Background: The earthquake that struck Haiti on 12 January 2010 caused significant devastation to both the country and the existing healthcare infrastructure in both urban and rural areas. Most hospital and health care facilities in Port-au-Prince and the surrounding areas were significantly damaged or destroyed. Consequently, large groups of Haitians fled Port-au-Prince for rural areas to seek emergency medical and surgical care. In partnership with the Haitian Ministry of Health, Partners in Health (PIH) and Zanmi Lasante (ZL) have developed and maintained a network of regional and district hospitals in rural Haiti for over twenty-five years. This PIH/ZL system was ideally situated to accommodate the increased need for emergent surgical care in the immediate quake aftermath. The goal of the present study was to provide a cross-sectional assessment of surgical need and care delivery across PIH/ZL facilities after the earthquake in Haiti.
Methods: We conducted a retrospective review of hospital case logs and operative records over the course of three weeks immediately following the earthquake.
Results: Roughly 3,000 patients were seen at PIH/ZL sites by a combination of Haitian and international surgical teams. During that period 513 emergency surgical cases were logged. Other than wound debridement, the most commonly performed procedure was fixation of long bone fractures, which constituted approximately one third of all surgical procedures.
Conclusions: There was a significant demand for emergent surgical care after the earthquake in Haiti. The PIH/ZL hospital system played a critical role in addressing this acutely increased burden of surgical disease, and it allowed for large numbers of Haitians to receive needed surgical services. Our experiences reinforce that access to essential surgery is an essential pillar in public health.
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http://dx.doi.org/10.1007/s00268-011-0961-6 | DOI Listing |
Patients with anterior cruciate ligament reconstruction frequently present asymmetries in the sagittal plane dynamics when performing single leg jumps but their assessment is inaccessible to health-care professionals as it requires a complex and expensive system. With the development of deep learning methods for human pose detection, kinematics can be quantified based on a video and this study aimed to investigate whether a relatively simple 2D multibody model could predict relevant dynamic biomarkers based on the kinematics using inverse dynamics. Six participants performed ten vertical and forward single leg hops while the kinematics and the ground reaction force "GRF" were captured using an optoelectronic system coupled with a force platform.
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[This corrects the article doi: 10.1590/S1980-220X2017009603269].
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Fellow Pain and Palliative Care, Department of Anesthesiology Universidad CES Medellín,
Anesth Analg
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Department of Anesthesiology, Intensive Care and Pain Medicine St Antonius Hospital Nieuwegein, Netherlands Department of Anesthesiology and Intensive Care University Medical Center Utrecht Utrecht, Netherlands.
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