American Journal of Emergency Medicine最新文献

英文中文

Machine learning models to detect opioid misuse in emergency department patients at triage 机器学习模型检测阿片类药物滥用的急诊科患者在分流。

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-06-01 Epub Date: 2026-02-26 DOI: 10.1016/j.ajem.2026.02.037

Chirag Chhablani , Usman Shahid , Natalie Parde , Sami Muslmani , Huiyi Hu , Dillon Thorpe , Majid Afshar , Niranjan Karnik , Neeraj Chhabra

Objective

Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based treatments for patients with opioid misuse, but few receive such care. Universal manual screening has been proposed to improve patient identification but is uncommon due to its time and resource-intensive nature. We sought to determine the feasibility of identifying patients with opioid misuse at the time of ED triage using machine learning (ML).

Methods

We conducted a retrospective cohort study of 1123 ED encounters (September 2020 – March 2023) at a tertiary hospital. Encounters were enriched for opioid misuse, manually annotated, and chronologically split for training, validation, and testing. Candidate triage-time features included patient demographics, Emergency Severity Index, arrival time of day, chief complaint, comorbidities, and chronic medications. Model performance was evaluated using F1 score, area under the precision–recall curve (AUPRC), accuracy, recall, and AUROC. Post-hoc explainability analyses included SHapley Additive exPlanations (SHAP) and feature importance.

Results

All models performed comparably to opioid-related diagnosis codes placed at any time during the encounter. Random Forest (F1 = 0.75 [95%CI 0.70–0.83], AUPRC = 0.88 [0.81–0.93], accuracy = 0.79 [0.70–0.83]) and Gradient Boosting (F1 = 0.77 [0.71–0.82], AUPRC = 0.89 [0.85–0.93], accuracy = 0.81 [0.720.84]) had among the highest F1 score and AUPRC but confidence intervals overlapped with other methods. Explainability analyses highlighted prior drug-use diagnosis codes, triage acuity, and age as top predictors.

Conclusion

ML classifiers leveraging routinely collected triage data offer a feasible and scalable alternative to manual screening in flagging opioid misuse before physician evaluation, potentially enabling early harm-reduction interventions. Prospective multi-site validation, calibration, and bias assessments are warranted.

目的：急诊科（ED）的遭遇为阿片类药物滥用患者启动循证治疗提供了宝贵的机会，但很少有人得到这样的护理。普遍的人工筛查已被提出以改善患者的识别，但由于其时间和资源密集的性质是不常见的。我们试图确定在ED分诊时使用机器学习（ML）识别阿片类药物滥用患者的可行性。方法：我们对一家三级医院的1123例急诊患者（2020年9月至2023年3月）进行了回顾性队列研究。遭遇丰富了阿片类药物滥用，手动注释，并按时间顺序分开进行训练，验证和测试。候选的分诊时间特征包括患者人口统计学特征、紧急严重程度指数、到达时间、主诉、合并症和慢性药物。使用F1评分、精确召回曲线下面积（AUPRC）、准确率、召回率和AUROC来评估模型的性能。事后可解释性分析包括SHapley加性解释（SHAP）和特征重要性。结果：所有模型的表现与在遭遇过程中任何时间放置的阿片类药物相关诊断代码相当。随机森林（F1 = 0.75 [95%CI 0.70-0.83], AUPRC = 0.88[0.81-0.93]，准确率= 0.79[0.70-0.83]）和梯度增强（F1 = 0.77 [0.71-0.82], AUPRC = 0.89[0.85-0.93]，准确率= 0.81[0.720.84]）的F1得分和AUPRC最高，但置信区间与其他方法重叠。可解释性分析强调了先前的药物使用诊断代码、分诊敏锐度和年龄是最重要的预测因素。结论：ML分类器利用常规收集的分诊数据提供了一种可行且可扩展的替代方法，可以在医生评估之前标记阿片类药物滥用，从而潜在地实现早期危害减少干预。有必要进行前瞻性多站点验证、校准和偏倚评估。

