ADR Detection Research Articles

A study to Monitor Adverse drug reactions in a patients of Chronic Obstructive pulmonary Disease

Background: Inappropriate drug usage may preclude ideal benefit due to increased medical cost, adverse effects and mortality. Therefore drug utilization studies have become a plausible means in evaluating the healthcare systems. COPD management usually involves more than one drug which may escalate the risk of ADEs (adverse drug events). The present study aimed at assessing the current drug practice and ADEs in COPD management in ICU. Material and Methods: A prospective, single centered, observational and open labeled study was carried out in Department of Pulmonary Medicine and Pharmacology, Tertiary Care Teaching Hospital. The patient population was broadly divided into four categories based on diagnosis ‑ chronic obstructive pulmonary disease, Infections, Asthma and Others. Suspected ADRs were reported, analyzed, and causality assessment was carried out using Naranjo’s algorithm scal0065. Results: In our study, most important causative drug was Budesonide (11.1%). Causality assessment of ADR by Naranjo’s algorithm showed 11.9% probable and 88.1% possible reactions. According to WHO-UMC scale, 85.9% reactions are possible, 11.1% are probable, and 3% are unlikely. Among the 270 ADR reported, the most common ADR was oral thrush which accounted for 11.1% (n = 30) of the reported cases, followed by palpitation 11.1% (n = 30), sore throat 20 (7.4%), dizziness 17 (6.3%) cases, and headache 20 (7.4%) of reported ADR cases. Conclusion: Many research have been conducted separately on various respiratory diseases such as COPD, tuberculosis, asthma, respiratory tract infections (upper/lower), and so on. However, this study included some of the most common diseases in this field, such as COPD, tuberculosis, and respiratory tract infections. A routine patient follow-up is needed for the early detection and prevention of ADRs in order to improve patient adherence to drug therapy and provide improved drug therapy by avoiding associated morbidity and mortality.

Precision fluoropyrimidines dosing in a compound heterozygous variant carrier of the DPYD gene: a case report.

Fluoropyrimidines (FPs) form still nowadays the backbone of chemotherapic schemes in colorectal cancer (CRC). Inter-patient variability of the toxicity profile of FPs may be partially accounted for by variable expression of dihydropyrimidine dehydrogenase (DPD). DPD rate activity is genetically determined by its extremely polymorphic coding gene DPYD. In spite of pharmacogenetic guideline-directed-dosing of FPs based regimens treating carrier of multiple variants of DPYD gene remains still challenging. We present a case of a 48-year-old Caucasian man, compound heterozygous variant carrier of the DPYD gene (HapB3 and c.2194G>A) who had a diagnosis of adenocarcinoma of the left colon and was safely treated with a pharmacogenetic-guided 25% dose reduction of the standard CAP adjuvant treatment. Compound heterozygosis may have been responsible for an earlier over exposure to CAP resulting into low-grade toxicity with an anticipated median time to toxicity of the c.2194G>A variant to the 4th vs. 6th cycles. Some haplotypes of DPYD variants may have an advantage in terms of survival compared to wild-type patients. Our patient may also have benefitted from compound heterozygosis, as shown by no evidence of disease (NED) at 6-month follow-up. Pharmacogenetic-guided dosing of DPYD intermediate metabolizer compound heterozygous HapB3 and c.2194G>A variant carries should be managed by a multidisciplinary team with a dose reduction ranging from 25 to 50% to maintain effectiveness and close clinical monitoring for early detection of ADRs.

Pattern of adverse drug reactions with chemotherapeutic drugs in a tertiary care hospital of North India: a retrospective study

Background: Adverse drug reactions are important causes of mortality and morbidity in the patients. Early detection, evaluation and monitoring of ADRs is essential to improve public health. Methods: This was an observational, non-interventional and retrospective study conducted at the ADR monitoring centre of a tertiary care hospital of North India. Suspected ADR forms reported over a period of 4 years involving at least one chemotherapeutic drug with at least one dose were analyzed. Results: A total of 261 chemotherapeutic drugs associated ADRs were analyzed. Out of these, maximum numbers of ADRs were reported by males (54%). Maximum reporting was done by Skin and VD department (37.93%). Causality assessment was probable in maximum number of cases (54%). Most common ADRs were skin rashes (21.46%), followed by jaundice, urticaria and fixed drug eruptions. Maximum ADRs were suspected to be caused by Anti tubercular drugs (31.42%) followed by anticancer drugs (14.56%). Conclusions: ADRs due to antibiotics and anticancer drugs is a significant health problem.

