A Non-Interventional Naturalistic Study of the Prescription Patterns of Antipsychotics in Patients with Schizophrenia from the Spanish Province of Tarragona

<div><p>Background</p><p>The analysis of prescribing patterns in entire catchment areas contributes to global mapping of the use of antipsychotics and may improve treatment outcomes.</p><p>Objective</p><p>To determine the pattern of long-term antipsychotic prescription in outpatients with schizophrenia in the province of Tarragona (Catalonia-Spain).</p><p>Methods</p><p>A naturalistic, observational, retrospective, non-interventional study based on the analysis of registries of computerized medical records from an anonymized database of 1,765 patients with schizophrenia treated between 2011 and 2013.</p><p>Results</p><p>The most used antipsychotic was risperidone, identified in 463 (26.3%) patients, followed by olanzapine in 249 (14.1%), paliperidone in 225 (12.7%), zuclopenthixol in 201 (11.4%), quetiapine in 141 (8%), aripiprazole in 100 (5.7%), and clozapine in 100 (5.7%). Almost 8 out of 10 patients (79.3%) were treated with atypical or second-generation antipsychotics. Long-acting injectable (LAI) formulations were used in 44.8% of patients. Antipsychotics were generally prescribed in their recommended doses, with clozapine, ziprasidone, LAI paliperidone, and LAI risperidone being prescribed at the higher end of their therapeutic ranges. Almost 7 out of 10 patients (69.6%) were on antipsychotic polypharmacy, and 81.4% were on psychiatric medications aside from antipsychotics. Being prescribed quetiapine (OR 14.24, 95% CI 4.94–40.97), LAI (OR 9.99, 95% CI 6.45–15.45), psychiatric co-medications (OR 4.25, 95% CI 2.72–6.64), and paliperidone (OR 3.13, 95% CI 1.23–7.92) were all associated with an increased likelihood of polypharmacy. Being prescribed risperidone (OR 0.54, 95% CI 0.35–0.83) and older age (OR 0.98, 95% CI 0.97–0.99) were related to a low polypharmacy probability.</p><p>Conclusions</p><p>Polypharmacy is the most common pattern of antipsychotic use in this region of Spain. Use of atypical antipsychotics is extensive. Most patients receive psychiatric co-medications such as anxiolytics or antidepressants. Polypharmacy is associated with the use of quetiapine or paliperidone, use of a LAI, younger age, and psychiatric co-medication.</p></div

Polypharmacy for the five most common principal antipsychotic treatments.

<p>Polypharmacy for the five most common principal antipsychotic treatments.</p

Demographic and clinical characteristics and patterns of antipsychotic use in 1,765 outpatients with schizophrenia.

<p><b>Note</b>. SMD = Severe Mental Disorder. Values significantly different (according to Pearson’s Chi square or the Kruskal Wallis test) are in bold (p<0.01).</p><p>Values are frequencies (%) or means ± standard deviations.</p

Comparison of the frequencies of psychiatric co-medications (other than antipsychotics) between the principal antipsychotic prescription patterns.

<p>An asterisk (*) indicates an observed frequency higher than expected in all χ² comparisons, p<0.01.</p

Antipsychotic prescription patterns for 1,734 of 1,765 outpatients with schizophrenia.

<p><b><i>Note</i></b>. SD = Standard deviation; LAI = Long-acting injectable.</p><p>^a Doses are mg/day for oral antipsychotics and mg/injection for LAI.</p><p>Recommended maintenance doses and corresponding ranges according to the Spanish Medicines Agency are shown if available. Data are for principal antipsychotic treatments. Oral antipsychotics are in italic (n = 944) and LAI are in bold (n = 790).</p

Delirium diagnosis defined by cluster analysis of symptoms versus diagnosis by DSM and ICD criteria: diagnostic accuracy study

