Military medicine
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Pneumothorax (PTX) incidence in patients arriving to a trauma center can be as high as 20%. The severity of PTX can range from insignificant to life-threatening. Five percent of combat casualties sustaining thoracic trauma have tension PTX (tPTX) at the time of death. Rapid diagnosis and decompression, traditionally with a needle decompression in the prehospital setting, is essential. However, high iatrogenic injury rates reveal a need for a device with the potential to decrease injury rate without compromising decompression success. The Donaldson Decompression Needle (DDN) is a 10-gauge × 3.25 inch needle with a locking mechanism designed to prevent over-insertion. During insertion, a spring-loaded blunt tip retracts, releasing the lock. After penetration of the parietal pleura, the blunt tip projects forward, which in turn locks the device in place on the chest. The device also contains an integrated 1-way valve (OWV) to prevent causing iatrogenic PTX, if placed into a healthy lung cavity. ⋯ Despite the similar length and gauge of the DDN compared to the standard of care (SOC), the success rate of thoracic decompression was lower for the DDN when compared to the SOC (46% vs. 87%, P = .077) although statistical noninferiority was not established. Additionally, intradevice comparisons indicated decompression with the OWV on significantly prolonged decompression time when compared to when it was removed. It could be appropriate to consider removing the OWV after placement to decrease the decompression time, followed by reattachment for transport. Further research into the ability of the DDN to decrease iatrogenic injury will follow validation of decompression capabilities.
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A comparison of body composition assessments using military circumferences to bioelectrical impedance analysis (BIA) and the reference standard dual-energy X-ray absorptiometry (DEXA) can gauge effectiveness of assessments. High-frequency (500 KHz) direct segmental multifrequency bioelectrical impedance analysis (DSM-BIA) accurately calculates total water mass and body fat% (BF%), but it is unknown whether higher frequencies (1,000 KHz) increase measurement accuracy. The purpose was to compare DSM-BIA 500, DSM-BIA 1000, the DoD Circumference Method (CM), and the reference-standard DEXA. ⋯ This study found that CM BF% was moderately correlated with DSM-BIA 500 kHz, DSM-BIA 1,000 kHz BIA, and DEXA. Both DSM-BIA 500 and DSM-BIA 1,000 kHz strongly correlated well with DEXA implying that there was no further increase in correlation with increased frequency. Additionally, there was proportional bias in BF% in the female group between CM and DEXA and in the total group between CM and DSM BIA 1000.
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The prevalence of treatment-resistant depression within global and military populations highlights the need for novel treatment approaches beyond monoamine neurotransmitter modulators. Buprenorphine (BUP), a semi-synthetic partial opioid agonist, is approved for the treatment of opioid use disorder and has shown promise in treating both depression and chronic pain. ⋯ An unexpected finding was the discontinuation of prescribed hydromorphone for pain, suggesting the potential unique benefit of BUP in treating chronic pain and treatment resistant depression comorbidities. These findings implicate the diverse beneficial potential of BUP in psychiatric treatments for military populations.
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The Military Health System (MHS) has historically been at the forefront of innovation in medicine and science, but it has also historically struggled to implement battlefield innovations or civilian technologies for wider domestic use. Artificial intelligence (AI) has emerged as a transformative force in health care with civilian health systems and institutions at the forefront of these innovations. While these tools have the potential to support resolution of military health's most pressing issues, the MHS is behind its civilian counterparts in advancing AI. ⋯ To address these, the MHS should engage in three lines of effort to advance AI: establishing governance, education and training of medical personnel, and engaging in research, development, testing, and piloting of AI applications. This will require dedicated personnel and resources for a substantial initial outlay to be recouped later through more effective administration and care. By leveraging lessons learned from civilian systems, the MHS can design, adopt, and implement AI solutions to improve care for service members in both domestic and operational contexts, and for their beneficiaries.