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1.
目的分析重症监护病房(ICU)中重症肺炎婴儿的死亡危险因素。方法收集医院信息系统中儿科和新生儿科ICU 2012年1月1日至2017年1月1日收治的年龄不超过2个月的重症肺炎患儿的病历信息。采用SAS 9.4统计学软件分析数据,以患儿的一般资料、药物治疗方案、合并用药、合并疾病、临床结局等指标进行单因素分析,采用多因素Logistic回归分析法筛选出与患儿死亡相关的独立危险因素。结果共纳入604例重症肺炎患儿,其中死亡49例(8.11%)。多因素Logistic回归分析结果显示,出生体质量低于1.8 kg[OR=3.92,95%CI(1.50,10.23),P=0.002],极危重肺炎[OR=3.55,95%CI(1.39,9.09),P=0.008],进行机械通气[OR=5.06,95%CI(1.97,12.95),P<0.001],合并贫血[OR=5.61,95%CI(2.36,13.35),P<0.001],合并新生儿窒息[OR=6.03,95%CI(1.57,23.12),P=0.009],合并消化道出血[OR=3.73,95%CI(1.21,11.48),P=0.021],合用镇静催眠药[OR=4.32,95%CI(1.76,10.61),P<0.001]均为重症肺炎婴幼儿死亡的独立危险因素;合用微生态制剂为保护性因素,可显著降低患儿的死亡率[OR=0.24,95%CI(0.10,0.54),P<0.001]。结论重症肺炎疾病的严重程度、患儿的营养状态、合并疾病、临床治疗方案、合用药物等均可对重症肺炎婴儿的临床结局产生较大影响,医师和药师在临床治疗过程中应早期识别死亡危险因素,并建立相应的预防措施,以降低死亡率,提高合理用药水平和医疗质量。 相似文献
2.
目的 掌握2015—2020年徐州市铜山区5~18岁儿童青少年伤害死亡流行特征,为政府部门出台相关政策提供科学依据。方法 搜集徐州市铜山区2015—2020年儿童青少年伤害死亡资料进行描述性统计分析,计算伤害的死亡率和构成比,比较采用χ2检验。结果 伤害是铜山区儿童青少年的首位死亡原因,死亡率为8.01/10万,占儿童青少年总死亡的54.05%。随着年龄增加,主要伤害的死亡率从5~9岁年龄组的5.30/10万增加到15~18岁年龄组的12.47/10万(χ2趋势=14.383,P<0.001)。道路交通事故、溺水、意外跌落和自杀的死亡率分别为3.01/10万、2.81/10万、0.67/10万、0.33/10万,居铜山区儿童青少年伤害死亡的前4位。结论 道路交通事故、溺水、意外跌落、自杀是铜山区儿童青少年伤害死亡的主要原因,应采取针对性措施,预防控制儿童青少年伤害的发生。 相似文献
3.
《Journal d'obstetrique et gynecologie du Canada》2022,44(8):901-907
ObjectivePregnancies complicated by fetal heart defects often undergo a planned delivery prior to term by either induction of labour or cesarean delivery to ensure optimal availability of neonatal care. We aimed to assess whether such planned deliveries achieve their goal of better perinatal care.MethodsWe conducted a retrospective case-control study of pregnancies complicated by isolated fetal cardiac defects, without other fetal comorbidities, managed at a single fetal medicine unit over a 10-year period. Only pregnancies delivered past 37 weeks gestation were included. Patients undergoing elective delivery for care planning reasons only were compared with patients in whom planned delivery was clinically indicated and patients who laboured spontaneously. Obstetric and perinatal outcomes were recorded.ResultsOf the 180 pregnancies included in the study, 59 (32.8%) were in the elective group, 49 (27.2%), in the indicated group, and 72 (40%), in the spontaneous group. Mean gestational age at delivery was 39.0 ± 1.1 weeks overall and did not differ between the groups. For the elective group, only 35.6% of deliveries occurred during office hours, which was similar to the 2 other groups. The rate of adverse obstetric or postnatal outcomes was not statistically significantly different between groups.ConclusionTimed delivery at term does not seem to be associated with an increased risk of poor perinatal outcomes. It may improve perinatal care by providing proximity to a neonatal intensive care unit and convenience for patients and providers. 相似文献
4.
