Impact of pelvic fractures on the early clinical outcomes of severely injured trauma patients

BACKGROUND

Pelvic fractures contribute to morbidity and mortality following injury. We sought to study the impact of pelvic fractures on the clinical course and outcomes of trauma patients with a pelvic fracture in comparison to patients with similar injury severity without pelvic fracture to identify potential parameters to track patients' clinical course post-injury.

METHODS

A cohort of 206 consecutive blunt trauma survivors, studied over a 5-year period in a level I trauma center of which 75 patients (36.4%) had a pelvic fracture, was included in the study. To perform a retrospective cohort study with matched controls, 60 patients of the pelvic fracture group [(PF), 41 males and 19 females; age: 40 ± 17; injury severity score (ISS): 26.6 ± 9.3] were compared to 60 patients without pelvic fracture (non-PF) trauma as controls (41 males and 19 females; age: 40 ± 13; ISS: 26.9 ± 7.7), both with matching age (±5 years), sex, and ISS (±5 points).

RESULTS

Statistically significant differences were observed in Intensive Care Unit (ICU) length of stay (LOS), total LOS, and Marshall MOD score between PF and non-PF groups, respectively. Acid-base markers such as pH, lactate, LDH, and base deficit were all significantly altered in PF compared to non-PF cohort upon admission. Moreover, our analysis showed significant differences in inflammatory biomarkers (Prolactin, CRP, and IL-6), and clinical parameters (CPK, Hgb, Platelets count, and WBC) over the 7-day clinical course in patients with PF when compared to non-PF cohort.

CONCLUSION

In this matched cohort, patients with pelvic fractures exhibited biochemical and physiological alterations upon admission. Furthermore, our results suggest that pelvic fracture affects the clinical outcomes in severely injured patients, independently of injury severity, mechanism of injury, age or gender.

Management of extrapulmonary sarcoidosis: challenges and solutions

Background

Sarcoidosis is a chronic multisystem disease of unknown etiology characterized by noncaseating granulomas that most often involves the lungs, but frequently has extrapulmonary manifestations, which might be difficult to treat in individual patients.

Objective

To review different disease manifestations, focusing on extrapulmonary organ systems, and to provide treatment options for refractory cases.

Materials and methods

We performed a literature search using Medline and Google Scholar for individual or combined keywords of “sarcoidosis, extrapulmonary, treatment, kidney, neurosarcoidosis, cardiovascular, gastrointestinal, transplantation, musculoskeletal, rheumatology, arthritis, and skin”. Peer-reviewed articles, including review articles, clinical trials, observational trials, and case reports that were published in English were included. References from retrieved articles were also manually searched for relevant articles.

Results and conclusion

Isolated involvement of a single organ or organ system is rare in sarcoidosis, and thus all patients must be thoroughly evaluated for additional disease manifestations. Cardiac sarcoidosis and neurosarcoidosis may be life-threatening. Clinicians need to assess patients comprehensively using clinical, laboratory, imaging, and histopathological data to recommend competently the best and least toxic treatment option for the individual patient.

Automated tracing and change analysis of angiogenic vasculature from in vivo multiphoton confocal image time series

Automated methods are described for tracing and analysis of changes in angiogenic vasculature imaged by a multiphoton laser-scanning confocal microscope. Utilizing chronic animal window models, time series of in vivo 3-D images were acquired on approximately the same target volume of the same specimen while undergoing angiogenic change (typically every 24 h for 7 days). Objective, precise, 3-D, rapid, and fully automated vessel morphometry was performed using an adaptive tracing algorithm that is based on a generalized irregular cylinder model of the vasculature. This algorithm was found to be not only adaptive enough for tracing angiogenic vasculature, but also very efficient in its use of computer memory, and fast, taking less than 1 min to trace a 768 x 512 x 32, 8-bit/pixel 3-D image stack on a Dell Pentium III 1-GHz computer. The automatically traced centerlines were manually validated on six image stacks and the average spatial error was measured to be 2 pixels, with an average concordance of 81% between manual and automated traces on a voxel basis. The tracing output includes geometrical statistics of traced vasculature and serves as the basis of statistical change analysis. The computer methods described here are designed to be scalable to much larger hypothesis testing studies involving quantitative measurements of tumor angiogenesis, gene expression relative to known vascular structures, and impact of drug delivery.