Bleeding in patients on concurrent treatment with a selective serotonin reuptake inhibitor (SSRI) and low-dose acetylsalicylic acid (ASA) compared with SSRI or low-dose ASA alone-A systematic review and meta-analysis.

AIMS: The aim of this study was to systematically review whether concurrent treatment with an SSRI and low-dose ASA increases the risk of bleeding compared with treatment with an SSRI alone or ASA alone. METHODS: Medline, Embase, the Cochrane Library, PsycINFO and Web of Science (from database inception to January 2023) were searched according to PICO: P = patients on treatment with an SSRI and/or low-dose ASA; I = intervention: SSRI + ASA; C = comparison: ASA or SSRI alone; O = outcomes: bleeding/major bleeding. The included articles were assessed using checklists. Studies without major risk of bias formed the basis for the conclusions. Extracted data were pooled using random-effects meta-analyses. Certainty of evidence was assessed according to GRADE. RESULTS: Twenty-four studies met the PICO and were included. One randomized and six nonrandomized studies were assessed not to have major risk of bias. Regarding SSRI + ASA vs. ASA only, the pooled hazard ratio of three nonrandomized studies (n = 38 467) was 1.37 (95% confidence interval: 1.10; 1.70; I2 = 0%), and the pooled odds ratio of two nonrandomized studies (n = 28 296) was 0.95 (0.77; 1.19; I2 = 0%). Regarding SSRI + ASA vs. SSRI only, the randomized controlled trial (n = 1048) reported a hazard ratio of 1.82 (0.66; 5.02), the hazard ratio being 1.60 (1.24; 2.06) for ASA vs. placebo in patients without SSRI treatment; and one nonrandomized controlled study (n = 18 920) reported an incidence rate ratio of 1.03 (0.96; 1.12). CONCLUSIONS: The compiled evidence was too uncertain to support an interaction when an SSRI is added to low-dose ASA. Low-dose ASA added to an SSRI may imply an increased risk of bleeding primarily attributable to the initiation of ASA.

Interaction alerts: A comparison of classifications and recommendations for clinical management between Janusmed and three other knowledge resources.

Classifications of drug interaction alerts differ between knowledge resources, but agreement regarding recommendations for clinical management is less explored. Starting from the medication lists of 274 older patients with ≥2 drugs, all unique drug pairs that triggered a clinically significant interaction alert in Janusmed were included: 100 Category C (manageable by, e.g. dose adjustment) and nine Category D interactions (should be avoided). Out of 109 C/D alerts in Janusmed, 89 (82%), 75 (69%) and 45 (41%) drug pairs triggered an alert of similar clinical significance in Lexicomp, Micromedex® and Stockley's Drug Interactions/Checker (Stockley), respectively. Eight (7%), 20 (18%) and 10 (9%) drug pairs did not trigger any alert in these resources. For 81 (74%), 81 (74%) and 94 (86%) drug pairs, Lexicomp, Micromedex and Stockley provided at least one recommendation for clinical management similar to those provided by Janusmed. For 16 (15%), 9 (8%) and 21 (19%) drug pairs, these resources provided recommendation(s) entirely in agreement with Janusmed. Although many drug pairs elicit alerts of similar significance, and partly concordant recommendations, a non-negligible proportion do not. The findings encourage medical/pharmaceutical reflection by prescribing clinicians and dispensing pharmacists; recommendations provided by knowledge resources vary considerably and cannot be considered definite.

Drug interaction alerts in older primary care patients, and related medically justified actions.

PURPOSE: To describe presented interaction alerts in older patients, and the extent to which these require further medical action for the specific patient or are already being addressed. METHODS: Interaction alerts presented at a physician consultation, for 274 consecutive primary care patients treated with two or more drugs (median age: 75 years; 59% female), were extracted. These alerts are based on Janusmed, a decision support integrated in the medical records that provides recommendations for managing the interactions. One general practitioner (GP) and one GP/clinical pharmacologist determined in retrospect, first independently and then in consensus, whether the alerts justified further medical action, considering each patient's health condition. RESULTS: In all, 405 drug interaction alerts in 151 (55%) patients were triggered. Medical action in response was deemed medically justified for 35 (9%) alerts in 26 (17%) patients. These actions most often involved a switch to a less interacting drug from the same drug class (n = 10), a separate intake (n = 9), or the ordering of a laboratory test (n = 8). Out of 531 actions suggested by the alert system, only 38 (7%) were applicable to the specific patient, as, for instance, laboratory parameters were already being satisfactorily monitored or a separate intake implemented. CONCLUSIONS: More than every other older patient receives drug treatment that triggers drug interaction alerts. Nine in ten alerts were already being addressed or were not relevant in the clinical setting, whereas, for the remaining tenth, some medical action, that for unknown reasons had not been taken, was reasonable. These findings show that interaction alerts are questionable as indicators of problematic prescribing.

