Can hemifacial spasm lead to glaucomatous changes?

PURPOSE: To evaluate the association between hemifacial spasm (HFS) patients and glaucoma as a function of the Botox dosage required. METHODS: A retrospective review of clinical documents and procedure records. RESULTS: Information of 76 consecutive patients (58 females) with HFS who received Botox treatment were reviewed. The age at onset of HFS was 66±11 (32-85) years, and all manifested unilaterally. Ten (13%, 95% confidence interval: 6.5-22.9%) patients were diagnosed with glaucoma, including 8 primary open-angle glaucoma (POAG) (4 unilateral and ipsilateral to the HFS), and 2 bilateral chronic angle-closure glaucoma (CACG). Nine of the 10 patients developed glaucoma after the onset of the HFS. The Botox dosage was significantly higher among those diagnosed with glaucoma (31+/8 vs. 26+/7units, P<0.05). There was a positive relationship between the presenting intraocular pressure (IOP) and the Botox dosage required (R=0.31, P=0.0116). However, there was a weak relationship between the Botox dosage required and the vertical cup to disc ratio (R=0.076, P=0.525). The presenting IOP of the HFS-affected eyes in those diagnosed with glaucoma was higher than those without glaucoma (19±3.5 vs. 13±3.2mmHg, P=<0.05). The presenting IOP between the HFS-affected and unaffected eyes was similar (16±4.8 vs. 15+/4.6mmHg, P=0.430). Smoking status, history of diabetes mellitus, hypertension, hyperlipidemia and obstructive sleep apnea were not different between HFS patients with or without glaucoma. CONCLUSIONS: Hemifacial spasm patients with glaucoma were associated with a higher Botox dosage. We found a positive relationship between the Botox dosage required and the presenting IOP. Whether hemifacial spasm can result in fluctuation of IOP, eventually causing glaucomatous damage, remains to be studied further.

A practical approach to the early identification of antidepressant medication non-responders.

BACKGROUND: The aim of the present study was to determine whether a combination of baseline features and early post-baseline depressive symptom changes have clinical value in predicting out-patient non-response in depressed out-patients after 8 weeks of medication treatment. METHOD: We analysed data from the Combining Medications to Enhance Depression Outcomes study for 447 participants with complete 16-item Quick Inventory of Depressive Symptomatology - Self-Report (QIDS-SR16) ratings at baseline and at treatment weeks 2, 4 and 8. We used a multi-time point, recursive subsetting approach that included baseline features and changes in QIDS-SR16 scores from baseline to weeks 2 and 4, to identify non-responders (<50% reduction in QIDS-SR16) at week 8 with a pre-specified accuracy level. RESULTS: Pretreatment clinical features alone were not clinically useful predictors of non-response after 8 weeks of treatment. Baseline to week 2 symptom change identified 48 non-responders (of which 36 were true non-responders). This approach gave a clinically meaningful negative predictive value of 0.75. Symptom change from baseline to week 4 identified 79 non-responders (of which 60 were true non-responders), achieving the same accuracy. Symptom change at both weeks 2 and 4 identified 87 participants (almost 20% of the sample) as non-responders with the same accuracy. More participants with chronic than non-chronic index episodes could be accurately identified by week 4. CONCLUSIONS: Specific baseline clinical features combined with symptom changes by weeks 2-4 can provide clinically actionable results, enhancing the efficiency of care by personalizing the treatment of depression.

Investigating the influence of treatment philosophy on outcome of methadone maintenance.

This study is based on a 'natural experiment' in which a cohort of heroin users was assessed at one unit, then referred on geographic grounds for treatment to one of two clinics--one orientated to long-term maintenance (Clinic 2, with 61 subjects), the other to time-limited treatment aimed at achieving abstinence from all drugs including methadone (Clinic 1, 141 subjects). The outcome measure was heroin use as measured by urine testing performed regularly at both clinics. Overall, 25% of urine tests from Clinic 1 were positive for heroin compared to 18% in Clinic 2. This difference reflected in part a high rate of heroin use during the period of mandatory withdrawal from treatment in clinic 1. Statistical models were developed to identify factors associated with heroin use. There was a strong association between methadone dose and heroin use; relative to a daily dose of 40 mg, a dose of 80 mg/day of methadone was less likely to be associated with a heroin-positive urine (OR 0.55, 95% CI [0.45, 0.68]). Average doses prescribed in Clinic 1 were lower, reflecting the clinic's orientation to abstinence. Adjusting for dose, and for the fact that certain individuals tend to use heroin heavily while others do not, there was no difference between the clinics in risk of heroin use during maintenance treatment. The higher rates of heroin use in the abstinence-orientated clinic were attributable to time-limited treatment and the use of lower doses of methadone. This finding confirms that in investigating the effects of treatment factors, the powerful influence of methadone dose needs to be taken into account.