***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Weight gain is a major adverse effect of several second-generation antipsychotic medications . Rimonabant is a cannabinoid-1 receptor antagonist that promotes weight loss in the general population . We conducted a 16-week , double-blind , placebo-controlled study of rimonabant ( 20 mg/d ) in people with schizophrenia or schizoaffective disorder , based on the Diagnostic and Statistical Manual of Mental Disorders , Fourth Edition criteria , who were clinical ly stable on second-generation antipsychotics . Participants had a body mass index of 27 kg/m2 or higher with hyperlipidemia or body mass index of 30 kg/m2 or higher , and no current substance abuse/dependence ( except nicotine ) , more than weekly cannabis use , or recent depressive symptoms/suicidality . An exercise and dietary counseling group was offered weekly . Target enrollment was 60 ; the trial was terminated early because of withdrawal of rimonabant from the European market . Fifteen participants were r and omized ( 7 rimonabant  , 8 placebo ) ; 5 completed in each group . Rimonabant was associated with a greater reduction in Brief Psychiatric Rating Scale total score  versus placebo ( mean ± SE difference , −1.9 ± 0.8 , P = 0.02 ) , driven by differences in the Brief Psychiatric Rating Scale anxiety/depression ( −1.4 ± 0.35 , P = 0.0004 ) and hostility ( −0.7 ± 0.3 , P = 0.02 ) factors . Group differences were not significant for the Calgary Depression Scale total score ( P = 0.24 ) , Scale for the Assessment of Negative Symptoms total score ( P = 0.13 ) , weight , blood pressure , or fasting lipids or glucose . Rimonabant was well tolerated with no significant adverse events . No significant weight loss , metabolic effects , or adverse psychiatric effects were associated with the cannabinoid-1 receptor antagonist rimonabant in this small sample of people with schizophrenia . The endocannabinoid system remains a promising target for pharmacotherapy of schizophrenia and obesity We examined the potential risks and benefits of switching from olanzapine to quetiapine in mentally stable , obese , or overweight patients with schizophrenia or schizoaffective disorder . Patients receiving olanzapine were r and omized to continuing olanzapine treatment ( N = 68 ; 7.5–20 mg/day ) or switching to  quetiapine ( N = 65 ; 300–800 mg/day ) . Time to relapse was the primary study objective ; secondary objectives included changes in weight , metabolic parameters , and psychiatric symptoms , and discontinuation rates . No significant difference in time to relapse was observed ( p = 0.293 ) , but significantly more patients remained on treatment in the olanzapine group compared with the quetiapine group ( 70.6 % vs 43.1 % ; p = 0.002 ) . Olanzapine-treated patients had significantly lower rates of study discontinuation for lack of efficacy and psychiatric adverse events ( AEs ) compared to quetiapine ( 2.94 % vs 15.38 % , p = 0.015 ) . Significantly more patients in the olanzapine group experienced an increase in BMI ≥1 kg/m2 . Olanzapine-treated patients experienced significantly greater increases in weight from Weeks 2 through 13 . Switching patients with stable disease from olanzapine to quetiapine did not significantly shorten time to relapse , but produced more frequent study discontinuations due to lack of efficacy or psychiatric AEs with moderate but variable improvement in weight and no significant between-group differences in mean changes in metabolic laboratory parameters Clozapine is associated with significant weight gain and metabolic disturbances .  This multicentre , r and omized study comprised a double-blind , placebo-controlled treatment phase of 16 wk , and an open-label extension phase of 12 wk . Out patients who met DSM-IV-TR criteria for schizophrenia , who were not optimally controlled while on stable dosage of clozapine for > or =3 months and had experienced weight gain of > or = 2.5 kg while taking clozapine , were r and omized ( n=207 ) to aripiprazole at 5 -  15  mg/d or placebo , in addition to a stable dose of clozapine . The primary endpoint was mean change from baseline in body weight at week 16 ( last observation carried forward ) . Secondary endpoints included clinical efficacy , body mass index ( BMI ) and waist circumference . A statistically significant difference in weight loss was reported for aripiprazole vs. placebo ( -2.53 kg vs. -0.38 kg , respectively , difference=-2.15 kg , p<0.001 ) . Aripiprazole-treated patients also showed BMI ( median reduction 0.8 kg/m(2 ) ) and waist circumference reduction ( median reduction 2.0 cm ) vs. placebo ( no change in either parameter , p<0.001 and p=0.001 , respectively ) . Aripiprazole-treated patients had significantly greater reductions in total and low-density lipoprotein ( LDL ) cholesterol . There were no significant differences in Positive and Negative Syndrome Scale total score changes between groups but Clinical Global Impression Improvement and Investigator 's Assessment Question naire scores favoured aripiprazole over placebo .  