An inter-professional student-run medication review programme. Reducing adverse drug reactions in a memory outpatient clinic: a controlled clinical trial

ABSTRACT Background We investigated if the addition of an inter-professional student-led medication review team (ISP-team) to standard care can increase the number of detected ADRs and reduce the number of ADRs 3 months after an outpatient visit. Research design and methods In this controlled clinical trial, patients were allocated to standard care (control group) or standard care plus the ISP team (intervention group). The ISP team consisted of medical and pharmacy students and student nurse practitioners. The team performed a structured medication review and adjusted medication to reduce the number of ADRs. Three months after the outpatient visit, a clinical pharmacologist who was blinded for allocation performed a follow-up telephone interview to determine whether patients experienced ADRs. Results During the outpatient clinic visit, significantly more (p < 0.001) ADRs were detected in the intervention group (n = 48) than in the control group (n = 10). In both groups, 60–63% of all detected ADRs were managed. Three months after the outpatient visit, significantly fewer (predominantly mild and moderately severe) ADRs related to benzodiazepine derivatives and antihypertensive causing dizziness were detected in the patients of the intervention group. Conclusions An ISP team in addition to standard care increases the detection and management of ADRs in elderly patients resulting in fewer mild and moderately severe ADRs.

A Prospective Study on Usage Pattern of Corticosteroids in a Tertiary Care Hospital

Rational use of corticosteroids is very essential for improving patient safety on long term use. The present study aimed to study the prescribing usage pattern of corticosteroids in a tertiary care hospital. A prospective observational study was conducted in the department of dermatology, gynecology and general medicine in a tertiary care teaching hospital for the period of 6 months (August-February). All patients receiving any category of Steroid therapy were included and the prescribing and tapering pattern of steroids were reviewed. Prescribing pattern was observed and analysed in 132 participants during the study period. Cases were collected from the departments of Dermatology, General Medicine, Pediatrics and Gynecology in Gandhi Hospital, Secunderabad. All the prescriptions containing steroids were included in this study and the parameters evaluated were gender distribution, age of the patients, types of steroids according to the route of administration, number of prescribed daily dose (PDD) where compared with defined daily dose (DDD). In the collected 132 cases, 162 times corticosteroids were prescribed. The steroid utilization was found to be more in female patients, the maximum number of cases with corticosteroids was found in Dermatology department (39.4%). Particularly Injection Dexamethasone (24.7%) and Tablet Prednisolone (24.7%) are mostly prescribed. Most drugs were prescribed rationally although some factors like improper history,drug administration time and tapering were deviating away from rationality. Although most of the drugs were prescribed rationally, involvement of a Clinical pharmacist in patient care can help in more rational prescribing along with prevention and early detection of ADRs which can directly promote drug safety and better patient outcomes.

Drug utilization review of corticosteroids in a tertiary care hospital of Salem District, Tamilnadu, India

Corticosteroids are widely used compounds for allergic reactions, autoimmune diseases, inflammatory conditions, hormone replacement therapy etc. Hence, with widespread use and actions, these have several interactions with drugs and diseases. The purpose of this study was to obtain information about Corticosteroids prescribing and utilization pattern, to understand the prescribing behaviour of physicians and to identify drug interactions. A retrospective observational study was conducted in the department of dermatology and general medicine in a tertiary care hospital for 6 months. All the patients receiving any category of steroid therapy were included, and the prescribing and tapering pattern of steroids were reviewed. Drug utilization pattern (DUR) was observed and analysed among 150 patients during the study period. The results revealed that steroids were prescribed for various respiratory illnesses (66%) and skin-related conditions (34%). The steroid utilization was found to be more in elderly patients, particularly in males. Intravenous administration was common in 33% of cases. Budesonide was the most commonly prescribed steroid (36%), followed by Hydrocortisone (24%) and Dexamethasone (14%). The most frequent drug-drug interaction was between Hydrocortisone and Theophylline as well as Hydrocortisone and Hypoglycaemic agents. Most drugs were prescribed rationally, although some factors like prescribing drugs in the brand name, without mentioning route of administration, frequency and dose were deviating away from rationality. Not much variation was found in the pattern of prescription amongst healthcare professionals. Although most of the drugs were prescribed rationally, the involvement of a clinical pharmacist in patient care can help in more rational prescribing along with prevention and early detection of ADRs which can directly promote drug safety and better patient outcomes.

Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection.

BackgroundAdverse drug reactions (ADRs) occur in nearly all patients on chemotherapy, causing morbidity and therapy disruptions. Detection of such ADRs is limited in clinical trials, which are underpowered to detect rare events. Early recognition of ADRs in the postmarketing phase could substantially reduce morbidity and decrease societal costs. Internet community health forums provide a mechanism for individuals to discuss real-time health concerns and can enable computational detection of ADRs.ObjectiveThe goal of this study is to identify cutaneous ADR signals in social health networks and compare the frequency and timing of these ADRs to clinical reports in the literature.MethodsWe present a natural language processing-based, ADR signal-generation pipeline based on patient posts on Internet social health networks. We identified user posts from the Inspire health forums related to two chemotherapy classes: erlotinib, an epidermal growth factor receptor inhibitor, and nivolumab and pembrolizumab, immune checkpoint inhibitors. We extracted mentions of ADRs from unstructured content of patient posts. We then performed population-level association analyses and time-to-detection analyses.ResultsOur system detected cutaneous ADRs from patient reports with high precision (0.90) and at frequencies comparable to those documented in the literature but an average of 7 months ahead of their literature reporting. Known ADRs were associated with higher proportional reporting ratios compared to negative controls, demonstrating the robustness of our analyses. Our named entity recognition system achieved a 0.738 microaveraged F-measure in detecting ADR entities, not limited to cutaneous ADRs, in health forum posts. Additionally, we discovered the novel ADR of hypohidrosis reported by 23 patients in erlotinib-related posts; this ADR was absent from 15 years of literature on this medication and we recently reported the finding in a clinical oncology journal.ConclusionsSeveral hundred million patients report health concerns in social health networks, yet this information is markedly underutilized for pharmacosurveillance. We demonstrated the ability of a natural language processing-based signal-generation pipeline to accurately detect patient reports of ADRs months in advance of literature reporting and the robustness of statistical analyses to validate system detections. Our findings suggest the important contributions that social health network data can play in contributing to more comprehensive and timely pharmacovigilance.

Improved ADR detection with machine-learning model

Improved ADR detection with machine-learning model

POLYPHARMACY INDUCED DRUG INTERACTIONS, ADVERSE DRUG REACTIONS (ADR) AND MEDICATION ERRORS IN TERTIARY CARE SOUTH INDIAN HOSPITAL

Objective: To study the pattern of drug interactions (DI) in our hospital and to identify whether it is associated with polypharmacy. To determine the level of severity of potential drug-drug interactions (PDDI), to detect, monitor and prevention of ADRs in the hospitalized patients and to identify the medication errors (ME).&#x0D; Methods: A prospective interventional study was conducted in a 300 bedded tertiary care South Indian hospital for a period of 6 mo. Prescriptions were analysed for PDDI using Micromedex software 2.2. The causality and severity of ADRs were assessed by using Naranjo’s, WHO UMC Scales and Hart wigs severity scales. ME was identified by review of patient drug charts.&#x0D; Results: Total 190 prescriptions were analyzed, in which 1028 drug interactions were seen. Out of which 718 were DDI, 198 DFI, 100 DEI, and 12 DTI were observed. More number of DI was seen in cardiovascular drugs, antibiotics followed by antacids and antiulcer agents. A total of 52 ADRs were identified in 43 patients. Diuretics, cardiovascular drugs were associated with a higher incidence of ADRs followed by Anti-Diabetic agents. 58 ME was seen in 190 prescriptions, among them omission error, prescribing errors and Wrong dose error was seen.&#x0D; Conclusion: Clinical pharmacist plays a potential role in the health care system in assisting the physician i.e. modifying the number of drugs taken, number of doses taken, medication adherence, identification of drug interactions, preventing, monitoring and detection of ADRs and identifying the medication errors.

