Therapeutic effects of adriamycin combined with high-intensity focused ultrasound on osteosarcoma.

J BUON. 2019 Mar-Apr;24(2):826-831

Authors: Wang C

Abstract
PURPOSE: To analyze the efficacy of adriamycin (ADM) combined with high-intensity focused ultrasound (HIFU) in patients with osteosarcoma.
METHODS: A total of 72 patients with osteosarcoma were selected and divided into the control group (n=36) and the observation group (n=36). Patients in the control group were treated with ADM, while those in the observation group received HIFU in addition to ADM. The efficacy and adverse reactions in the observation and control group were compared.
RESULTS: The response rate and disease control rate in the observation group were significantly higher than those in the control group (p<0.05). No significant difference was found in the survival rate at year 1 after treatment between the two groups, but the observation group had overtly higher survival rates at years 2 and 3 after treatment in comparison with the control group (p<0.05). There was no obvious difference in the incidence rate of adverse reactions between the observation and control group. After treatment, the levels of serum tumor necrosis factor-alpha (TNF-α), interleukin-2 (IL-2) and IL-8 in the observation group were clearly higher than those in the control group. Serum alkaline phosphatase (ALP) and creatinine (Cr) in the observation and control group showed no significant differences. Compared with the control group, ALP level was significantly decreased in the observation group (p<0.05). The limb function and psychological behavior after treatment in the observation group were significantly superior to those in the control group (p<0.05).
CONCLUSIONS: The application of ADM combined with HIFU is conducive to improving efficacy on osteosarcoma, prolonging survival and improving prognosis.

PMID: 31128042 [PubMed - indexed for MEDLINE]

A validation sampling approach for consistent estimation of adverse drug reaction risk with misclassified right-censored survival data.

Stat Med. 2018 11 30;37(27):3887-3903

Authors: Gravel CA, Dewanji A, Farrell PJ, Krewski D

Abstract
Patient electronic health records, viewed as continuous-time right-censored survival data, can be used to estimate adverse drug reaction risk. Temporal outcome misclassification may occur as a result of errors in follow-up. These errors can be due to a failure to observe the incidence time of the adverse event of interest (due to misdiagnosis or nonreporting, etc) or an actual misdiagnosis of a competing adverse event. As the misclassifying event is often unobservable in the original data, we apply an internal validation sampling approach to produce consistent estimation in the presence of such errors. We introduce a univariate survival model and a cause-specific hazards model in which misclassification may also manifest as a diagnosis of an alternate adverse health outcome other than that of interest. We develop a method of maximum likelihood estimation of the model parameters and establish consistency and asymptotic normality of the estimators using standard results. We also conduct simulation studies to numerically investigate the finite sample properties of these estimators and the impact of ignoring the misclassification error.

PMID: 30084171 [PubMed - indexed for MEDLINE]

Phlegmonous gastritis in a patient with mixed-phenotype acute leukemia in the neutropenia phase during chemotherapy: A case report.

Medicine (Baltimore). 2019 Nov;98(45):e17777

Authors: Shi D, He J, Lv M, Liu R, Zhao T, Jiang Q

Abstract
RATIONALE: Phlegmonous gastritis is a rare bacterial infection of the gastric wall with high mortality. However, diagnosis of phlegmonous gastritis is difficult and standard treatment remains unestablished.
PATIENT CONCERNS: We report a 33-year-old male patient with mixed-phenotype acute leukemia who developed acute phlegmonous gastritis during the neutropenia phase on induction chemotherapy and was successfully treated.
DIAGNOSES: The patient was diagnosed with phlegmonous gastritis, which might be caused by Stenotrophomonas maltophilia on the basis of clinical manifestation, physical examination, enhanced computed tomography scan, histological finding, and microorganism culture of biopsied specimen in endoscopy.
INTERVENTIONS: The patient was treated with gastrointestinal decompression and broad-spectrum antibiotics.
OUTCOMES: He recovered from phlegmonous gastritis and received the 2nd cycle of chemotherapy with no complaint of abdominal discomfort.
LESSONS: Early recognition and proper management including broad-spectrum antibiotics are key approaches to phlegmonous gastritis.

PMID: 31702630 [PubMed - indexed for MEDLINE]

Real-world treatment patterns and adverse events in metastatic renal cell carcinoma from a large US claims database.