{"title":"Machine learning models to detect opioid misuse in emergency department patients at triage","authors":"Chirag Chhablani , Usman Shahid , Natalie Parde , Sami Muslmani , Huiyi Hu , Dillon Thorpe , Majid Afshar , Niranjan Karnik , Neeraj Chhabra","doi":"10.1016/j.ajem.2026.02.037","DOIUrl":"10.1016/j.ajem.2026.02.037","url":null,"abstract":"<div><h3>Objective</h3><div>Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based treatments for patients with opioid misuse, but few receive such care. Universal manual screening has been proposed to improve patient identification but is uncommon due to its time and resource-intensive nature. We sought to determine the feasibility of identifying patients with opioid misuse at the time of ED triage using machine learning (ML).</div></div><div><h3>Methods</h3><div>We conducted a retrospective cohort study of 1123 ED encounters (September 2020 – March 2023) at a tertiary hospital. Encounters were enriched for opioid misuse, manually annotated, and chronologically split for training, validation, and testing. Candidate triage-time features included patient demographics, Emergency Severity Index, arrival time of day, chief complaint, comorbidities, and chronic medications. Model performance was evaluated using F1 score, area under the precision–recall curve (AUPRC), accuracy, recall, and AUROC. Post-hoc explainability analyses included SHapley Additive exPlanations (SHAP) and feature importance.</div></div><div><h3>Results</h3><div>All models performed comparably to opioid-related diagnosis codes placed at any time during the encounter. Random Forest (F1 = 0.75 [95%CI 0.70–0.83], AUPRC = 0.88 [0.81–0.93], accuracy = 0.79 [0.70–0.83]) and Gradient Boosting (F1 = 0.77 [0.71–0.82], AUPRC = 0.89 [0.85–0.93], accuracy = 0.81 [0.720.84]) had among the highest F1 score and AUPRC but confidence intervals overlapped with other methods. Explainability analyses highlighted prior drug-use diagnosis codes, triage acuity, and age as top predictors.</div></div><div><h3>Conclusion</h3><div>ML classifiers leveraging routinely collected triage data offer a feasible and scalable alternative to manual screening in flagging opioid misuse before physician evaluation, potentially enabling early harm-reduction interventions. Prospective multi-site validation, calibration, and bias assessments are warranted.</div></div>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"104 ","pages":"Pages 17-23"},"PeriodicalIF":2.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147367374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time to intubate comparing non-channeled video laryngoscope blade (66° v/s 45°) in patients requiring emergency airway management - A randomized study. 在需要紧急气道管理的患者中比较非通道视频喉镜刀片（66°v/s 45°）的插管时间-一项随机研究

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-09 DOI: 10.1016/j.ajem.2026.02.012

Nikita Patil, Ankur Verma, Sanjay Jaiswal, Maheshwar Lal

引用次数: 0

Reader Comment Regarding Outcomes of Boarding Critically Ill Patients in U.S. EDs: A Systematic Review and Meta-Analysis. 治疗病人，而不是时间：急诊科的重症护理决定了结果——读者对“美国急诊科重症患者入住的结果：系统回顾和荟萃分析”的评论。

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-12 DOI: 10.1016/j.ajem.2026.02.018

Matthias Noitz, Wilhelm Behringer, Harald Herkner, Michael Reindl, Martin W Dünser

引用次数: 0

Mobile phone auscultation to detect carotid stenosis and cerebral ischemia. 手机听诊检测颈动脉狭窄和脑缺血。

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-04 DOI: 10.1016/j.ajem.2026.02.004

Evan Otte, Martin Huecker

引用次数: 0

Increasing naloxone distribution to opioid overdose patients in the emergency department following best practice advisory enhancement. 增加纳洛酮分配到阿片类药物过量的病人在急诊部门的最佳实践咨询加强。

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-08 DOI: 10.1016/j.ajem.2026.01.056

Nicholas Nacca, Nicole M Acquisto, Cole Schailey, Matthew C Lambrych, Justin A Mazzillo

引用次数: 0

Temperature at admission and mortality in older adults with infection: Limited prognostic value in non-sepsis cases 入院时的体温和老年人感染的死亡率：对非败血症病例的有限预后价值

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-01-24 DOI: 10.1016/j.ajem.2026.01.045

Finn Erland Nielsen , Osama Bin Abdullah , Lana Chafranska , Thomas Andersen Schmidt , Rune Husås Sørensen

Background

Temperature abnormalities are established prognostic markers in sepsis, but their predictive value in older adults with infection without sepsis remains unclear.

