Patient demographics and medications by ward.

a<p>Totals might exceed 100% because some patients received more than one drug type.</p>b<p>chlorpromazine, flupentixol, fluphenazine, haloperidol, levomepromazine, penfluridol, perhphenazine, zuclopenthixol.</p>c<p>amisulpride, aripriprazole, asenapine, clotiapine, clozapine, olanzapine, paliperidone, palperidone, quetiepine, risperidone, sertindole, ziprasidone.</p>d<p>escitalopram, paroxetine, reboxetine, trazadone.</p>e<p>buspirone, clonazepam, diazepam, lorazepam, oxazepam.</p>f<p>carbamazepine, lamotrigine, lithium.</p>g<p>brotizolam, nitrazepam, zopiclone.</p

Frequency and percentage of sodium valproate use by ward and diagnosis.

a<p>Significant dependency between ward and sodium valproate use: χ² = 4.674, p = 0.031.</p>b<p>Significant dependency between diagnosis and sodium valproate use: χ²_(1df) = 29.0, p<0.001.</p

Frequency and percentage of sodium valproate use by number and type of drugs.

a<p>Other than sodium valproate.</p

Logistic regression predicting the use of sodium valproate by gender, diagnosis, ward and number of antipsychotics.

<p>Logistic regression predicting the use of sodium valproate by gender, diagnosis, ward and number of antipsychotics.</p

Types of antipsychotics by ward.

<p>Types of antipsychotics by ward.</p

Logistic regression predicting the use of sodium valproate by gender, ward, diagnosis and number of drugs.

<p>Logistic regression predicting the use of sodium valproate by gender, ward, diagnosis and number of drugs.</p