Variable Endoscopist performance in proximal and distal adenoma detection during colonoscopy: a retrospective cohort study

BackgroundAdenoma Detection Rate (ADR) is a validated colonoscopy quality indicator. In addition to overall ADR, Distal and Proximal Adenoma Detection Rates may provide important colonoscopy quality information. The goal of this study is to determine the association between distal and proximal adenoma detection (AD) and to identify factors contributing to overall, distal, and proximal AD.MethodsThis is a retrospective cohort study of patients with a noted family history of CRC or positive fecal occult blood test who underwent a screening colonoscopy at a regional colorectal cancer (CRC) screening center between May 2009 and December 2011. Data regarding patient demographics, procedure details, endoscopist characteristics and polyp histology were captured. The main outcomes measured were overall, distal, and proximal AD.Results1907 patients were included. The median age was 60 years and 42% were male. Endoscopist median overall ADR was 25% (30% male, 21% female). Endoscopist distal ADR was only modestly associated with their proximal ADR (Spearman Rank: 0.51 p = 0.11). Highest overall ADR (29 to 45%) was found for endoscopists whose distal and proximal ADRs were above the group median. In multivariate analysis, factors associated with overall, distal, and proximal AD included age, sex, and endoscopist practicing experience.ConclusionInclusion of distal and proximal ADRs, in addition to overall ADR, in colonoscopy quality assessment provides the more accurate feedback on endoscopist performance.

Supervised signal detection for adverse drug reactions in medication dispensing data

MotivationAdverse drug reactions (ADRs) are one of the leading causes of morbidity and mortality and thus should be detected early to reduce consequences on health outcomes. Medication dispensing data are comprehensive sources of information about medicine uses that can be utilized for the signal detection of ADRs. Sequence symmetry analysis (SSA) has been employed in previous studies to detect signals of ADRs from medication dispensing data, but it has a moderate sensitivity and tends to miss some ADR signals. With successful applications in various areas, supervised machine learning (SML) methods are promising in detecting ADR signals. Gold standards of known ADRs and non- ADRs from previous studies create opportunities to take into account additional domain knowledge to improve ADR signal detection with SML. ObjectiveWe assess the utility of SML as a signal detection tool for ADRs in medication dispensing data with the consideration of domain knowledge from DrugBank and MedDRA. We compare the best performing SML method with SSA. MethodsWe model the ADR signal detection problem as a supervised machine learning problem by linking medication dispensing data with domain knowledge bases. Suspected ADR signals are extracted from the Australian Pharmaceutical Benefit Scheme (PBS) medication dispensing data from 2013 to 2016. We construct predictive features for each signal candidate based on its occurrences in medication dispensing data as well as its pharmacological properties. Pharmaceutical knowledge bases including DrugBank and MedDRA are employed to provide pharmacological features for a signal candidate. Given a gold standard of known ADRs and non-ADRs, SML learns to differentiate between known ADRs and non-ADRs based on their combined predictive features from linked sources, and then predicts whether a new case is a potential ADR signal. ResultsWe evaluate the performance of six widely used SML methods with two gold standards of known ADRs and non-ADRs from previous studies. On average, gradient boosting classifier achieves the sensitivity of 77%, specificity of 81%, positive predictive value of 76%, negative predictive value of 82%, area under precision-recall curve of 81%, and area under receiver operating characteristic curve of 82%, most of which are higher than in other SML methods. In particular, gradient boosting classifier has 21% higher sensitivity than and comparable specificity with SSA. Furthermore, gradient boosting classifier detects 10% more unknown potential ADR signals than SSA. ConclusionsOur study demonstrates that gradient boosting classifier is a promising supervised signal detection tool for ADRs in medication dispensing data to complement SSA.

Overview of post marketing aggregate reports and global regulatory requirements

Pharmacovigilance is the science that deals with the activities related to the detection, assessment, understanding, and prevention of ADRs. The scope of pharmacovigilance has evolved over time. We now recognize the importance of a systematic approach for monitoring and improving the safe use of medicines. At the level of individual case safety reports, it is not possible for marketing authorization holders (MAH) to evaluate benefit/risk ratio profile and understand the detailed safety feature of a medicinal product. In addition to submission of individual case safety reports MAH also review periodically, cumulative safety information attained from various sources and submit the findings as aggregate reports to drug regulators. Aggregate reporting is a vital tool to study benefit/risk balance of a medicinal product throughout the product’s life cycle. The timelines, frequency and exact type of aggregate report required to be submitted for the approved product varies globally amongst various drug regulatory agencies. In this review the significance, background, objectives, scope, structural components, timelines for regulatory submissions of post marketing aggregate reports viz. PSUR, PBRER, and PADER have been discussed.

