 versus patients without diabetes mellitus—23.9, interquartile range: 21.5–26.9, p < 0.001), and Charlson comorbidity index (insulin-treated diabetes mellitus—65.6% versus non-insulin-treated diabetes mellitus—46.8% versus patients without diabetes mellitus—10.8%, p < 0.001). After endovascular revascularization, limb salvage was poorer for insulin-treated diabetes mellitus (p = 0.046) and non-insulin-treated diabetes mellitus groups (p = 0.011) compared to surgery, but not for patients without diabetes mellitus (p = 0.15). Patients with crural index IV in insulin-treated diabetes mellitus (p = 0.001) and non-insulin-treated diabetes mellitus (p = 0.013) had higher mortality after revascularization. Crural index IV was a risk factor for limb loss (hazard ratio: 1.37, 95% confidence interval: 1.08–1.74, p = 0.008).

Conclusions:

Limb salvage after bypass is better for insulin and non-insulin diabetics, compared to the endovascular approach. Extensive tibial atherosclerosis is an independent risk factor for limb loss. It associates with increased mortality in both insulin and non-insulin diabetics.

Effects of heavy metal pollution on red wood ant (Formica s. str.) populations

We studied the species composition, mound population densities, relative abundance and colony sizes of red wood ants along a well known air pollution gradient of a copper smelter in Southwest Finland. The dominant species, Formica aquilonia, was further studied for heavy metal (Al, Cu, Cd, Ni, Zn, As, Pb, Hg) levels and morphological characters (body mass, head width, labial gland disease) of workers. We found five species belonging to Formica s. str., and two of them showed changes in their relative abundance, which could not be explained by natural habitat differences. Nest mound volumes were 34% smaller in the polluted area, suggesting that smaller colonies can be maintained there. The heavy metal levels in F. aquilonia workers were higher in the polluted area for all metals, except Hg. The largest relative differences between the study areas (polluted/unpolluted) were found for As (4.1), Ni (2.4), Cu (2.1) and Pb (1.8). Morphological characters of workers were not related to the heavy metal levels. Our data showed that red wood ants can tolerate relatively high amounts of heavy metals and maintain reproducing colonies even in a heavily polluted area, but on the basis of smaller colony sizes, pollution stress may also cause trade-offs in reproduction.

Adaptive algorithm for blind separation from noisy time-varying mixtures

This article addresses the problem of blind source separation from time-varying noisy mixtures using a state variable model and recursive estimation. An estimate of each source signal is produced real time at the arrival of new observed mixture vector. The goal is to perform the separation and attenuate noise simultaneously, as well as to adapt to changes that occur in the mixing system. The observed data are projected along the eigenvectors in signal subspace. The subspace is tracked real time. Source signals are modeled using low-order AR (autoregressive) models, and noise is attenuated by trading off between the model and the information provided by measurements. The type of zero-memory nonlinearity needed in separation is determined on-line. Predictor-corrector filter structures are proposed, and their performance is investigated in simulation using biomedical and communications signals at different noise levels and a time-varying mixing system. In quantitative comparison to other widely used methods, significant improvement in output signal-to-noise ratio is achieved.

Nonlinear filtering of multivariate images under robust error criterion

A class of nonlinear filters for multivariate data is introduced. A robust error criterion is minimized. Approximate algorithms for computing the filter output are developed. A polynomial signal model is used in applications where the signal amplitude has to be retained with high fidelity. Simulated data and RGB color image data are used in experiments.

A robust nonlinear filter for image restoration

A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.