Objective

To examine the association between arrival temperature and 28-day all-cause mortality among emergency department patients aged ≥65 years with infection, stratified by sepsis status.

Methods

We performed a post-hoc analysis of a prospective cohort from a Danish emergency department. Sepsis was defined as infection plus an acute ≥2 point increase in the Sequential Organ Failure Assessment (SOFA) score. Propensity score matching balanced covariates between groups. The restricted cubic spline regression modelled non-linear temperature-mortality associations. Sensitivity analyses excluded patients with comorbidities that affected baseline SOFA and used the National Early Warning Score (NEWS2) to classify likely sepsis.

Results

Among 1431 patients (median age 78.9 years; 49.3% male), 545 (38.1%) met sepsis criteria. In non-sepsis patients, mortality was stable across 36–41 °C with no statistically significant association (global spline p = 0.320), although a modest increase was observed below 36 °C. In sepsis, hypothermia (<36 °C) was associated with higher mortality, whereas fever (>38 °C) was protective. At temperature extremes (<36 °C and > 39 °C), confidence intervals widened substantially due to sparse data. Findings were consistent across sensitivity analyses.

Conclusions

In older adults with infection but without sepsis, arrival temperature did not predict 28-day mortality. In sepsis, hypothermia was associated with higher mortality, and fever with lower mortality. The prognostic interpretation of very low or very high temperatures remains uncertain, suggesting clinical caution in these temperature ranges.

背景：体温异常是脓毒症的预后指标，但其在老年感染无脓毒症患者中的预测价值尚不清楚。目的探讨急诊年龄≥65岁感染患者28天全因死亡率与到达温度的关系。方法：我们对来自丹麦急诊科的前瞻性队列进行事后分析。脓毒症被定义为感染加上顺序器官衰竭评估（SOFA）评分急性≥2分升高。倾向评分匹配组间平衡协变量。限制三次样条回归模拟了温度-死亡率的非线性关系。敏感性分析排除了影响基线SOFA的合并症患者，并使用国家早期预警评分（NEWS2）对可能的败血症进行分类。结果1431例患者（中位年龄78.9岁，男性49.3%）中，545例（38.1%）符合脓毒症标准。在非脓毒症患者中，死亡率在36 - 41°C范围内保持稳定，无统计学意义（全局样条p = 0.320），尽管在36°C以下观察到适度增加。在败血症中，低体温（36°C）与较高的死亡率相关，而发烧（38°C）具有保护作用。在极端温度（<；36°C和>； 39°C），由于数据稀疏，置信区间大幅扩大。敏感性分析的结果是一致的。结论在感染但无败血症的老年人中，到达温度不能预测28天死亡率。在败血症中，低温与较高的死亡率相关，而发烧与较低的死亡率相关。非常低或非常高的温度的预后解释仍然不确定，建议在这些温度范围内临床谨慎。

