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Critical Article Analysis Validity Questions

Critical Article Analysis Validity Questions

Article 1

Were the subjects randomly selected? Provide a description of the sampling technique & group assignment procedure.

No. This does not apply to the article as it was a systematic review of studies. The study reviewed articles that discussed factors that are linked to screening tools and opioid addiction for the identification of adult patients at low versus high risk. The risk, in this case, was in reference to developing symptoms of addiction to prescription opioids when the drugs were initiated for pain. The authors selected the articles from Embase and MEDLINE from 1946-2018.

What were the main results of the study? List main results. Explain.

The authors identified 1287 studies, of which 4 and 6 were included in the quantitative synthesis and qualitative synthesis, respectively. The 4 studies were retrospective that included more than 2.8 million patients, with 4470 cases meeting the definitions that the authors had on addiction to opioid prescriptions. The parameters that appeared useful in identifying patients that are at a high risk of addiction to opioids include

  • Likelihood Ratio (LR), 17; 95% CI, 15-18 for concomitant prescription of certain psychiatric medications such as atypical antipsychotics;
  • LR, 27; 95% CI, 18-41 for some specific mental disorders such as personality disorder;
  • LR range, 4.2-17 for substance abuse;
  • and LR range, 17-22 for opioid use disorder history.
  • LR, 0.50; 95% CI, 0.45-0.52 for the absence of mood disorder which was linked to the lower risk of addiction to opioid addiction.

The incidence of Opioid Use Disorder (OUD) symptoms from prescription varied with the diagnosis criteria, care setting, and the population of patients. These symptoms were highest in studies that involved programs on chronic pain management, which involved all patients in a screening process and follow-up, compared to database studies whose administrative data sets depended on diagnostic codes. Additionally, having a mental health diagnosis and a history of substance use disorder was linked to an increased likelihood of developing prescription OUD.

Are the results clinically as well as statistically significant? Explain.

Yes, they are. The review showed that there are a number of factors that are useful in identifying patients who are at a high risk of OUD for prescription drugs. Among these, as the results from the research showed, include a history of certain mental health disorders, higher daily opioid doses, prolonged duration of opioid prescriptions lasting 30 days, concomitant prescription for some specific medications for psychiatric disorders, and history of substance use disorder for opioid and non-opioids.

Was the power (effect size) of the study adequate? Is this provided in the methods or discussion? Explain. If yes, indicate power value.

No. The study did not use the power effect as it was a systematic review.

Article 2

Were the subjects randomly selected? Provide a description of the sampling technique & group assignment procedure.

This does not apply to the study as it was a systematic review. The authors selected subjects from databases for studies evaluating tools for analgesic misuse risk during or before chronic pain analgesic therapy. They used the inclusion and exclusion criteria that were predetermined. Of the 1844 studies, only 30 met the inclusion criteria, and these included 3 and 4 studies that were systematic reviews and bibliography reviews, respectively. The inclusion articles covered topics that dealt with opioid use with analgesics that are non-opioid.

What were the main results of the study? List main results. Explain

  1. For the best performing tool as regards screening patients for current misuse, the current opioid misuse measure (COMM) was most effective.
  2. The OCC was found to be more promising in offering functionality for prediction and screening as it is shorter and validated through studies of good quality.

Are the results clinically as well as statistically significant? Explain.

No. The study reviewed a broad range of databases of clinical utility, but a very small fraction of 30/1844 was found to meet the search inclusion criteria.

Was the power (effect size) of the study adequate? Is this provided in the methods or discussion? Explain. If yes, indicate power value.

No. The study did not use the power effect as it was a systematic review.

Article 3

Were the subjects randomly selected? Provide a description of the sampling technique & group assignment procedure.

This does not apply to the study as it was a systematic review. The study involved a secondary analysis of the data that was collected from more than 1100 patients. The participants consented to take part in the naturalistic and cross-sectional study to create a profile of both phenotypes and genotypes risk factors of patients for OUD development when receiving opioid therapy in the long term. The control patients were those with chronic nonmalignant pain (CNMP) and on long-term therapy, who displayed no evidence of OUD. These were recruited from primary care and ambulatory pain practices. The participants were recruited from cases of CNMP patients who had no previous history of Substance Use Disorders (SUD) and developed OUD following long-term treatment. The latter were recruited from urban and suburban substance abuse treatment facilities in the Midwest, Pacific Northwest, and Northeast.

What were the main results of the study? List main results. Explain.