Background: Information on validity and reliability of delirium criteria is necessary for clinicians, researchers, and further developments of DSM or ICD. We compare four DSM and ICD delirium diagnostic criteria versions, which were developed by consensus of experts, with a phenomenology-based natural diagnosis delineated using cluster analysis of delirium features in a sample with a high prevalence of dementia. We also measured inter-rater reliability of each system when applied by two evaluators from distinct disciplines. Methods: Cross-sectional analysis of 200 consecutive patients admitted to a skilled nursing facility, independently assessed within 24–48 h after admission with the Delirium Rating Scale-Revised-98 (DRS-R98) and for DSM-III-R, DSM-IV, DSM-5, and ICD-10 criteria for delirium. Cluster analysis (CA) delineated natural delirium and nondelirium reference groups using DRS-R98 items and then diagnostic systems’ performance were evaluated against the CA-defined groups using logistic regression and crosstabs for discriminant analysis (sensitivity, specificity, percentage of subjects correctly classified by each diagnostic system and their individual criteria, and performance for each system when excluding each individual criterion are reported). Kappa Index (K) was used to report inter-rater reliability for delirium diagnostic systems and their individual criteria. Results: 117 (58.5 %) patients had preexisting dementia according to the Informant Questionnaire on Cognitive Decline in the Elderly. CA delineated 49 delirium subjects and 151 nondelirium. Against these CA groups, delirium diagnosis accuracy was highest using DSM-III-R (87.5 %) followed closely by DSM-IV (86.0 %), ICD-10 (85.5 %) and DSM-5 (84.5 %). ICD-10 had the highest specificity (96.0 %) but lowest sensitivity (53.1 %). DSM-III-R had the best sensitivity (81.6 %) and the best sensitivity-specificity balance. DSM-5 had the highest inter-rater reliability (K =0.73) while DSM-III-R criteria were the least reliable. Conclusions: Using our CA-defined, phenomenologically-based delirium designations as the reference standard, we found performance discordance among four diagnostic systems when tested in subjects where comorbid dementia was prevalent. The most complex diagnostic systems have higher accuracy and the newer DSM-5 have higher reliability. Our novel phenomenological approach to designing a delirium reference standard may be preferred to guide revisions of diagnostic systems in the future

Correlation between prolactin levels and MCCB cognitive domains (T-scores) and psychopharmacological treatments.

<p>Stratified analysis by diagnostic group.</p><p>^* Log transformed (ln) values of prolactin.</p>†<p>In equivalents of chlorpromazine (mg/day).</p>‡<p>In equivalents of diazepam (mg/day).</p>§<p>In equivalents of fluoxetine (mg/day).</p

Results of the multiple linear regression analysis exploring the relationship between prolactin levels and speed of processing in subjects with early psychoses.

<p>T-score (adjusted for age, gender and education level) in the speed of processing MCCB domain was considered the dependent variable.</p><p>Abbreviations: PANSS = Positive and Negative Syndrome Scale; <i>β = </i>Standardized beta coefficient; MCCB = MATRICS Consensus Cognitive Battery.</p><p>* In chlorpromazine equivalents, mg/day.</p>‡<p>In diazepam equivalents, mg/day.</p>†<p>In fluoxetine equivalents, mg/day.</p

Clinical and cognitive variables by diagnostic groups.

<p>Data are mean (SD) or N (%). Four participants (3 PD, 1 HR) had missing data for prolactin analyses.</p><p>Abbreviation: PANSS = Positive and Negative Syndrome Scale; MCCB = MATRICS Consensus Cognitive Battery.</p>†<p>One-way ANOVA was used to compare continuous data among groups. Chi-square test was used to compare categorical data among groups.</p>‡<p>Psychopharmacologic treatment was compared between PD and HR groups (HS were excluded in the comparison).</p><p>Significant ANOVA post-hoc analyses (with Bonferroni adjustment) are highlighted: ^a HS vs PD, ^bHS vs HR, ^cPD vs HR.</p

Results of the mediation analysis exploring the relationship between risperidone/paliperidone dose and processing speed in subjects with early psychoses.

<p>Log transformed (ln) levels of prolactin were used in the mediation analysis. The mediated effect (b) was adjusted for the following covariates: olanzapine/clozapine/quetiapine dose (β = 0.002, SE = 0.008, P = 0.848), aripiprazole dose (β = −0.016, SE = 0.011, P = 0.151), biperiden dose (β = −0.567, SE = 1.486, P = 0.704) and antidepressant dose (β = 0.048, SE = 0.101, P = 0.638). Abbreviations: β = unstandardized regression coefficient; SE = standard error.</p