Pharmacist intervention in patients receiving treatment for Chagas disease: An emerging challenge for non-endemic countries

Abstract Background Spain has the second highest number of Chagas disease-infected patients among non-endemic countries. However, there is limited knowledge about pharmacist involvement in managing patients with Chagas disease. Method A retrospective observational study was performed in two periods (before and after intervention) to describe the characteristics of patients with Chagas disease. Pharmacist intervention, based on two pharmacist-visit programs and development of information for patients, was applied to patients under pharmacological treatment in a non-endemic country. Depending on the initial results in 2010–2011, specific pharmacist attention program for patients with Chagas disease was implemented in 2012. The results of 2010–2011 (before intervention) and 2013 (after intervention) were compared. Results A high number of adverse drug reactions were reported in both periods, 50.0% (2010–2011) vs. 90.9% (2013). With regard to treatment completion, in 2010–2011, 60% achieved the treatment completion criteria (>95% days of treatment) vs. 68.2% in 2013 (p = 0.580). There was, however, a significant increase in the detection of ADRs in the second period (50.0% vs. 90.9%; p = 0.003) and an increase in the severity (75% [6/8] of uncompleted treatments were due to ADRs vs. 100% [7/7] in the first and second period, respectively). Conclusions This study was useful to provide more information about patients with Chagas disease, provide pharmacist intervention/information material to patients, and detect a point of improvement in hospital follow-up care. Although it was not possible to demonstrate it with a statistically significant result, we believe that pharmacist intervention that includes in-depth patient information about possible ADRs and their management could increase adherence and treatment completion rates. In addition, pharmacist intervention helped to better detect and control ADRs that could lead to generating better health outcomes in Chagas disease. Although our patients' health literacy was not evaluated, it would be a potential avenue for future research.

A Questionnaire Study on the Knowledge, Attitude, and Practice of Pharmacovigilance among the Medical Post Graduates in a Teaching Hospital in West Uttar Pradesh

Background: Pharmacovigilance aids in early detection of ADRs and as well as identification of various risk factors. Reporting of ADRs is crucial for the success of pharmacovigilance program. Aims/Objective: This questionnaire based study among medical resident’s aims at assessing knowledge, attitude & practice towards adverse drug reaction reporting in the teaching hospital attached to a private medical college and design methods to improve existing ADR reporting system in our setup. Methods: This study is a questionnaire based cross-sectional study. It was conducted at Teerthanker Mahaveer Medical College & research Centre, Moradabad, West Uttar Pradesh, among the first year and final year medical post graduates/PGs, by using a pre-validated, modified questionnaire on knowledge, attitude & practice. A total of 90 questionnaires were duly filled out by the post graduates. Data was analyzed by using SPSS V.20. The chi-square test was used to determine statistical significance. Results: Majority (89%) reported to have reasonable knowledge of adverse drug reactions, but reported an average degree of knowledge regarding various aspects of pharmacovigilance. 61% respondents were not aware of presence of an AMC affiliated to this hospital. Final year medical post graduates were found to have poor attitude towards acts of reporting of adverse drug reactions although they pose better knowledge regarding drug safety as well as importance of ADR reporting. Lack of training (90%) on ADR reporting was also recorded. Conclusions: This study recorded average knowledge, positive attitude towards necessity of reporting of ADRs of medical post graduates. Necessity of educational interventions to update knowledge and improve practice of ADR reporting were identified as important measures that need to be taken care of.

Impact of ‘‘Advance Patients Care Plan’’ in Cardiovascular Disorders

Background and Objective: Cardiovascular deaths and disorders have increased at a fast rate in low and middle-income countries. In India most of population pays their healthcare bills out of their own pocket, so there is always a need to reduce the economic burden on the patients. The research was conducted to implement and analyze “Advance Patients Care Plan” for cardiovascular disorders and its impact in terms of patient therapeutic outcomes. Methods: In this single blinded double arm interventional research three different strategic interventions were implemented under “Advance Patients Care Plan” namely Cost minimization by prescribing cheap brands/generics, Early ADR detection & prevention and Life style modifications. The outcomes were recorded in terms of patient’s therapeutic outcomes, quality of life and reduction in economic burden. The data was analyzed statistically. Results: The overall mean score of WHO QoL BREF questionnaire of experimental group was 58.2±8.65 which was comparatively higher than 45.95±1.08 of control group. The overall mean MLHFQ score was 38.33±6.98 and 65.67±3.75 for experimental group and control group respectively. The total cumulative therapy cost was accounted ₹ 240660 in Experimental Group whereas patients in Control Group spend ₹ 319114.80 on therapy. The Implemented ‘‘Advance Patients Care Plan’’ reduced total cost for therapy by ₹ 2615.16 for each patient. Interpretation and Conclusions: Advance Patients Care Plan in addition to treatment showed significant evidence in improvement of patients’ therapeutic outcomes, improved quality of life and reduced economic burden on the patients.