{"title":"Temperature at admission and mortality in older adults with infection: Limited prognostic value in non-sepsis cases","authors":"Finn Erland Nielsen , Osama Bin Abdullah , Lana Chafranska , Thomas Andersen Schmidt , Rune Husås Sørensen","doi":"10.1016/j.ajem.2026.01.045","DOIUrl":"10.1016/j.ajem.2026.01.045","url":null,"abstract":"<div><h3>Background</h3><div>Temperature abnormalities are established prognostic markers in sepsis, but their predictive value in older adults with infection without sepsis remains unclear.</div></div><div><h3>Objective</h3><div>To examine the association between arrival temperature and 28-day all-cause mortality among emergency department patients aged ≥65 years with infection, stratified by sepsis status.</div></div><div><h3>Methods</h3><div>We performed a post-hoc analysis of a prospective cohort from a Danish emergency department. Sepsis was defined as infection plus an acute ≥2 point increase in the Sequential Organ Failure Assessment (SOFA) score. Propensity score matching balanced covariates between groups. The restricted cubic spline regression modelled non-linear temperature-mortality associations. Sensitivity analyses excluded patients with comorbidities that affected baseline SOFA and used the National Early Warning Score (NEWS2) to classify <em>likely sepsis</em>.</div></div><div><h3>Results</h3><div>Among 1431 patients (median age 78.9 years; 49.3% male), 545 (38.1%) met sepsis criteria. In non-sepsis patients, mortality was stable across 36–41 °C with no statistically significant association (global spline <em>p</em> = 0.320), although a modest increase was observed below 36 °C. In sepsis, hypothermia (<36 °C) was associated with higher mortality, whereas fever (>38 °C) was protective. At temperature extremes (<36 °C and > 39 °C), confidence intervals widened substantially due to sparse data. Findings were consistent across sensitivity analyses.</div></div><div><h3>Conclusions</h3><div>In older adults with infection but without sepsis, arrival temperature did not predict 28-day mortality. In sepsis, hypothermia was associated with higher mortality, and fever with lower mortality. The prognostic interpretation of very low or very high temperatures remains uncertain, suggesting clinical caution in these temperature ranges.</div></div>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"103 ","pages":"Pages 1-8"},"PeriodicalIF":2.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Clinical differences between metformin-associated lactic acidosis and metformin-unrelated lactic acidosis: A descriptive study 二甲双胍相关乳酸酸中毒与二甲双胍无关乳酸酸中毒的临床差异：一项描述性研究

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-01-22 DOI: 10.1016/j.ajem.2026.01.027

Yuji Okazaki MD , Fumiya Inoue MD , Toshihisa Ichiba MD , Akira Namera PhD

Background

The extent to which metformin contributes to lactic acidosis in metformin-treated patients presenting to the emergency department (ED) remains unclear, particularly when blood metformin concentrations are unavailable. This study aimed to clarify the clinical differences between metformin-associated lactic acidosis (MALA) and metformin-unrelated lactic acidosis (MULA) on ED admission.

Methods

We conducted a retrospective study at a tertiary care hospital from January 1, 2023 to July 31, 2025. We included adult patients receiving metformin who presented to the ED with lactic acidosis, defined as pH < 7.35 and lactate ≥5 mmol/L. Patients were classified as having MALA if their serum metformin concentration at ED admission was ≥5 mg/L; others were categorized as MULA.

Results

Among 14 patients with available serum metformin concentrations, 3 were classified as MALA and 11 as MULA. MALA patients presented with lower blood pressure at ED admission (median 65/36 versus 130/74 mmHg), more profound acidemia (median pH 7.03 [IQR 6.89–7.06] versus 7.22 [IQR 7.20–7.32]), and higher lactate levels (median 14.8 mmol/L [IQR 14.3–19.0] versus 7.3 mmol/L [IQR 5.7–12.5]). Serum creatinine was also higher in the MALA group (median 2.65 mg/dL [IQR 2.26–6.35]) than in the MULA group (median 1.16 mg/dL [IQR 0.97–1.39]).

Conclusions

Although the sample size was small, three clinical clues for identifying MALA may include severe acidemia with hyperlactatemia, kidney impairment, and hypotension. Clinicians may consider MALA when these findings coexist in the absence of measured blood metformin concentrations. Further large-scale studies are warranted to confirm our findings.