目的了解郑州市二七区居民2011—2020年恶性肿瘤死亡流行趋势及对居民寿命的影响情况,为制定恶性肿瘤防治对策提供科学依据。方法对2011—2020年郑州市二七区居民恶性肿瘤死亡资料进行分析,计算恶性肿瘤死亡率、潜在减寿年数(potential years of life lost,PYLL)、标化潜在减寿年数(standardized potential years of life lost,SPYLL)、标化潜在减寿率(standardized potential years of life lost rate,SPYLLR)和人均减寿年数(average years of life lost,AYLL)等指标,采用年度变化百分比(annual percent change,APC)分析率的时间变化趋势。结果2011—2020年郑州市二七区居民恶性肿瘤年均死亡率为114.68/10万,标化死亡率为103.52/10万,男性年均死亡率(146.09/10万)高于女性(84.56/10万)。恶性肿瘤前5位死因依次为肺癌、肝癌、胃癌、结直肠癌和食管癌,共占恶性肿瘤死亡构成的65.36%。2011—2020年该区居民恶性肿瘤死亡率呈上升趋势(APC=3.70%,P<0.001)。0~44岁年龄组恶性肿瘤死亡率处于较低水平,45岁后随年龄增长逐渐升高,75岁以后迅速升高。恶性肿瘤总PYLL为39067人年,SPYLLR为6.73‰,AYLL为12.59年。结论肺癌、肝癌、胃癌、结直肠癌和食管癌是二七区恶性肿瘤预防控制的重点工作,同时宫颈癌和乳腺癌对女性健康的影响不可忽视,应针对主要恶性肿瘤和重点人群开展综合防控措施,以降低恶性肿瘤的死亡率。 相似文献
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6.
目的 探讨中性粒细胞计数与淋巴细胞和血小板计数比值(N/LPR)对慢性阻塞性肺疾病急性加重期(AECOPD)患者28天死亡预测价值。方法 选择2018年2月~2020年10月在我院就诊的169例AECOPD患者病例资料进行研究。收集患者性别、年龄等一般资料及入组时中性粒细胞计数、淋巴细胞计数、血小板计数,并分别计算中性粒细胞计数与淋巴细胞计数比值(NLR)及N/LPR。根据28天生存情况将患者分为生存组与死亡组,比较两组患者一般资料及实验室检查指标。并以ROC分析法评估NLR及N/LPR对AECOPD患者28天生存情况的预测价值。结果 纳入的169例AECOPD患者中28天内死亡35例。两组患者性别、年龄、慢阻肺病程、吸烟史、饮酒史及并发脓毒症例数比较差异均无统计学意义(P>0.05)。死亡组中性粒细胞计数、NLR、N/LPR及APACHEⅡ评分、PaCO2均高于生存组,淋巴细胞计数、血小板计数、PaO2均低于生存组,差异有统计学意义(P<0.05)。相关性分析结果显示,中性粒细胞计数、NLR、N/LPR、PaCO2与APACHEⅡ评分均呈正相关(均P<0.05),淋巴细胞计数、血小板计数、PaO2与APACHEⅡ评分均呈负相关(均P<0.05)。NLR对AECOPD患者28天死亡最佳预测截断值为14.28,敏感度为71.42%,特异度为78.36%,曲线下面积(AUC)低于N/LPR(0.766,95%CI:0.691~0.842 vs 0.916,95%CI:0.869~0.963);当最佳预测截断值为17.13时,敏感度为85.71%,特异度为86.57%。结论 N/LPR可用于AECOPD患者的28天死亡预测,且其预测价值较NLR更高。 相似文献
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8.