Safety and tolerability were generally comparable between groups . Combining aripiprazole and clozapine result ed in significant weight , BMI and fasting cholesterol benefits to patients suboptimally treated with clozapine . Improvements may reduce metabolic risk factors associated with clozapine treatment Objective : Few interventions have been successful to prevent or reverse the medical complications associated with antipsychotic agents in the schizophrenia population . In particular , no single agent can correct multiple metabolic abnormalities such as insulin resistance , hyperlipidemia , inflammation , obesity , and fat distribution . We now report a r and omized placebo-controlled pilot study to examine the effects of ramelteon on obesity and metabolic disturbances among subjects with schizophrenia . Methods : A double-blind , placebo-controlled , 8-week pilot trial was conducted , adding ramelteon 8 mg/d to stable out patients with schizophrenia .  Vital signs and anthropometric measurements , including height , weight , waist circumference , and body fat were assessed , and laboratory assays were tracked to monitor changes in metabolic markers . Results : Twenty-five subjects were r and omly assigned to treatment with study drug or placebo , and 20 subjects were included in the final analysis .  Ramelteon did not improve anthropometric measurements , glucose metabolism , and inflammatory markers . There was , however , a significant decrease in total cholesterol and ratio of cholesterol to high-density lipoprotein in the ramelteon group . Although the st and ard anthropometric measures did not show significant change , the dual-energy x-ray absorptiometry scan showed a trend toward reduction in fat in the abdominal and trunk areas with a moderate effect size . Conclusions : Although ramelteon decreased cholesterol , treatment may have to be longer than 8 weeks and with a higher dose for maximal effect of ramelteon for body fat and lipid changes . Future studies are needed for patients with schizophrenia with a larger sample size to fully underst and ramelteon 's effects on abdominal adiposity and lipids In this issue , we answer three questions with respect to loss to follow-up in a clinical trial : How important is loss to follow-up ? How is loss to follow-up calculated ? How many patients can be lost to follow-up without mistrusting the results ? 1 . How important is loss to follow-up ? The simple answer to this question is “ very important ” because loss to follow-up can severely compromise a study 's validity . Incomplete follow-up biases the results when either : The dropout rates are different between study groups ; or The patients who drop out are different from those who do not drop out . Why do these situations make a difference ? Because in each situation , those lost to follow-up often have a different prognosis than those who complete the study . For example , patients who receive treatment for cervical myelopathy may not return for follow-up because they became asymptomatic and felt no need to return to see the surgeon . Conversely , some patients may not return because they had a particularly bad outcome ( worse pain or function ) or complication , or because they died . In either case , bias can affect the validity of the inferences drawn from the study . 2 . How is loss to follow-up calculated ? There is much confusion about how to determine the proportion of patients lost to follow-up . In order to correctly calculate the follow-up rate , one needs to know the denominator . In a r and omized controlled trial ( RCT ) , the denominator for each group is the number of patients who were r and omized , not the number who received the treatment . For example , suppose we have an RCT comparing two treatment groups , Group A and Group B. The investigators evaluate 178 patients and r and omize 120 ; 61 to Group A and 59 to Group B ( Fig 1 ) . Following the figure , we note that 49 patients received treatment A and 52 received treatment B. At the final follow-up 40 were analyzed in Group A and 41 in Group B. How many were considered lost to follow-up ? Many would consider the loss to follow-up rate to be 9 ( 18 % ) of 49 in treatment A and 11 ( 21 % ) of 52 in treatment B using as the denominator only those that were treated . However , the real proportion lost to follow-up must consider those who were r and omly assigned , even if they did not receive treatment . In the present example , this is calculated as 21 ( 34 % ) of 61 for treatment A and 18 ( 31 % ) of 59 for treatment B. Fig 1 Hypothetical example of patients lost to follow-up in a r and omized controlled trial . When calculating