BMC Cancer. 2019 Jun 07;19(1):548

Authors: Pal S, Gong J, Mhatre SK, Lin SW, Surinach A, Ogale S, Vohra R, Wallen H, George D

Abstract
BACKGROUND: Vascular endothelial growth factor (VEGF), tyrosine kinase (TK) and mechanistic target of rapamycin kinase (mTOR) inhibitors are common first-line (1 L) treatments for metastatic renal cell carcinoma (mRCC). Despite treatment availability, the 5-year survival rate in patients diagnosed at the metastatic stage is only ≈ 10%. To gain contemporary insights into RCC treatment trends that may inform clinical, scientific and payer considerations, treatment patterns and adverse events (AEs) associated with 1 L therapy were examined in a retrospective, longitudinal, population-based, observational study of patients with mRCC.
METHODS: US administrative claims data (Truven Health MarketScan Commercial Databases) were used to assess trends in 1 L treatment initiation in mRCC (2006-2015) and characterize patterns of individual 1 L treatments, baseline characteristics, comorbidities and treatment-related AEs from 2011 through 2015. Outcomes were evaluated by drug class and route of administration.
RESULTS: Ten-year trend analysis (n = 4270) showed that TK/VEGF-directed therapy rapidly became more common than mTOR-directed therapy, and oral treatments were favored over intravenous (IV) treatments. Overall, 1992 eligible patients initiated 1 L treatment for mRCC from 2011 through 2015: 1752 (88%) received TK/VEGF-directed agents and 233 (12%) received mTOR-directed agents; 1674 (84%) received oral treatments, and 318 (16%) received IV treatments. The most common 1 L treatment was sunitinib (n = 849), followed by pazopanib (n = 631), temsirolimus (n = 157) and bevacizumab (n = 154). Patient characteristics and comorbidities, including age, diabetes and congestive heart failure, were independent predictors of 1 L mRCC treatment choice. The three most common potentially 1 L treatment-related AEs were nausea/vomiting (128.2 per 100 patient-years [PY]), hypertension (69 per 100 PY) and renal insufficiency (44.6 per 100 PY). A wide variety of agents were used as second-line (2 L) therapy. Substantial latency of onset was observed for several potentially treatment-related toxicities in patients treated with TK/VEGF- or mTOR-directed agents.
CONCLUSIONS: In the US, 1 L TK/VEGF inhibitor uptake in recent years appears largely in line with national approvals and guidelines, with varied 2 L agent use. Although retrospective evaluation of claims data cannot assess underlying causality, insights from these real-world RCC treatment and AE patterns will be useful in informing medical and payer decisions.

PMID: 31174493 [PubMed - indexed for MEDLINE]

Differential completeness of spontaneous adverse event reports among hospitals/clinics, pharmacies, consumers, and pharmaceutical companies in South Korea.

PLoS One. 2019;14(2):e0212336

Authors: Oh IS, Baek YH, Kim HJ, Lee M, Shin JY

Abstract
The differential pattern and characteristics of completeness in adverse event (AE) reports generated by hospitals/clinics, pharmacies, consumer and pharmaceutical companies remain unknown. Thus, we identified the characteristics of complete AE reports, compared with those of incomplete AE reports, using a completeness score. We used Korea Institute of Drug Safety and Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD) between January 1, 2016 and December 31, 2016. The completeness score was determined out of a total of 100 points, based on the presence of information on temporal relationships, age and sex of patients, AE progress, name of reported medication, reporting group by profession, causality assessment, and informational text. AE reports were organized into four groups based on affiliation: hospitals/clinics, pharmacies, consumers, and pharmaceutical companies. Affiliations that had median completeness scores greater than 80 points were classified as 'well-documented' and these reports were further analyzed by logistic regression to estimate the adjusted odds ratios and 95% confidence intervals. We examined 228,848 individual reports and 735,745 drug-AE combinations. The median values of the completeness scores were the highest for hospitals/clinics (95 points), followed by those for consumers (85), pharmacies (75), and manufacturers (72). Reports with causality assessment of 'certain', 'probable', or 'possible' were more likely to be 'well-documented' than reports that had causality assessments of 'unlikely'. Serious reports of AEs were positively associated with 'well-documented' reports and negatively associated with hospitals/clinics.

PMID: 30763386 [PubMed - indexed for MEDLINE]

Drug-Drug Interactions (DDIs) in Psychiatric Practice, Part 2: Strategies to Minimize Adverse Outcomes From Unintended DDIs.