《Journal of the American Medical Directors Association》2022,23(9):1608.e1-1608.e8
ObjectiveData on prognostic tools for indicating mechanical ventilation in older people with COVID-19 are still limited. The aim of this research was to evaluate if the Multidimensional Prognostic Index (MPI), based on the Comprehensive Geriatric Assessment (CGA), may help physicians in identifying older hospitalized patients affected by COVID-19 who might benefit from mechanical ventilation.DesignLongitudinal, multicenter study.Settings and Participants502 older people hospitalized for COVID-19 in 10 European hospitals.MethodsMPI was calculated using 8 different domains typical of the CGA. A propensity score, Cox's regression analysis was used for assessing the impact of mechanical ventilation on rehospitalization/mortality for 90 days' follow-up, stratified by MPI = 0.50. The accuracy of MPI in predicting negative outcomes (ie, rehospitalization/mortality) was assessed using the area under the curve (AUC), and the discrimination with several indexes like the Net Reclassification Improvement (NRI) and the Integrated Discrimination Improvement (IDI).ResultsAmong 502 older people hospitalized for COVID-19 (mean age: 80 years), 152 were treated with mechanical ventilation. In the propensity score analysis, during the 90-day follow-up period, there were 44 rehospitalizations and 95 deaths. Mechanical ventilation in patients with MPI values ≥ 0.50, indicating frailer participants, was associated with a higher risk of rehospitalization/mortality (hazard ratio 1.56, 95% CI 1.09-2.23), whereas in participants with MPI values < 0.50 this association was not significant. The accuracy of the model including age, sex, respiratory parameters, and MPI was good (AUC = 0.783) as confirmed by an NRI of 0.2756 (P < .001) and an IDI of 0.1858 (P < .001), suggesting a good discrimination of the model in predicting negative outcomes.Conclusions and ImplicationsMPI could be useful for better individualizing older people hospitalized by COVID-19 who could benefit from mechanical ventilation. 相似文献
9.
《Vaccine》2022,40(27):3737-3745
BackgroundVaccines may induce non-specific effects on survival and health outcomes, in addition to protection against targeted pathogens or disease. Observational evidence suggests that infant Baccillus Calmette-Guérin (BCG) vaccination may provide non-specific survival benefits, while diphtheria-tetanus-pertussis (DTP) vaccination may increase the risk of mortality. Non-specific vaccine effects have been hypothesized to modify the effect of neonatal vitamin A supplementation (NVAS) on mortality.Methods22,955 newborns in Ghana and 31,999 newborns in Tanzania were enrolled in two parallel, randomized, double-blind, placebo-controlled trials of neonatal vitamin A supplementation from 2010 to 2014 and followed until 1-year of age. Cox proportional hazard models were used to estimate associations of BCG and DTP vaccination with infant survival.ResultsBCG vaccination was associated with a decreased risk of infant mortality after controlling for confounders in both countries (Ghana adjusted hazard ratio (aHR): 0.51, 95% CI: 0.38–0.68; Tanzania aHR: 0.08, 95% CI: 0.07–0.10). Receiving a DTP vaccination was associated with a decreased risk of death (Ghana aHR: 0.39, 95% CI: 0.26–0.59; Tanzania aHR: 0.19, 95% CI: 0.16–0.22). There was no evidence of interaction between BCG or DTP vaccination status and infant sex or NVAS.ConclusionWe demonstrated that BCG and DTP vaccination were associated with decreased risk of infant mortality in Ghana and Tanzania with no evidence of interaction between DTP or BCG vaccination, NVAS, and infant sex. Our study supports global recommendations on BCG and DTP vaccination and programmatic efforts to ensure all children have access to timely vaccination.Clinical trials registration: Ghana (Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12610000582055) and Tanzania (ANZCTR: ACTRN12610000636055) 相似文献