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Introduction: Despite reports suggesting an association between COVID-19 mRNA vaccination and pericarditis and myocarditis, detailed nationwide population-based data are sparsely available. We describe the incidence of pericarditis and myocarditis by age categories and sex after COVID-19 mRNA vaccination from a nationwide mass vaccination programme in Singapore. Methods: The incidence of adjudicated cases of pericarditis and myocarditis following COVID-19 mRNA vaccination that were reported to the vaccine safety committee between January to July 2021 was compared with the background incidence of myocarditis in Singapore. All treatment was discontinued after 2 months. Average NAPSI score on each hand was analysed. Results: As of end July 2021, a total of 34 cases were reported (9 pericarditis only, 14 myocarditis only, and 11 concomitant pericarditis and myocarditis) with 7,183,889 doses of COVID-19 mRNA vaccine administered. Of the 9 cases of pericarditis only, all were male except one. The highest incidence of pericarditis was in males aged 12–19 years with an incidence of 1.11 cases per 100,000 doses. Of the 25 cases of myocarditis, 80% (20 cases) were male and the median age was 23 years (range 12–55 years) with 16 cases after the second dose. A higher-than-expected number of cases were seen in males aged 12–19 and 20–29 years, with incidence rates of 3.72 and 0.98 case per 100,000 doses, respectively. Conclusion: Data from the national registry in Singapore indicate an increased incidence of pericarditis and myocarditis in younger men after COVID-19 mRNA vaccination. Keywords: COVID-19 vaccine, myocarditis, pericarditis

We analyzed the spontaneous adverse event database in Singapore to determine the types of cutaneous adverse drug reactions ( CADR s) and causative drugs reported. We selected 10 CADR s‐of‐interest, and identified the suspected drugs and the characteristics of the at‐risk population. ADR reports received from 2006 to 2015 of the system organ class “Skin and Appendages Disorders” were analyzed based on patient demographics, the types of CADR s, suspected drugs, outcome, and latency period. Of the 104 372 reports analyzed, 56.2% involved females and 72.5% involved Chinese patients. The mean age was 41.1 years old. The top CADR s reported were rash (including nonspecified rash, follicular rash, maculopapular rash, and vesicular rash) (67.2%) and angioedema (13.9%). The drugs frequently associated with the CADR s‐of‐interest include nonsteroidal antiinflammatory drugs and antibiotics with angioedema, iohexol with urticaria, and antiepileptics and allopurinol with Stevens‐Johnson syndrome ( SJS )/toxic epidermal necrolysis ( TEN ). A subgroup analysis based on age, sex, and race on the 10 CADR s‐of‐interest showed the following trends in reporting: Alopecia (reported more in females), drug hypersensitivity syndrome (more in males), angioedema (more in younger patients), and photosensitivity (more in older patients). In general, the racial distribution across each CADR ‐of‐interest was consistent with that of Singapore's population, with slight deviations observed for SJS / TEN , photosensitivity and skin discoloration. We analyzed CADR reports from Singapore over 10 years, and identified the types of CADR s reported, and their associated drugs, latency periods and patient characteristics. Such information could add value to healthcare professionals as they assess CADR cases and evaluate suspected drugs.

The purpose of this study was to develop and validate sensitive algorithms to detect hospitalized statin-induced myopathy (SIM) cases from electronic medical records (EMRs). We developed four algorithms on a training set of 31,211 patient records from a large tertiary hospital. We determined the performance of these algorithms against manually curated records. The best algorithm used a combination of elevated creatine kinase (>4× the upper limit of normal (ULN)), discharge summary, diagnosis, and absence of statin in discharge medications. This algorithm achieved a positive predictive value of 52-71% and a sensitivity of 72-78% on two validation sets of >30,000 records each. Using this algorithm, the incidence of SIM was estimated at 0.18%. This algorithm captured three times more rhabdomyolysis cases than spontaneous reports (95% vs. 30% of manually curated gold standard cases). Our results show the potential power of utilizing data and text mining of EMRs to enhance pharmacovigilance activities.

Purpose: The Singapore regulatory agency for health products (Health Sciences Authority), in performing active surveillance of medicines and their potential harms, is open to new methods to achieve this goal. Laboratory tests are a potential source of data for this purpose. We have examined the performance of the Comparison on Extreme Laboratory Tests (CERT) algorithm, developed by Ajou University, Korea, as a potential tool for adverse drug reaction detection based on the electronic medical records of the Singapore health care system. Methods:We implemented the original CERT algorithm, comparing extreme laboratory results pre-and post-drug exposure, and 5 variations thereof using 4.5 years of National University Hospital (NUH) electronic medical record data (31 869 588 laboratory tests, 6 699 591 drug dispensings from 272 328 hospitalizations). We investigated 6 drugs from the original CERT paper and an additional 47 drugs. We benchmarked results against a reference standard that we created from UpToDate 2015.Results: The original CERT algorithm applied to all 53 drugs and 44 laboratory abnormalities yielded a positive predictive value (PPV) and sensitivity of 50.3% and 54.1%, respectively. By raising the minimum number of cases for each drug-laboratory abnormality pair from 2 to 400, the PPV and sensitivity increased to 53.9% and 67.2%, respectively. This post hoc variation, named CERT400, performed particularly well for drug-induced hepatic and renal toxicities. Discussion:We have demonstrated that the CERT algorithm can be applied across national boundaries. One modification (CERT400) was able to identify adverse drug reaction signals from laboratory data with reasonable PPV and sensitivity, which indicates potential utility as a supple- reporting from its contributors, and susceptibility to under-reporting as well as over-reporting (eg, due to media interest), (2) incomplete or missing data, hindering causality assessment, and (3) difficulty in detecting duplicate reports. | Selection of drugs for evaluationAmong the 10 drugs analysed in the original CERT paper, one drug (ketorolac) was not used at NUH, while 3 oncologic drugs (etoposide, fluorouracil, and methotrexate) were incompletely captured because oncologic drugs are mainly ordered and recorded in another database.To have a direct head-to-head comparison of algorithm performance from the EMRs of two different health care institutions, we first analysed only 6 drugs described in the original CERT publication (round 1, Table 1).In round 2, we investigated an additional 47 drugs (Table 2).Factors considered in drug selection were drug usage volume and the likelihood of the drug being started during hospitalisation. Drugs with high usage were prioritised to provide sufficient number of cases for analysis. We also included negative controls (chlorpheniramine, metronidazole, and risedronic acid) with no ADRs detectable by abnormal laboratory test results in the reference standard. KEY POINTS• The Comparison on Extreme Laboratory Tests (CERT) algor...