J Psychiatr Pract. 2018 09;24(5):341-347

Authors: Preskorn SH

Abstract
This column is the second in a series exploring drug-drug interactions (DDIs) with a special emphasis on psychiatric medications. The first column in this series discussed why patients being treated with psychiatric medications are at increased risk for taking multiple medications and thus experiencing DDIs and how to recognize such DDIs, and strategies for avoiding them. This second column in the series discusses strategies for minimizing adverse outcomes from such unintended DDIs. Given the huge and rapidly increasing number of available prescription and over-the-counter medications as well as nutritional supplements, the author recommends that all prescribers develop a personal formulary of ∼30 drugs that they use in everyday practice and with which they are intimately familiar. It is recommended that their knowledge of these drugs include both their generic and brand names (to avoid confusion leading to prescription of the wrong drugs), routinely used doses, pharmacokinetics including half-lives, pharmacodynamics including mechanism(s) of action and binding profile for specific receptors, adverse effect profiles, potential DDIs, and the evolving research literature on these agents. The author stresses the value of establishing a therapeutic alliance involving the patient and the people around him or her (eg, prescribers, family members, pharmacists, nurse practitioners, home health professionals, friends when appropriate) to promote the patient's understanding of and adherence to treatment. It is also important to establish a therapeutic goal with a specific time expectation (eg, reduction in depressive symptoms within 4 wk), after which the prescriber should discuss adherence with the patient and significant others, consider a dose adjustment, or discontinue the drug after an adequate therapeutic trial or the development of an adverse effect that outweighs any benefit the drug may be having. The author outlines major principles for avoiding adverse DDIs and includes a table of online resources that provide information concerning different types of DDIs. The column ends with a discussion of limitations of currently available drug alert software programs and information on how and where to report adverse drug reactions.

PMID: 30427821 [PubMed - indexed for MEDLINE]

Drug-drug Interactions in Psychiatric Practice, Part 1: Reasons, Importance, and Strategies to Avoid and Recognize Them.

J Psychiatr Pract. 2018 07;24(4):261-268

Authors: Preskorn SH

Abstract
This column begins a series exploring drug-drug interactions (DDIs) with a special emphasis on psychiatric medications. As explained in this column, this topic is important for multiple reasons. First, a large percentage of the population is receiving psychiatric medications. Second, these patients are likely to be on multiple medications which means that they are at risk for an adverse DDI. Third, DDIs may occur but not be recognized even though they have significant health care consequences for the patient. Fourth, these consequences can range from a catastrophic outcome to more everyday clinical problems involving a myriad of presentations as enumerated in this column. Also discussed in this column is the fact that all drugs, including psychiatric medications, interact on the basis of their pharmacodynamics and pharmacokinetics rather than their therapeutic use. Therefore, psychiatric medications may interact with medications prescribed for nonpsychiatric reasons as well as with other psychiatric medications. Tables are included that explain reasons for multiple medication use and principles to follow to minimize the risk of adverse DDIs.

PMID: 30427809 [PubMed - indexed for MEDLINE]

Long-term (52-week) efficacy and safety of ipragliflozin add-on therapy to insulin in Japanese patients with type 1 diabetes mellitus: An uncontrolled, open-label extension of a phase 3 study.

J Diabetes Investig. 2019 Nov 19;:

Authors: Kaku K, Isaka H, Sakatani T, Toyoshima J

Abstract
AIMS/INTRODUCTION: To assess the long-term (52-week) efficacy and safety of ipragliflozin in insulin-treated Japanese patients with type 1 diabetes mellitus (T1DM) and inadequate glycemic control.
MATERIALS AND METHODS: In this 28-week, open-label extension of a multicenter, randomized, placebo-controlled, 24-week phase 3 study, ipragliflozin recipients continued treatment (50 mg, once daily) and placebo recipients were switched to once-daily 50 mg ipragliflozin at the start of the extension period. The ipragliflozin dose could be increased to 100 mg if warranted. The primary endpoint was change in glycated hemoglobin (HbA1c); secondary endpoints were change in insulin dose and body weight. Safety outcomes were monitored as treatment-emergent adverse events (TEAEs).
RESULTS: Fifty-three (placeboipragliflozin) and 108 (ipragliflozin) patients completed the open-label extension (treatment period 2), with 24 and 44 patients, respectively, receiving dose increases. From baseline to end of treatment, the overall mean change (standard deviation) in HbA1c was -0.33% (0.72) (-3.7 mmol/mol [7.9]), with changes in basal, bolus and total insulin doses of -3.76 (3.85), -2.51 (7.08) and -6.27 (8.16) IU, respectively. No serious drug-related TEAEs or deaths were reported. TEAEs leading to study discontinuation occurred in 0 and 3 (2.6%) patients in the placeboipragliflozin and ipragliflozin groups, respectively; all were considered drug-related. There were no cases of severe hypoglycemia or diabetic ketoacidosis and no safety concerns related to dose increase.
CONCLUSIONS: Efficacy and safety of 50 mg, once-daily ipragliflozin in insulin-treated T1DM patients were confirmed in this long-term, open-label extension study. No safety concerns were attributed to a dose increase to 100 mg.