loss to follow-up in a retrospective cohort study , all individuals receiving treatment during the study period should be used as the denominator , not just those with complete data . For example , let 's say you want to compare decompression plus lumbar fusion with decompression alone in disc herniation and the data available are all patients receiving either treatment in the last 5 years ( N = 275 ) . However , the data base from which the data are obtained is incomplete and only 190 have the necessary data available . Since the investigators stated as part of the inclusion criteria that only those patients with complete data are included , they consider the follow-up to be 100 % ( 190/190 ) . This conclusion is wrong . The denominator should include all patients who underwent the surgery irrespective of completeness of data . The follow-up rate for this example is 69 % ( 190/275 ) . 3 . How many patients can be lost to follow-up without mistrusting the results ? Some have suggested that 20 % poses serious threats to validity 1 . This may be a good rule of thumb , but keep in mind that even small proportions of patients lost to follow-up can cause significant bias 2 . One way to determine if loss to follow-up can seriously affect results is to assume a worst-case scenario with the missing data and look to see if the results would change . Here is an example : Let 's assume a multicenter study enrolled 500 patients into each arm of a study comparing artificial disc replacement ( ADR ) with fusion , and the end point is adjacent segment disease ( ASD ) . The trial numbers are found in Fig 2 . Fig 2 Hypothetical example of the effect of loss to follow-up considering a worst-case scenario . ADR indicates artificial disc replacement ; ASD , adjacent segment disease . The proportion of patients with ASD in the ADR group is half as much versus the fusion group , 25 % ( 100/400 ) compared with 50 % ( 200/400 ) . If we assume that the 100 lost to follow-up in the ADR group had ASD and the 100 lost to follow-up in the fusion group did not , then the rate of ASD in each group would be 40 % ( 200/500 ) . In this case , adopting the worst-case scenario for the intervention group with respect to those lost to follow-up causes the results to change significantly from half the rate of ASD with ADR to the same rate . When this happens , loss to follow-up can threaten the internal validity of the trial . Only when the worst case does not change the inferences derived from the results is lost to follow-up not a problem While weight-management interventions are effective in attenuating antipsychotic-induced weight , there is no available evidence on their long-term effectiveness . This study sought to investigate the 2-year effects of an early behavioural intervention ( EBI ) design ed to prevent antipsychotic-induced weight gain in first-episode psychosis ( FEP ) patients . Sixty-one FEP patients were r and omized to receive either EBI or treatment-as-usual .  Intention-to-treat and observed-cases analysis showed that patients in the EBI group gained significantly less weight than those allocated to routine care at intervention completion ( 3-month follow-up ) with treatment effects maintained over 3months . Differences between groups were no longer significant by 12months . Weight-management interventions may need to be offered for longer periods to maintain preventative effects . Alternatively , booster sessions may need to be regularly delivered after intervention completion BACKGROUND Patients with schizophrenia and bipolar disorder have frequently reported weight gain during olanzapine treatment . Previous studies have observed a decrease in weight gain , or weight loss , in patients switching from st and ard olanzapine tablets ( SOT )  to orally disintegrating olanzapine ( ODO ) tablets . The primary objective of this study was to investigate the change in body mass index ( BMI ) in patients who had previously gained weight with SOT and continued with this therapy during the study period 
    Output:
    
People are less likely to leave the study early if they remain on olanzapine compared to switching to quetiapine or aripiprazole .
There was no significant difference in outcomes of mental state , global state , and adverse events between groups which switched medications and those that remained on previous medication .
Three different switching strategies were compared and no strategy was found to be superior to the others for outcomes of weight gain , mental state and global state .
There was no difference in mental state , global state and other treatment related adverse events between switching to another medication and continuing on the previous one .
When the three switching strategies were compared none of them had an advantage over the others in their effects on the primary outcomes considered in this review .