The efficacy of TKIs in treatment of human primary small cell lung cancer xenograft model in vivo

Objective: To study the treatmaient of non-small cell lung cancer, we established the HU-Prim allograft transplantation tumor model. Methods: The fresh tumor samples were transplanted in the right scapular subcutaneous layer of the severe combined immunodeficient Non-obese diabetic/severe combined immunodeficient(NOD/SCID) mice. The pathological features of the tumors were observed. Nonnecrotic tissue was inoculated subcutaneously into the right axillary. When the tumor in burdened rat grew approximately 100 mm3, according to the tumor size all the animals were divided into the following four groups, eight rats in each group: solvent control group, gefitinib group(100 mg/kg), erlotinib group(50 mg/kg), afatinib group(20 mg/kg). Aniamals were treated with drugs by intragastric(i.g.) administrated, once daily, for consecutively 14 days. Measure the tumor size 2-3 times every week. Results: Hu Prime1-NSCLC mutant sensitive xenograft model research data showed that reversible tyrosine kinase inhibitors gefitinib, erlotinib and irreversible tyrosine kinase inhibitor afatinib could effectively inhibit tumor growth in EGFR positive NSCLC allografts model. The pharmacodynamic activity of irreversible inhibitor was better than that of the reversible inhibitor. Specimens from clinical anthropogenic tumor retain characteristics of the human primary malignancy, histopathology, biological characteristics, and tumor markers, etc., which can more accurately reflect the characteristics of the tumor and the impact of interventions. Conclusion: The model is not only a good antitumor drug experimental platform, but also a new evaluation tool of individualized medication.

Successful Conservative Management of Trimethoprim Induced Life-Threatening Hyperkalaemia in a Patient with <i>Pneumocystis jirovecii</i>Pneumonia

Co-trimoxazole is a combination antibiotic made up of trimethoprim and sulphamethoxazole that is first line treatment for Pneumocystis jirovecii pneumonia (PJP). Hyperkalaemia is a relatively common side effect of the trimethoprim component of co-trimoxazole but it is not well recognised by clinicians. The mechanism of action causing hyperkalaemia due to trimethoprim is similar to the potassium sparing diuretic effect of amiloride. It has been suggested on this basis that the hyperkalaemia can be reversed by the administration of furosemide and 0.9% saline to promote kaliuresis. We present what we believe to be the first published case of successfully managing trimethoprim induced hyperkalaemia with furosemide and 0.9% saline allowing the continued use of co-trimoxazole to treat severe PJP.

Optimizing artificial intelligence in sepsis management: Opportunities in the present and looking closely to the future

Sepsis remains a major challenge internationally for healthcare systems.Its incidence is rising due to poor public awareness and delays in its recognition and subsequent management.In sepsis,mortality increases with every hour left untreated.Artificial intelligence(AI)is transforming worldwide healthcare delivery at present.This review has outlined how AI can augment strategies to address this global disease burden.AI and machine learning(ML)algorithms can analyze vast quantities of increasingly complex clinical datasets from electronic medical records to assist clinicians in diagnosing and treating sepsis earlier than traditional methods.Our review highlights how these models can predict the risk of sepsis and organ failure even before it occurs.This gives providers additional time to plan and execute treatment plans,thereby avoiding increasing complications associated with delayed diagnosis of sepsis.The potential for cost savings with AI implementation is also discussed,including improving workflow efficiencies,reducing administrative costs,and improving healthcare outcomes.Despite these advantages,clinicians have been slow to adopt AI into clinical practice.Some of the limitations posed by AI solutions include the lack of diverse data sets for model building so that they are widely applicable for routine clinical use.Furthermore,the subsequent algorithms are often based on complex mathematics leading to clinician hesitancy to embrace such technologies.Finally,we highlight the need for robust political and regulatory frameworks in this area to achieve the trust and approval of clinicians and patients to implement this transformational technology。

Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease

Background Since early December 2019,the 2019 novel coronavirus disease(COVID-19)has caused pneumonia epidemic in Wuhan,Hubei province of China.This study aimed to investigate the factors affecting the progression of pneumonia in COVID-19 patients.Associated results will be used to evaluate the prognosis and to find the optimal treatment regimens for COVID-19 pneumonia.Methods Patients tested positive for the COVID-19 based on nucleic acid detection were included in this study.Patients were admitted to 3 tertiary hospitals in Wuhan between December 30,2019,and January 15,2020.Individual data,laboratory indices,imaging characteristics,and clinical data were collected,and statistical analysis was performed.Based on clinical typing results,the patients were divided into a progression group or an improvement/stabilization group.Continuous variables were analyzed using independent samples t-test or Mann-Whitney U test.Categorical variables were analyzed using Chi-squared test or Fisher’s exact test.Logistic regression analysis was performed to explore the risk factors for disease progression.Results Seventy-eight patients with COVID-19-induced pneumonia met the inclusion criteria and were included in this study.Efficacy evaluation at 2 weeks after hospitalization indicated that 11 patients(14.1%)had deteriorated,and 67 patients(85.9%)had improved/stabilized.The patients in the progression group were significantly older than those in the disease improvement/stabilization group(66[51,70]vs.37[32,41]years,U=4.932,P=0.001).The progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilization group(27.3%vs.3.0%,χ^2=9.291,P=0.018).For all the 78 patients,fever was the most common initial symptom,and the maximum body temperature at admission was significantly higher in the progression group than in the improvement/stabilization group(38.2[37.8,38.6]vs.37.5[37.0,38.4]°C,U=2.057,P=0.027).Moreover,the proportion of patients with respiratory failure(54.5%vs.20.9%,χ^2=5.611,P=0.028)and respiratory rate(34[18,48]vs.24[16,60]breaths/min,U=4.030,P=0.004)were significantly higher in the progression group than in the improvement/stabilization group.C-reactive protein was significantly elevated in the progression group compared to the improvement/stabilization group(38.9[14.3,64.8]vs.10.6[1.9,33.1]mg/L,U=1.315,P=0.024).Albumin was significantly lower in the progression group than in the improvement/stabilization group(36.62±6.60 vs.41.27±4.55 g/L,U=2.843,P=0.006).Patients in the progression group were more likely to receive high-level respiratory support than in the improvement/stabilization group(χ^2=16.01,P=0.001).Multivariate logistic analysis indicated that age(odds ratio[OR],8.546;95%confidence interval[CI]:1.628-44.864;P=0.011),history of smoking(OR,14.285;95%CI:1.577-25.000;P=0.018),maximum body temperature at admission(OR,8.999;95%CI:1.036-78.147,P=0.046),respiratory failure(OR,8.772,95%CI:1.942-40.000;P=0.016),albumin(OR,7.353,95%CI:1.098-50.000;P=0.003),and C-reactive protein(OR,10.530;95%CI:1.224-34.701,P=0.028)were risk factors for disease progression.Conclusions Several factors that led to the progression of COVID-19 pneumonia were identified,including age,history of smoking,maximum body temperature at admission,respiratory failure,albumin,and C-reactive protein.These results can be used to further enhance the ability of management of COVID-19 pneumonia.

Altered diaphragmatic contractile properties after high airway pressure controlled mechanical ventilation

Acute respiratory failure is the most frequent indication for the application of mechanical ventilation. As commonly used in clinical settings, lung protective strategies and recruitment manoeuvres are applications of higher than normal airway pressure to open the collapsed alveoli and prevent lung atelectasis caused by minimal vital ventilation. Under those conditions, we pay more attention to the lung injury and circulatory failure,

疑似肺栓塞的诊断策略:系统性综述和汇总分析

目的:评估肺栓塞诊断策略的似然比 (likelihood ratios),并通过验前概率(pretest probability)来决定其临床应用价值。数据来源:通过检索Medline,Embase, Pascal Biomed等网络资源,结合人工检索查找 1990年1月至2003年9月期间发表的文章。研究选择:选择评估确诊或排除肺栓塞的诊断性检查的研究。数据提取:确诊肺栓塞诊断策略的阳性似然比,排除肺栓塞诊断策略的阴性似然比。数据综合:1012篇文章中共有48篇入选。诊断性检查的阳性似然比为:肺通气灌注扫描呈高度可能为18．3(95％置信区间为10．3- 32．5),螺旋CT为24．1(12．4-46．7),下肢静脉超声为16．2(5．6-46．7)。如果患者具有中度或高度的肺栓塞验前概率,那么其验后概率将高于 85％。阴性似然比为:肺通气灌注扫描正常或接近正常为0．05(0．03-0．10);螺旋CT和超声波检查均阴性为0．04(0．03-0．06);定量酶联免疫吸附试验法所测定的D-dimer浓度小于500μg／L 的为0．08(0．04-0．18),如果肺栓塞验前概率为低度或中度,那么其验后概率则低于5％。然而,单纯螺旋CT、肺通气灌注扫描呈低度可能、磁共振血管造影、乳胶凝集法(latex)定量测定D- dimer以及全血凝集法测定D-dimer试验的阴性似然比也是较高的,从而只能排除那些肺栓塞验前概率低的诊断。结论:对于疑似肺栓塞的患者,各种诊断性检查的准确性差异很大。尽管如此,我们还是可以评估每一项确认或排除肺栓塞试验或策略的验前概率的范围。