Predicting in-hospital death among patients injured in traffic crashes in Saudi Arabia

IntroductionTraffic-related injuries are a major cause of premature death in developing countries. Saudi Arabia has struggled with high rates of traffic-related deaths for decades, yet little is known about health outcomes of motor vehicle victims seeking medical care. This study aims to develop and validate a model to predict in-hospital death among patients admitted to a large-urban trauma centre in Saudi Arabia for treatment following traffic-related crashes.MethodsThe analysis used data from King Abdulaziz Medical City (KAMC) in Riyadh, Saudi Arabia. During the study period 2001–2010, 5325 patients met the inclusion criteria of being injured in traffic crashes and seen in the Emergency Department (ED) and/or admitted to the hospital. Backward stepwise logistic regression, with in-hospital death as the outcome, was performed. Variables with p < 0.05 were included in the final model. The Bayesian Information Criterion (BIC) was employed to identify the most parsimonious model. Model discrimination was evaluated by the C-statistic and calibration by the Hosmer–Lemeshow Goodness of Fit statistic. Bootstrapping was used to assess overestimation of model performance and obtain a corrected C-statistic.Results457 (8.5%) patients died at some time during their treatment in the ED or hospital. Older age, the Triage-Revised Trauma Scale (T-RTS), and Injury Severity Score were independent risk factors for in-hospital death: T-RTS was best modelled with linear and quadratic terms to capture a flattening of the relationship to death in the more severe range. The model showed excellent discrimination (C-statistic = 0.96) and calibration (H–L statistic 4.29 [p > 0.05]). Internal bootstrap validation gave similar results (C-statistic = 0.96).ConclusionsThe proposed model can predict in-hospital death accurately. It can facilitate the triage process among injured patients, and identify unexpected deaths in order to address potential pitfalls in the care process. Conversely, by identifying high-risk patients, strategies can be developed to improve trauma care for these patients and reduce case-fatality. This is the first study to develop and validate a model to predict traffic-related mortality in a developing country. Future studies from developing countries can use this study as a reference for case fatality achievable for different risk profiles at a well-equipped trauma centre.     

改良Hardinge入路全髋置换在双下肢等长控制中的应用

目的评价改良Hardinge入路全髋置换在双下肢等长控制中的应用效果。方法对行改良Hardinge入路全髋置换及术中用自创等长测量方法进行双下肢等长控制并获1年以上随访的100例患者进行总结,采用Harris标准对髋关节功能进行评定。结果 100例患者均获随访,时间12~60(26±2.1)个月。Harris评分:优92例,良7例,可1例,优良率99%。下肢等长95例,下肢不等长在0.3~0.5 cm之间3例,相差0.6cm1例,相差0.8 cm 1例。结论该入路暴露好,假体安装定位好,因术中下肢基本处于标准侧卧位,易于控制下肢长度,特别适用自创的术中精确测量调控双下肢等长的手术方法,可减少因体位原因导致的误差,术后外展肌恢复快,总体恢复良好。     

专业防治宣教与高知人群血管性痴呆疾病负担的相关性

目的：研究专业防治宣教与高知人群血管性痴呆疾病负担的相关性。方法300例高知血管性痴呆者作为调研对象。评价其认知功能、日常生活的能力、伤残和存活年限,将患者分为A、B、C3组,A组接受宣教0次,B组接受宣教1～3次,C组接受宣教≥4次。计算出DALY（即伤残调整寿命年）的数值。结果3组DALY值中,A组为7·63±2·37,B组为7·51±1·75,C组为4·93±0·48,3组差异有统计学意义（均 P＜0·05）。结论专业化防治宣教和高知人群的血管性痴呆疾病负担相关,随着宣教次数（≥4次最佳）的增多,DALY值逐渐减小。     

美国卫生服务循证决策及其对中国的启示

文章分析研究了二十一世纪以来美国卫生服务循证决策。十年来,美国卫生服务调查数据分析显示,其疾病格局发生改转,美国卫生服务体系的工作重点已由急性损伤和传染病的救治,逐渐转变为慢性病和传染病的救治和预防、保健。及时调整、准确定位卫生服务体系的功能,制定了有针对性的医疗卫生政策。中国作为发展中国家,现已进入老龄化社会,原来的疾病和健康问题依然存在,同时也出现了美国等发达国家面临的健康问题。美国所遇到的挑战及其所采取的对策,以及发展趋势,为当前在中国开展卫生服务政策研究提供了启示。     

剖宫产抗生素合理应用的临床分析

目的：探讨剖宫产围手术期抗菌药物预防感染的效果。方法将南京军区福州总医院2011年1至12月接受剖宫产手术的产妇600例随机分为两组,每组各300例。 A组于术中断脐后立即给予头孢一代（头孢硫脒）2g静滴,术后12小时再给同等剂量滴注1次;B组于术后给予头孢二代（头孢替安）2g静滴,每日2次,连用4天。比较两组临床效果及费用等情况。结果两组术后最高体温、切口感染、院内感染无显著性差异（均P＞0．05）。 A组抗生素费用约280元,B组抗生素费用约1050元,A组明显少于B组（F＝42．547,P＜0．01）。结论剖宫产围手术期通过使用价格昂贵的广谱头孢类抗生素及延长抗菌药物的使用时间,并不能提高术后预防感染的效果,头孢一代术中预防性给药不失为一种合理有效又经济的预防措施。     

Comparison of the Framingham Risk Score,SCORE and WHO/ISH cardiovascular risk prediction models in an Asian population

Background

Cardiovascular risk-prediction models are used in clinical practice to identify and treat high-risk populations, and to communicate risk effectively. We assessed the validity and utility of four cardiovascular risk-prediction models in an Asian population of a middle-income country.

Methods

Data from a national population-based survey of 14,863 participants aged 40 to 65 years, with a follow-up duration of 73,277 person-years was used. The Framingham Risk Score (FRS), SCORE (Systematic COronary Risk Evaluation)-high and -low cardiovascular-risk regions and the World Health Organization/International Society of Hypertension (WHO/ISH) models were assessed. The outcome of interest was 5-year cardiovascular mortality. Discrimination was assessed for all models and calibration for the SCORE models.

Results

Cardiovascular risk factors were highly prevalent; smoking 20%, obesity 32%, hypertension 55%, diabetes mellitus 18% and hypercholesterolemia 34%. The FRS and SCORE models showed good agreement in risk stratification. The FRS, SCORE-high and -low models showed good discrimination for cardiovascular mortality, areas under the ROC curve (AUC) were 0.768, 0.774 and 0.775 respectively. The WHO/ISH model showed poor discrimination, AUC = 0.613. Calibration of the SCORE-high model was graphically and statistically acceptable for men (χ² goodness-of-fit, p = 0.097). The SCORE-low model was statistically acceptable for men (χ² goodness-of-fit, p = 0.067). Both SCORE-models underestimated risk in women (p < 0.001).

Conclusions

The FRS and SCORE-high models, but not the WHO/ISH model can be used to identify high cardiovascular risk in the Malaysian population. The SCORE-high model predicts risk accurately in men but underestimated it in women.