PMID: 31743569 [PubMed - as supplied by publisher]

On Drugs: Preemption, Presumption, and Remedy.

J Leg Med. 2018 Jul-Dec;38(3-4):365-385

Authors: McCuskey EY

PMID: 31307348 [PubMed - indexed for MEDLINE]

Acute Tubulointerstitial Nephritis: A Case Report on Rare Adverse Effect of Pembrolizumab.

Medicina (Kaunas). 2019 May 21;55(5):

Authors: Basnet S, Dhital R, Tharu B

Abstract
Pembrolizumab is a novel immune checkpoint inhibitor approved for use in non-small cell lung carcinoma. There have been a few cases that have associated adverse renal outcomes with pembrolizumab. We present a case of acute kidney injury in a patient on pembrolizumab who was noted to have acute tubulointerstitial nephritis on renal biopsy. Pembrolizumab was discontinued and the patient was started on long-term corticosteroids with a taper. Her renal function improved partially with treatment.

PMID: 31117208 [PubMed - indexed for MEDLINE]

The Utilization of Mu-Opioid Receptor Biased Agonists: Oliceridine, an Opioid Analgesic with Reduced Adverse Effects.

Curr Pain Headache Rep. 2019 Mar 18;23(5):31

Authors: Urits I, Viswanath O, Orhurhu V, Gress K, Charipova K, Kaye AD, Ngo A

Abstract
PURPOSE OF REVIEW: The purpose of this review is to summarize the current understanding of opioid pathways in mediating and/or modulating analgesia and adverse effects. Oliceridine is highlighted as a novel mu-opioid receptor agonist with selective activation of G protein and β-arrestin signaling pathways.
RECENT FINDINGS: Oliceridine (TRV130; [(3-methoxythiophen-2-yl)methyl]({2-[(9R)-9-(pyridin-2-yl)-6-oxaspiro[4.5]decan-9-yl]ethyl})amine) is a novel MOR agonist that selectively activates G protein and β-arrestin signaling pathways. A growing body of evidence suggests that compared to existing MOR agonists, Oliceridine and other G protein-selective modulators may produce therapeutic analgesic effects with reduced adverse effects. Oliceridine provides analgesic benefits of a pure opioid agonist while limiting related adverse effects mediated through the β-arrestin pathway. Recent insights into the function and structure of G protein-coupled receptors has led to the development of novel analgesic therapies.

PMID: 30880365 [PubMed - indexed for MEDLINE]

Multidisciplinary intervention to improve medication safety in nursing home residents: protocol of a cluster randomised controlled trial (HIOPP-3-iTBX study).

BMC Geriatr. 2019 01 25;19(1):24

Authors: Krause O, Wiese B, Doyle IM, Kirsch C, Thürmann P, Wilm S, Sparenberg L, Stolz R, Freytag A, Bleidorn J, Junius-Walker U, HIOPP-3-iTBX study group