  1. The results revealed that the original Opioid Risk Tool (ORT) could discriminate between patients who had OUD and those who did not. This observation had a 95% confidence interval [CI] = 1.539−1.715, P < .001 and an odds ratio of 1.624.
  2. A weighted Opioid Risk Tool (ORT) with a gender-specific history as regards preadolescent sexual abuse removed also had the capability of discriminating between patients with or without OUD.
  3. An updated unweighted ORT, which had the preadolescent sexual abuse history section removed, proved superior in the prediction of OUD development in CNMP patients on long-term therapy for opioid use. These showed; 95% CI = 2.725−3.493; P < .001 and an odds ratio of 3.085 and a high specificity of 851; 95% CI = .811−.885; a negative predictive value of .914; 95% CI = .885−.937; a positive predictive value of .757; 95% CI = .709−.799 and a sensitivity of .854; 95% CI = .799−.898.

The results of the study showed that the original ORT validity in predicting the risk of a person developing OUD in CNMP patients was not conclusive. However, a revised 9-item un-weighted version of the tool yielded better results when distinguishing persons with OUD from those without OUDs. The key finding is that the original ORT could discriminate between patients with OUDs and those with no OUDs compared to a general analysis made by a physician.

Are the results clinically as well as statistically significant? Explain.

Yes. Opioid therapy, unlike behaviors related to drug aberrance, can be a reflection of several issues. There is clinical usefulness of the revised ORT as it provides clinicians with a validated and simple method of rapidly screening for OUD risk development in patients or in individuals being considered for opioid therapy.

Was the power (effect size) of the study adequate? Is this provided in the methods or discussion? Explain. If yes, indicate power value.

No. The study did not use the power effect as it was a systematic review.

Article 4

Were the subjects randomly selected? Provide a description of the sampling technique & group assignment procedure.

The subjects were not randomly selected. The Brief Risk Questionnaire (BRQ) was finalized and administered within a psychological assessment packet to 299 patients. These were consecutive patients who had been referred to a psychological practice that worked in collaboration with a practice of medical pain. The practice offers comprehensive treatment for persons with chronic pain, and this includes continuous opioid therapy. The patients were being considered for opioids as part of chronic pain treatment, with an opioid risk assessment required on referral.

What were the main results of the study? List main results. Explain.

Two hundred ninety-nine patients were evaluated using the risk assessment tools. Out of the 299, 157 were not given opioids as a treatment option; if they were, they did not return following the 1st prescription. A total of 142 were prescribed an opioid as their treatment for a minimum of 1 month and had 1 clinic return visit.

  1. The follow-up data on the medication aberrance absence or presence showed that there were a number of behaviors linked to aberrance in 48 patients.
  2. Twenty-two patients showed more than a single aberrance to medication following 6 months of follow-up.
  3. At the end of the treatment, 142 participants made it to 6 months period of follow-up, while 16 percent and 13 percent had been discharged because of Medication Aberrant Behavior (MAB) or dropped from care, respectively.

The BRQ is a sensitive tool that identifies patients who later show MAB. It also identifies patients who are at risk but do not show MAB later. Further, missing data on questionnaires completed by patients had no substantial adverse effects on the predictive characteristics measures completed by patients. This shows that the tool tends to over-predict the risk as well as the chances of MAB relative to other risk assessment tools that patients complete.

Are the results clinically as well as statistically significant? Explain.

Yes. The results showed that the BRQ can be compared to the Pain Medication Questionnaire (PMQ) and ORT in the overall accuracy of prediction. The BRQ also tends to be sensitive and can identify most patients who show MAB later.

Was the power (effect size) of the study adequate? Is this provided in the methods or discussion? Explain. If yes, indicate power value.

No, the study did not use the power effect.

References

Cheatle, M. D., Compton, P. A., Dhingra, L., Wasser, T. E., & O’Brien, C. P. (2019). Development of the revised opioid risk tool to predict opioid use disorder in patients with chronic nonmalignant pain. The Journal of Pain20(7), 842-851.

Jones, T., Lookatch, S., Grant, P., McIntyre, J., & Moore, T. (2014). Further validation of an opioid risk assessment tool: the Brief Risk Interview. J Opioid Manag10(5), 353-364.

Klimas, J., Gorfinkel, L., Fairbairn, N., Amato, L., Ahamad, K., Nolan, S., … & Wood, E. (2019). Strategies to identify patient risks of prescription opioid addiction when initiating opioids for pain: a systematic review. JAMA network open2(5), e193365-e193365.

Lawrence, R., Mogford, D., & Colvin, L. (2017). Systematic review to determine which validated measurement tools can be used to assess risk of problematic analgesic use in patients with chronic pain. BJA: British Journal of Anaesthesia119(6), 1092-1109.

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Critical Article Analysis Validity Questions

Critical Article Analysis Validity Questions

Critical Article Analysis Validity Questions

Critical Article Analysis Validity Questions for 4 articles. I need these questions answered on one page for each article.

  1. Were the subjects randomly selected? Provide a description of the sampling technique & group assignment procedure.
  2. What were the main results of the study? List main results. Explain
  3. Are the results clinically as well as statistically significant? Explain
  4. Was the power (effect size) of the study adequate? Is this provided in the methods or discussion? Explain. If yes, indicate power value.

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