Privacy preserving data anonymization of spontaneous ADE reporting system dataset.

BackgroundTo facilitate long-term safety surveillance of marketing drugs, many spontaneously reporting systems (SRSs) of ADR events have been established world-wide. Since the data collected by SRSs contain sensitive personal health information that should be protected to prevent the identification of individuals, it procures the issue of privacy preserving data publishing (PPDP), that is, how to sanitize (anonymize) raw data before publishing. Although much work has been done on PPDP, very few studies have focused on protecting privacy of SRS data and none of the anonymization methods is favorable for SRS datasets, due to which contain some characteristics such as rare events, multiple individual records, and multi-valued sensitive attributes.MethodsWe propose a new privacy model called MS(k, θ*)-bounding for protecting published spontaneous ADE reporting data from privacy attacks. Our model has the flexibility of varying privacy thresholds, i.e., θ*, for different sensitive values and takes the characteristics of SRS data into consideration. We also propose an anonymization algorithm for sanitizing the raw data to meet the requirements specified through the proposed model. Our algorithm adopts a greedy-based clustering strategy to group the records into clusters, conforming to an innovative anonymization metric aiming to minimize the privacy risk as well as maintain the data utility for ADR detection. Empirical study was conducted using FAERS dataset from 2004Q1 to 2011Q4. We compared our model with four prevailing methods, including k-anonymity, (X, Y)-anonymity, Multi-sensitive l-diversity, and (α, k)-anonymity, evaluated via two measures, Danger Ratio (DR) and Information Loss (IL), and considered three different scenarios of threshold setting for θ*, including uniform setting, level-wise setting and frequency-based setting. We also conducted experiments to inspect the impact of anonymized data on the strengths of discovered ADR signals.ResultsWith all three different threshold settings for sensitive value, our method can successively prevent the disclosure of sensitive values (nearly all observed DRs are zeros) without sacrificing too much of data utility. With non-uniform threshold setting, level-wise or frequency-based, our MS(k, θ*)-bounding exhibits the best data utility and the least privacy risk among all the models. The experiments conducted on selected ADR signals from MedWatch show that only very small difference on signal strength (PRR or ROR) were observed. The results show that our method can effectively prevent the disclosure of patient sensitive information without sacrificing data utility for ADR signal detection.ConclusionsWe propose a new privacy model for protecting SRS data that possess some characteristics overlooked by contemporary models and an anonymization algorithm to sanitize SRS data in accordance with the proposed model. Empirical evaluation on the real SRS dataset, i.e., FAERS, shows that our method can effectively solve the privacy problem in SRS data without influencing the ADR signal strength.

Monitoring and Analysis of Adverse Drug Reactions in A Private Tertiary Care Hospital

The detection of ADRs has become increasingly significant because of introduction of a large number of potent drugs in the last two or three decades, especially antimicrobials. ADRs could be monitored through active monitoring or through voluntary reporting system in a hospital set up. This observational prospective study spread over 12 month’s duration, was conducted on admitted patients after obtaining approval of ethics committee of the hospital. 3150 subjects receiving antimicrobial therapy were included in the study. The overall incidence of ADRs to antimicrobials in our study was 6.12%. ADRs related to gastrointestinal tract 117(60.62%) were most frequent. The lowest were blood dyscrasias 02(01.03). The highest incidence local site ADR’s was seen with piperacillin + tazobactum (1.5%) and (1.2%) respectively. Practically all antimicrobial agents cause local irritation at the site of administration. Highest incidence of GI effects was observed with ceftriaxone (10.9%). Diarrhoea occurred maximum with amoxycillin+clavulanic acid (4.1%). Amongst CNS manifestations the highest incidence of headache was with ciprofloxacin (0.9%). Cephalosporins (5.1%) had the highest incidence of development of dermatomucosal effects. Blood dyscrasias were seen in patients treated with metronidazole and cefoperazone+sulbactum. In the analysis of antimicrobial-related ADRs, it was found that most episodes were type A (87.05%). In this study majority of the ADRs episodes 106(54.9%) were judged as probable, 44(22.8%) as possible, and 43(22.3%) as definite. The implementation of adverse event monitoring and notification programs in hospital settings is an important action for the prevention of these events. These programs promote event surveillance and encourage their documentation and notification.