Drug information centre queries and responses about drug interactions over 10 years-A descriptive analysis.

Many people are treated with ≥1 drug, implying that risks of drug interactions need to be considered. The aim of this study was to describe drug interaction queries from healthcare professionals to a drug information centre in Sweden over 10 years focusing on drugs frequently asked about and the advice provided. Advice was recorded in mutually exclusive groups: Avoid, Adjust dose, Separate intake, Vigilance or No problem. For queries with Avoid, Adjust dose or Separate intake advice, alerts were extracted from an interaction database (Janusmed). Of 4335 queries to the centre in 2008-2017, 589 (14%) concerned interactions. Most were posed by physicians (91%) and concerned a specific patient (83%) before treatment initiation (76%). Sertraline, warfarin and methotrexate were the most frequently asked about, whereas queries about cyclophosphamide and rifampicine occurred most often in relation to the number of exposed patients. Advice provided in 557 (95%) replies comprised Avoid: n = 85 (15%), Adjust dose: n = 57 (10%), Separate intake: n = 17 (3%), Vigilance: n = 235 (42%) or No problem: n = 163 (29%). In all, 113 (71%) of 159 queries with Avoid/Adjust dose/Separate intake advice elicited an action alert on Janusmed, whereas 31 (20%) did not result in any alert at all. Summarized, seven in ten replies from the drug information centre recommended an explicit drug treatment action, regarding either specific prescribing aspects, for instance dose adjustments, or active follow-up including monitoring potential adverse reactions and/or laboratory results. Readily accessible decision support regarding drug interactions often provides relevant action alerts, but cannot be solely relied on.

Individual case safety reports in children in commonly used drug groups - signal detection.

BACKGROUND: Due to few paediatric drug safety studies, knowledge on risks of drug treatment in children is limited. The knowledge needs to be increased to make proper risk-benefit analyses possible when treating paediatric patients with drugs. The aim of the present study was to investigate drug groups commonly used in children concerning type and frequency of individual case safety reports in children. METHODS: Number and type of individual case safety reports in the 30 groups of drugs (5th level ATC-code) most sold (number of defined daily doses) in outpatient treatment to children (<15 years old) during 2005 were obtained. Descriptive analyses of the adverse drug reactions reported in children were performed. RESULTS: The number of individual case safety reports per million defined daily doses in children varied in the groups of drug between 0 and 24. The largest number was found in the drug group R03DC, the leukotriene receptor antagonist montelukast; the majority of the children being <5 years old and experiencing psychiatric adverse drug reactions. CONCLUSION: The number of individual case safety reports per million defined daily doses varies in different groups of drugs. A possible signal for montelukast and psychiatric adverse drug reactions was found, which should be further explored.

Reporting of adverse drug reactions may be influenced by feedback to the reporting doctor.

OBJECTIVE: The purpose of this study was to investigate two different feedback alternatives to doctors reporting adverse drug reactions (ADRs) concerning (1) effects on reporting rates and (2) doctors' opinions. METHODS: When reporting an ADR during January through March 2006, doctors in the western part of Sweden were randomised according to working address to receive feedback I or feedback II. Feedback I consisted of the conventional mode of feedback. Feedback II consisted of the contents of feedback I supplemented with information on the reported drug from the regional drug information centre. A questionnaire was administered 2 weeks after the feedback. The doctors were asked to give their opinion on the feedback concerning amount of information, quality and overall impression on a 6-point scale, where 1 corresponded to too little/very bad and 6 to too much/very good. During the inclusion period and the 6-month follow-up period, additional ADR reports originating from receivers of either feedback I or II were identified and compared. RESULTS: Sixty-six doctors received feedback I, and 49 received feedback II. The number of doctors reporting more than once was greater in the group receiving feedback II (39% vs. 22%; P = 0.039). Feedback II was judged to contain more information than feedback I (4.1 +/- 0.8 vs. 3.6 +/- 0.9; P = 0.014). No difference between the feedback alternatives concerning doctors' opinions on quality and overall impression could be detected. Sixty-five doctors (70%) stated that the content of the feedback letter could affect their willingness to report ADRs. CONCLUSION: The content of the feedback to doctors reporting ADRs may influence reporting rates.