背景：二甲双胍对急诊科（ED）接受二甲双胍治疗的患者乳酸性酸中毒的影响程度尚不清楚，特别是在无法获得血液二甲双胍浓度的情况下。本研究旨在阐明二甲双胍相关乳酸性酸中毒（MALA）和二甲双胍无关乳酸性酸中毒（MULA）在急诊科入院时的临床差异。方法对2023年1月1日至2025年7月31日在某三级医院进行回顾性研究。我们纳入了接受二甲双胍治疗并以乳酸酸中毒（定义为pH <； 7.35，乳酸≥5 mmol/L）向ED就诊的成年患者。如果患者入院时血清二甲双胍浓度≥5mg /L，则归类为MALA；其他被归类为MULA。结果14例患者血清二甲双胍可用浓度中，3例为MALA， 11例为MULA。MALA患者入院时血压较低（中位数65/36对130/74 mmHg），更严重的酸血症（中位数pH为7.03 [IQR 6.89-7.06]对7.22 [IQR 7.20-7.32]），乳酸水平较高（中位数14.8 mmol/L [IQR 14.3-19.0]对7.3 mmol/L [IQR 5.7-12.5]）。MALA组的血清肌酐（中位数2.65 mg/dL [IQR 2.26-6.35]）也高于MULA组（中位数1.16 mg/dL [IQR 0.97-1.39]）。结论虽然样本量较小，但重度酸血症伴高乳酸血症、肾功能损害和低血压可能是诊断MALA的三个临床线索。当没有测量血液二甲双胍浓度时，这些发现共存，临床医生可能会考虑MALA。需要进一步的大规模研究来证实我们的发现。

{"title":"Clinical differences between metformin-associated lactic acidosis and metformin-unrelated lactic acidosis: A descriptive study","authors":"Yuji Okazaki MD , Fumiya Inoue MD , Toshihisa Ichiba MD , Akira Namera PhD","doi":"10.1016/j.ajem.2026.01.027","DOIUrl":"10.1016/j.ajem.2026.01.027","url":null,"abstract":"<div><h3>Background</h3><div>The extent to which metformin contributes to lactic acidosis in metformin-treated patients presenting to the emergency department (ED) remains unclear, particularly when blood metformin concentrations are unavailable. This study aimed to clarify the clinical differences between metformin-associated lactic acidosis (MALA) and metformin-unrelated lactic acidosis (MULA) on ED admission.</div></div><div><h3>Methods</h3><div>We conducted a retrospective study at a tertiary care hospital from January 1, 2023 to July 31, 2025. We included adult patients receiving metformin who presented to the ED with lactic acidosis, defined as pH < 7.35 and lactate ≥5 mmol/L. Patients were classified as having MALA if their serum metformin concentration at ED admission was ≥5 mg/L; others were categorized as MULA.</div></div><div><h3>Results</h3><div>Among 14 patients with available serum metformin concentrations, 3 were classified as MALA and 11 as MULA. MALA patients presented with lower blood pressure at ED admission (median 65/36 versus 130/74 mmHg), more profound acidemia (median pH 7.03 [IQR 6.89–7.06] versus 7.22 [IQR 7.20–7.32]), and higher lactate levels (median 14.8 mmol/L [IQR 14.3–19.0] versus 7.3 mmol/L [IQR 5.7–12.5]). Serum creatinine was also higher in the MALA group (median 2.65 mg/dL [IQR 2.26–6.35]) than in the MULA group (median 1.16 mg/dL [IQR 0.97–1.39]).</div></div><div><h3>Conclusions</h3><div>Although the sample size was small, three clinical clues for identifying MALA may include severe acidemia with hyperlactatemia, kidney impairment, and hypotension. Clinicians may consider MALA when these findings coexist in the absence of measured blood metformin concentrations. Further large-scale studies are warranted to confirm our findings.</div></div>","PeriodicalId":55536,"journal":{"name":"American Journal of Emergency Medicine","volume":"103 ","pages":"Pages 9-13"},"PeriodicalIF":2.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The authors respond to reader comment regarding Outcomes of boarding critically ill patients in U.S. EDs: A systematic review and meta-analysis. 作者回应了读者对《美国急诊科重症患者入住的结果：系统回顾和荟萃分析》的评论。

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-14 DOI: 10.1016/j.ajem.2026.02.019

Natalie N Htet, Jennifer A Walker, Daniel Jafari, Megan A Rech, Trager Hintze, Quincy K Tran

引用次数: 0

Optimizing the circuit: A critical enhancement at the 2025 NYC Marathon. 优化赛道：2025年纽约马拉松赛的关键改进。