Abstract
BACKGROUND: Medication safety is an important health issue for nursing home residents (NHR). They usually experience polypharmacy and often take potentially inappropriate medications (PIM) and antipsychotics. This, coupled with a frail health state, makes NHR particularly vulnerable to adverse drug events (ADE). The value of systematic medication reviews and interprofessional co-operation for improving medication quality in NHR has been recognized. Yet the evidence of a positive effect on NHR' health and wellbeing is inconclusive at this stage. This study investigates the effects of pharmacists' medication reviews linked with measures to strengthen interprofessional co-operation on NHR' medication quality, health status and health care use.
METHODS: Pragmatic cluster randomised controlled trial in nursing homes in four regions of Germany. A total of 760 NHR will be recruited. Inclusion: NHR aged 65 years and over with an estimated life expectancy of at least six months. Intervention with four elements: i) introduction of a pharmacist's medication review combined with a communication pathway to the prescribing general practitioners (GPs) and nursing home staff, ii) facilitation of change in the interprofessional cooperation, iii) educational training and iv) a "toolbox" to facilitate implementation in daily practice.
ANALYSIS: primary outcome - proportion of residents receiving PIM and ≥ 2 antipsychotics at six months follow-up. Secondary outcomes - cognitive function, falls, quality of life, medical emergency contacts, hospital admissions, and health care costs.
DISCUSSION: The trial assesses the effects of a structured interprofessional medication management for NHR in Germany. It follows the participatory action research approach and closely involves the three professional groups (nursing staff, GPs, pharmacists) engaged in the medication management. A handbook based on the experiences of the trial in nursing homes will be produced for a rollout into routine practice in Germany.
TRIAL REGISTRATION: Registered in the German register of clinical studies (DRKS, study ID DRKS00013588 , primary register) and in the WHO International Clinical Trials Registry Platform (secondary register), both on 25th January 2018.

PMID: 30683060 [PubMed - indexed for MEDLINE]

Approval of New Opioid Raises Concerns.

Am J Nurs. 2019 02;119(2):20-21

Authors: Aschenbrenner DS

Abstract

PMID: 30681473 [PubMed - indexed for MEDLINE]

Manifold regularized matrix factorization for drug-drug interaction prediction.

J Biomed Inform. 2018 12;88:90-97

Authors: Zhang W, Chen Y, Li D, Yue X

Abstract
Drug-drug interaction (DDI) prediction is one of the most important tasks in drug discovery. Prediction of potential DDIs helps to reduce unexpected side effects in the lifecycle of drugs, and is important for the drug safety surveillance. Here, we formulate the drug-drug interaction prediction as a matrix completion task, and project drugs in the interaction space into a low-dimensional space. We consider drug features, i.e., substructures, targets, enzymes, transporters, pathways, indications, side effects, and off side effects, to calculate drug-drug similarities, and assume them as manifolds in feature spaces. In this paper, we present a novel computational method named "Manifold Regularized Matrix Factorization" (MRMF) to predict potential drug-drug interactions, by introducing the drug feature-based manifold regularization into the matrix factorization. In the computational experiments, the MRMF models, which utilize known drug-drug interactions and the drug feature-based manifold, produce the area under precision-recall curves (AUPR) up to 0.7963. We test manifold regularizations based on different drug features, and the MRMF models can produce robust performances. Compared with other state-of-the-art methods, the MRMF models can produce better performances in the cross validation and case study. The manifold regularization is the critical factor for the high-accuracy performances of our method. MRMF is promising and effective for the prediction of drug-drug interactions.

PMID: 30445219 [PubMed - indexed for MEDLINE]

PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.

J Biomed Inform. 2018 11;87:96-107

Authors: Jang G, Lee T, Hwang S, Park C, Ahn J, Seo S, Hwang Y, Yoon Y

Abstract
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected actions of the derived candidate drugs. In order to overcome these limitations, computational methods for predicting the therapeutic effects and side effects have been proposed. In particular, text mining is a widely used technique in the field of systems biology, because it can discover hidden relationships between drugs, genes and diseases from a large amount of literature data. Compared with in vivo/in vitro experiments, text mining derives meaningful results with less time and cost. In this study, we propose an algorithm for predicting novel drug-phenotype associations and drug-side effect associations using topic modeling and natural language processing (NLP). We extract sentences in which drugs and genes co-occur from the abstracts of the literature and identify words that describe the relationship between them using NLP. Considering the characteristics of the identified words, we determine if the drug has an up-regulation effect or a down-regulation effect on the gene. Based on genes that affect drugs and their regulatory relationships, we group the frequently occurring genes and regulatory relationships into topics, and build a drug-topic probability matrix by calculating the score that the drug will have a topic using topic modeling. Using the matrix, a classifier is constructed for predicting the novel indications and side effects of drugs considering the characteristics of known drug-phenotype associations or drug-side effect associations. The proposed method predicts both indications and side effects with a single algorithm, and it can exclude drugs with serious side effects or side effects that patients do not want to experience from among the candidate drugs provided for the treatment of the phenotype. Furthermore, lists of novel candidate drugs for phenotypes and side effects can be continuously updated with our algorithm every time a document is added. More than a thousand documents are produced per day, and it is possible for our algorithm to efficiently derive candidate drugs because it requires less cost than the existing drug repositioning methods. The resource of PISTON is available at databio.gachon.ac.kr/tools/PISTON.

