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      Use of antipsychotic drugs and cholinesterase inhibitors and risk of falls and fractures: self-controlled case series

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          Abstract

          Objective

          To evaluate the association between the use of antipsychotic drugs and cholinesterase inhibitors and the risk of falls and fractures in elderly patients with major neurocognitive disorders.

          Design

          Self-controlled case series.

          Setting

          Taiwan’s National Health Insurance Database.

          Participants

          15 278 adults, aged ≥65, with newly prescribed antipsychotic drugs and cholinesterase inhibitors, who had an incident fall or fracture between 2006 and 2017. Prescription records of cholinesterase inhibitors confirmed the diagnosis of major neurocognitive disorders; all use of cholinesterase inhibitors was reviewed by experts.

          Main outcome measures

          Conditional Poisson regression was used to derive incidence rate ratios and 95% confidence intervals for evaluating the risk of falls and fractures for different treatment periods: use of cholinesterase inhibitors alone, antipsychotic drugs alone, and a combination of cholinesterase inhibitors and antipsychotic drugs, compared with the non-treatment period in the same individual. A 14 day pretreatment period was defined before starting the study drugs because of concerns about confounding by indication.

          Results

          The incidence of falls and fractures per 100 person years was 8.30 (95% confidence interval 8.14 to 8.46) for the non-treatment period, 52.35 (48.46 to 56.47) for the pretreatment period, and 10.55 (9.98 to 11.14), 10.34 (9.80 to 10.89), and 9.41 (8.98 to 9.86) for use of a combination of cholinesterase inhibitors and antipsychotic drugs, antipsychotic drugs alone, and cholinesterase inhibitors alone, respectively. Compared with the non-treatment period, the highest risk of falls and fractures was during the pretreatment period (adjusted incidence rate ratio 6.17, 95% confidence interval 5.69 to 6.69), followed by treatment with the combination of cholinesterase inhibitors and antipsychotic drugs (1.35, 1.26 to 1.45), antipsychotic drugs alone (1.33, 1.24 to 1.43), and cholinesterase inhibitors alone (1.17, 1.10 to 1.24).

          Conclusions

          The incidence of falls and fractures was high in the pretreatment period, suggesting that factors other than the study drugs, such as underlying diseases, should be taken into consideration when evaluating the association between the risk of falls and fractures and use of cholinesterase inhibitors and antipsychotic drugs. The treatment periods were also associated with a higher risk of falls and fractures compared with the non-treatment period, although the magnitude was much lower than during the pretreatment period. Strategies for prevention and close monitoring of the risk of falls are still necessary until patients regain a more stable physical and mental state.

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          Most cited references55

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          Sensitivity Analysis in Observational Research: Introducing the E-Value.

          Sensitivity analysis is useful in assessing how robust an association is to potential unmeasured or uncontrolled confounding. This article introduces a new measure called the "E-value," which is related to the evidence for causality in observational studies that are potentially subject to confounding. The E-value is defined as the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. A large E-value implies that considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. The authors propose that in all observational studies intended to produce evidence for causality, the E-value be reported or some other sensitivity analysis be used. They suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would improve considerably, and ultimately, science would be strengthened.
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            American Geriatrics Society 2019 Updated AGS Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults

            (2019)
            The American Geriatrics Society (AGS) Beers Criteria® (AGS Beers Criteria®) for Potentially Inappropriate Medication (PIM) Use in Older Adults are widely used by clinicians, educators, researchers, healthcare administrators, and regulators. Since 2011, the AGS has been the steward of the criteria and has produced updates on a 3-year cycle. The AGS Beers Criteria® is an explicit list of PIMs that are typically best avoided by older adults in most circumstances or under specific situations, such as in certain diseases or conditions. For the 2019 update, an interdisciplinary expert panel reviewed the evidence published since the last update (2015) to determine if new criteria should be added or if existing criteria should be removed or undergo changes to their recommendation, rationale, level of evidence, or strength of recommendation. J Am Geriatr Soc 67:674-694, 2019.
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              Taiwan’s National Health Insurance Research Database: past and future

              Abstract Taiwan’s National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have largely increased the reliability of NHIRD studies. Recently, Taiwan’s Ministry of Health and Welfare (MOHW) established a Health and Welfare Data Center (HWDC), a data repository site that centralizes the NHIRD and about 70 other health-related databases for data management and analyses. To strengthen the protection of data privacy, investigators are required to conduct on-site analysis at an HWDC through remote connection to MOHW servers. Although the tight regulation of this on-site analysis has led to inconvenience for analysts and has increased time and costs required for research, the HWDC has created opportunities for enriched dimensions of study by linking across the NHIRD and other databases. In the near future, researchers will have greater opportunity to distill knowledge from the NHIRD linked to hospital-based electronic medical records databases containing unstructured patient-level information by using artificial intelligence techniques, including machine learning and natural language processes. We believe that NHIRD with multiple data sources could represent a powerful research engine with enriched dimensions and could serve as a guiding light for real-world evidence-based medicine in Taiwan.
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                Author and article information

                Contributors
                Role: doctoral student
                Role: CW Maplethorpe fellow
                Role: psychiatrist
                Role: research analyst
                Role: associate professor
                Journal
                BMJ
                BMJ
                BMJ-UK
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2021
                09 September 2021
                : 374
                : n1925
                Affiliations
                [1 ]School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                [2 ]Research Department of Practice and Policy, UCL School of Pharmacy, London, UK
                [3 ]Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
                [4 ]Department of Psychiatry, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
                Author notes
                Correspondence to: E C-C Lai edward_lai@ 123456mail.ncku.edu.tw
                Author information
                https://orcid.org/0000-0001-7855-9590
                https://orcid.org/0000-0001-8645-1942
                https://orcid.org/0000-0002-5964-106X
                https://orcid.org/0000-0003-3933-8730
                https://orcid.org/0000-0002-5852-7652
                Article
                wang064733
                10.1136/bmj.n1925
                8427404
                34503972
                f359a8f6-b1a4-4915-9235-b075bde0e0cb
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 27 July 2021
                Categories
                Research

                Medicine
                Medicine

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