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-11 DOI: 10.1016/j.ajem.2026.02.009

Connor B Fitzpatrick, Phillip Groden, Matthew T Carroll, Paul C Saunders, Matt S Friedman

引用次数: 0

Impact of Turbo O₂™ cap on safe apnea period in intubation: A proof-of-concept crossover study using a porcine model. Turbo O2™帽对插管中安全呼吸暂停期的影响：一项使用猪模型的概念验证交叉研究

IF 2.2 3区医学 Q1 EMERGENCY MEDICINE

American Journal of Emergency Medicine

Pub Date : 2026-05-01 Epub Date: 2026-02-04 DOI: 10.1016/j.ajem.2026.02.003

Victor C Pinto, Robert C Doerning, Marina L Mamarian, Jane Hall, Steven H Mitchell

引用次数: 0

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

American Journal of Emergency Medicine

全部 BIOGEOSCIENCES Geobiology Basin Res. Environ. Toxicol. Pharmacol. Environ. Res. Lett. ARCT ANTARCT ALP RES ARCHAEOMETRY Mon. Weather Rev. Atmos. Chem. Phys. Geosci. J. ENVIRONMENT ENVIRON HEALTH-GLOB ArcheoSci.-Rev. Archeom. Environ. Mol. Mutagen. J. Clim. Environ. Technol. Innovation Nat. Clim. Change J. Atmos. Sol. Terr. Phys. Archaeol. Anthropol. Sci. Astrophys. J. Suppl. Ser. Carbon Balance Manage. Ocean and Coastal Research Terra Nova Int. J. Paleopathol. Engineering, Technology & Applied Science Research Environ. Eng. Manage. J. B SOC GEOL MEX Mineral. Mag. Chem. Ecol. European Journal of Clinical and Experimental Medicine TERR ATMOS OCEAN SCI REV MEX CIENC GEOL J. Atmos. Oceanic Technol. Enzyme Research Global Biogeochem. Cycles Eur. J. Control WEATHER TECTONOPHYSICS ACTA GEOL POL ACTA PARASITOL Chin. Phys. C Eurasian Journal of Emergency Medicine Surv. Geophys. Environmental dermatology : the official journal of the Japanese Society for Contact Dermatitis OCEAN SCI J Adv. Atmos. Sci. Ann. Phys. Atmos. Meas. Tech. Conserv. Biol. QUATERNAIRE Swiss J. Geosci. 2008 International Conference on Electronic Packaging Technology & High Density Packaging Surv. Rev. ASTROBIOLOGY Environmental Claims Journal Ecol. Indic. Environ. Educ. Res, Exp. Hematol. Oncol. Environmental Toxicology & Water Quality Geochim. Cosmochim. Acta EXP LUNG RES 2005 Asian Conference on Sensors and the International Conference on New Techniques in Pharmaceutical and Biomedical Research Adv. Meteorol. Exp. Eye Res. Aust. J. Earth Sci. GEOHERITAGE 2009 12th International Symposium on Design and Diagnostics of Electronic Circuits & Systems Appl. Clay Sci. Yan Ke Xue Bao (Hong Kong) Big Earth Data Int. J. Earth Sci. Contrib. Mineral. Petrol. Geostand. Geoanal. Res. Clean-Soil Air Water Appl. Geochem. Acta Oceanolog. Sin. Int. J. Biometeorol. Geochem. J. Annu. Rev. Earth Planet. Sci. npj Clim. Atmos. Sci. Ann. Glaciol. Asia-Pac. J. Atmos. Sci. Gondwana Res. J. Hydrol. Am. J. Phys. Anthropol. Aquat. Geochem. J. Atmos. Chem. GEOLOGY Geosci. Front. IZV-PHYS SOLID EART+ Environ. Geochem. Health AAPG Bull. Acta Geophys. ECOLOGY ACTA GEOL SIN-ENGL ACTA PETROL SIN Resour. Geol. Atmos. Res. Org. Geochem. ECOSYSTEMS

﹀