Rough-set-based ADR signaling from spontaneous reporting data with missing values

Spontaneous reporting systems of adverse drug events have been widely established in many countries to collect as could as possible all adverse drug events to facilitate the detection of suspected ADR signals via some statistical or data mining methods. Unfortunately, due to privacy concern or other reasons, the reporters sometimes may omit consciously some attributes, causing many missing values existing in the reporting database. Most of research work on ADR detection or methods applied in practice simply adopted listwise deletion to eliminate all data with missing values. Very little work has noticed the possibility and examined the effect of including the missing data in the process of ADR detection.This paper represents our endeavor towards the exploration of this question. We aim at inspecting the feasibility of applying rough set theory to the ADR detection problem. Based on the concept of utilizing characteristic set based approximation to measure the strength of ADR signals, we propose twelve different rough set based measuring methods and show only six of them are feasible for the purpose. Experimental results conducted on the FARES database show that our rough-set-based approach exhibits similar capability in timeline warning of suspicious ADR signals as traditional method with missing deletion, and sometimes can yield noteworthy measures earlier than the traditional method.

A meta-analysis of the elderly with colorectal cancer

Objective To systematically assess the efficiency of colonoscopy screening for the asymptomatic elderly. Methods A search was performed to identify studies related to colonoscopy screening for the aged in Pubmed and Embase. The key words used for the search included colorectal neoplasm, adenoma, screening, elderly, and colonoscopy.The detection rate of colorectal adenomas, advanced adenomas, colorectal cancer in the elderly and non-elderly were extracted.The studies were evaluated and analyzed by software RevMan 5.3. Results Twelve studies involving 312 111 cases were included(25 107 elderly and 287 004 non-elderly). The total AADR of the elderly was 9.97%, ADR was 11.33%, while CRC detection rate was 1.79%. The meta-analysis showed that there were significant differences in the AADR(RR=1.57, 95%CI: 1.51-1.64), ADR(RR=1.22, 95%CI: 1.19-1.25) and CRC detection rate(RR=2.6, 95%CI: 2.34-2.90) between the elderly and the younger patients(P<0.000 01). The detection rate of AADR, ADR, CRC in the elderly were significantly higher than the non-elderly. Conclusion The elderly have higher AADR and CRC detection rate than the younger. But further studies are needed because life expectancy and complications are factors that need to be considered for screening. Key words: Colonic neoplasms; Screening; Aged; Colonoscopy

Towards a Computable Data Corpus of Temporal Correlations between Drug Administration and Lab Value Changes.

BackgroundThe analysis of electronic health records for an automated detection of adverse drug reactions is an approach to solve the problems that arise from traditional methods like spontaneous reporting or manual chart review. Algorithms addressing this task should be modeled on the criteria for a standardized case causality assessment defined by the World Health Organization. One of these criteria is the temporal relationship between drug intake and the occurrence of a reaction or a laboratory test abnormality. Appropriate data that would allow for developing or validating related algorithms is not publicly available, though.MethodsIn order to provide such data, retrospective routine data of drug administrations and temporally corresponding laboratory observations from a university clinic were extracted, transformed and evaluated by experts in terms of a reasonable time relationship between drug administration and lab value alteration.ResultThe result is a data corpus of 400 episodes of normalized laboratory parameter values in temporal context with drug administrations. Each episode has been manually classified whether it contains data that might indicate a temporal correlation between the drug administration and the change of the lab value course, whether such a change is not observable or whether a decision between those two options is not possible due to the data. In addition, each episode has been assigned a concordance value which indicates how difficult it is to assess. This is the first open data corpus of a computable ground truth of temporal correlations between drug administration and lab value alterations.DiscussionThe main purpose of this data corpus is the provision of data for further research and the provision of a ground truth which allows for comparing the outcome of other assessments of this data with the outcome of assessments made by human experts. It can serve as a contribution towards systematic, computerized ADR detection in retrospective data. With this lab value curve data as a basis, algorithms for detecting temporal relationships can be developed, and with the classification made by human experts, these algorithms can immediately be validated. Due to the normalization of the lab value data, it allows for a generic approach rather than for specific or solitary drug/lab value combinations.