PMID: 30268842 [PubMed - indexed for MEDLINE]

From narrative descriptions to MedDRA: automagically encoding adverse drug reactions.

J Biomed Inform. 2018 08;84:184-199

Authors: Combi C, Zorzi M, Pozzani G, Moretti U, Arzenton E

Abstract
CONTEXT: The collection of narrative spontaneous reports is an irreplaceable source for the prompt detection of suspected adverse drug reactions (ADRs). In such task qualified domain experts manually revise a huge amount of narrative descriptions and then encode texts according to MedDRA standard terminology. The manual annotation of narrative documents with medical terminology is a subtle and expensive task, since the number of reports is growing up day-by-day.
OBJECTIVES: Natural Language Processing (NLP) applications can support the work of people responsible for pharmacovigilance. Our objective is to develop NLP algorithms and tools for the detection of ADR clinical terminology. Efficient applications can concretely improve the quality of the experts' revisions. NLP software can quickly analyze narrative texts and offer an encoding (i.e., a list of MedDRA terms) that the expert has to revise and validate.
METHODS: MagiCoder, an NLP algorithm, is proposed for the automatic encoding of free-text descriptions into MedDRA terms. MagiCoder procedure is efficient in terms of computational complexity. We tested MagiCoder through several experiments. In the first one, we tested it on a large dataset of about 4500 manually revised reports, by performing an automated comparison between human and MagiCoder encoding. Moreover, we tested MagiCoder on a set of about 1800 reports, manually revised ex novo by some experts of the domain, who also compared automatic solutions with the gold reference standard. We also provide two initial experiments with reports written in English, giving a first evidence of the robustness of MagiCoder w.r.t. the change of the language.
RESULTS: For the current base version of MagiCoder, we measured an average recall and precision of 86.9% and 91.8%, respectively.
CONCLUSIONS: From a practical point of view, MagiCoder reduces the time required for encoding ADR reports. Pharmacologists have only to review and validate the MedDRA terms proposed by the application, instead of choosing the right terms among the 70 K low level terms of MedDRA. Such improvement in the efficiency of pharmacologists' work has a relevant impact also on the quality of the subsequent data analysis. We developed MagiCoder for the Italian pharmacovigilance language. However, our proposal is based on a general approach, not depending on the considered language nor the term dictionary.

PMID: 29981491 [PubMed - indexed for MEDLINE]

[Bonzai, lead and bath salt-poisoning with new and old drugs : Synthetic amphetamines, cathinones, cannabinoids and opioids-an overview].

Med Klin Intensivmed Notfmed. 2019 Nov;114(8):684-692

Authors: Strube J, Schaper A

Abstract
BACKGROUND: There has been an increase in the number of serious poisonings and deaths after the use of new psychoactive substances (NPS). These are usually bought online: sometimes legally, often illegally or "in the grey area".
OBJECTIVES: Characteristics of different NPS. Legal status concerning the New Psychoactive Substances Act (NpSG). Risk assessment of several substance groups, possible complications of acute poisonings, therapeutic recommendations.
MATERIALS AND METHODS: Literature search and evaluation of own case data. Discussion of official statistics, literature and expert recommendations.
RESULTS: There has been an increase in the number of poisonings with NPS and associated deaths: in Germany in 2016 there were 98 deaths compared to 39 deaths in 2015. Serious acute poisonings require intensive care therapy. Therapy is usually symptomatic. Referring to the drugs discussed in this article an antidote is only available for the synthetic opioid: naloxone.
CONCLUSIONS: With the NpSG being in force since the end of 2016, the number of severe intoxications with NPS will probably (not immediately) decrease. It remains to be seen if the increasing number of fatalities will decrease again. Consultation with a poison centre is recommended in cases of suspected intoxication with NPS. Diagnosis and therapy can then be discussed. Toxicological screening may be false negative because many synthetic drugs are not detected in standard analysis. The NPS often require a special analysis.

PMID: 29404633 [PubMed - indexed for MEDLINE]

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

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14 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("drug-induced" OR "drug-related") AND ("adverse events" OR "side effects" OR "side-effects")

These pubmed results were generated on 2019/11/16

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13 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("drug-induced" OR "drug-related") AND ("adverse events" OR "side effects" OR "side-effects")

These pubmed results were generated on 2019/11/16

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.