Introdução: Os Benzodiazepínicos estão entre as drogas mais prescritas no mundo. Possuem características ansiolíticas, hipnóticas, miorelaxantes e anticonvulsivantes. Estudos prévios evidenciam inadequações nas prescrições de benzodiazepínicos, como uso equivocado para quadros inespecíficos, tratamento prolongado e abuso por idosos. Benzodiazepínicos podem trazer sérios efeitos adversos, sobretudo em idosos, como sonolência diurna, deterioro da memória e funções cognitivas, desequilíbrio e quedas. Objetivos: Analisar a prevalência do uso de benzodiazepínicos nos pacientes do Centro de Atenção Psicossocial (CAPS) de Campo Bom-RS em um período de 24 meses (Junho de 2013 a Maio de 2015), faixa etária, frequência de dispensações, dosagens, CIDs e especialidades dos médicos prescritores; bem como possíveis relações com a função cognitiva, afetiva, e quedas em idosos. Métodos: Estudo transversal, com informações coletadas e tabuladas a partir dos prontuários e prescrições médicas do CAPS Campo Bom, bem como do seu sistema informatizado de gerenciamento (Software Multi 24 Horas). Foram obtidos dados como idade, gênero, identificação dos CIDs; bem como informações sobre prescrições de Benzodiazepínicos, como frequência, quantidade, tipo de medicamento, posologia, profissional prescritor e demais medicamentos utilizados. Critério de inclusão: utilização de qualquer benzodiazepínico disponível na rede SUS: Clonazepam 0,5mg, Clonazepam 2,5 mg/ml, Clonazepam 2mg e Diazepam 5mg. Foram aplicados os testes MEEM e GDS nos pacientes idosos, em entrevistas individuais, nas quais também se avaliou a escolaridade, ocorrência e frequência de quedas, além das comorbidades auto relatadas. Para construção do banco de dados foi utilizado o Software Microsoft® Office Excel® 2007, e para análise estatística o Software PASW V18 (SPSS®). Resultados: O número total de pacientes ativos identificados no CAPS foi de 855 indivíduos, sendo 543 (63,5%) mulheres e 84 idosos (9,8%). A prevalência de utilização de BZD nesta população representou 47,2% (n=404 indivíduos). Foram identificadas 12.680 prescrições médicas dispensadas e, deste total, a prevalência de prescrições de benzodiazepínicos foi de 21,7% (n=2.748). Dentre os pacientes que receberam BZD, 297 (73,5%) eram mulheres e 59 idosos (14,6%), dos quais 56 foram entrevistados. Dentre os idosos entrevistados, 42 (75,0%) possuíram significativa sintomatologia depressiva (GDS≥5) e 32 (57,1%) apresentaram duas ou mais quedas no período de 1 ano. Dezoito pacientes idosos demonstraram fazer uso de dois ou mais BZDs. Houve correlação linear negativa entre os escores do MEEM e do GDS (r = - ,416; p=,002). Houve também uma correlação linear negativa entre o escore do MEEM e número de quedas em idosos (r = -,327 p=,016). Conclusões: Os benzodiazepínicos corresponderam a 21,7 % do total de prescrições do CAPS e do total dos indivíduos 47,2% receberam benzodiazepínicos. Proporcionalmente aos homens, as mulheres tenderam a receber mais prescrições de benzodiazepínicos (p<.001). A prevalência de significativa sintomatologia depressiva nos idosos usuários do CAPS foi alta (75,0%), assim como a incidência de quedas, sendo que mais da metade dos idosos caiu 2 ou mais vezes no período. Identificou-se uma correlação linear negativa entre a função cognitiva como avaliada pelo MEEM e a sintomatologia depressiva avaliada pelo GDS; bem como houve uma correlação linear negativa entre o MEEM e o número de quedas em idosos. / Introduction: Benzodiazepines are among the most prescribed drugs in the world, they have characteristics such as anxiolytic, hypnotic, muscle relaxants and anticonvulsants. Studies have pointed out distortions in benzodiazepines’ prescriptions, such as misuse for unspecific cases, prolonged treatment and use by elderly. Such medications may cause serious damage, particularly in the elderly, and its continued use causes side effects such as daytime somnolence, imbalance, memory and cognitive function loss, increased incidence of falls. Objectives: To assess the prevalence of benzodiazepine use among patients of the Center for Psychosocial Care in Campo Bom-RS within the period of June 2013 to May 2015. The variables analyzed were: age, frequency of dispensations, dosages, ICDs and specialties of prescribing doctors; as well as possible correlations between cognitive function, emotional function and falls in the elderly. Methods: Cross-sectional study, with data collected and tabulated from medical records and prescriptions, as well as from the management system from CAPS (Software Multi 24 hours). Data obtained was age, gender, ICDs identification; as well as frequency of prescriptions, quantity and type of medication, dosage, prescribing professional, others used drugs. Inclusion criteria: Use of any benzodiazepine available in the Health Unic System: Clonazepam 0,5 mg, Clonazepam 2,5 mg/ml, Clonazepam 2 mg and Diazepam 5mg. MMSE and GDS tests have been applied in the elderly, through individual interviews, in which we found about educational level, occurrence and frequency of falls and other self-reported comorbidities. The software Microsoft® Excel® 2007 was used to build database, and for statistical analysis the software PASW V18 (SPSS) was used. Results: The total number of active patients identified at CAPS was 855 individuals, of these 543 were women (63.5%) and 84 elderly (9.8%). The prevalence of benzodiazepines’ use in this population was 47.2 % (n = 404). We have found 12.680 prescriptions dispensed and the prevalence of benzodiazepines’ prescriptions was 21.7 % (n = 2.748). Among patients who received benzodiazepines, 297 (73.5%) were women and 59 elderly (14.6%), of these 56 were interviewed. From the interviewed patients, 42 (75.0%) had significant depressive symptomatology (GDS≥5) and 32 (57.1%) have suffered two or more falls. Eighteen elderly patients demonstrated to use two or more benzodiazepines. There was a negative linear correlation between MMSE and GDS scores (r = -.416, p =.002). There was also a negative linear correlation between MMSE scores and number of falls in elderly (r = -.327 p =. 016). Conclusions: Benzodiazepines accounted for 21.7% of the total CAPS’ prescriptions, and 47.2% individuals treated at CAPS received benzodiazepines. Women tended to receive more prescriptions of benzodiazepines (p <.001) than men. The prevalence of significant depressive symptomatology in the elderly was very high (75.0%). As well as the incidence of falls, since more than half of the elderly patients presented two or more falls in the period. We identified a negative linear correlation between cognitive function as assessed by MMSE and depressive symptoms assessed by the GDS; and there was a negative linear correlation between MMSE and the number of falls in the elderly.

Thesis (M.Sc. (Pharmacology))--North-West University, Potchefstroom Campus, 2009.

Our investigation sought to identify the incidence of treatment failure and its associated costs in patients with methicillin-resistant Staphylococcus aureus (MRSA) skin and soft tissue infections (SSTIs) treated in the primary care setting. Thirteen clinics participated in this multi-site, observational study. Clinicians consented patients and collected clinical information, pictures, and wound swabs; isolates were processed in the principal investigator's laboratory. Treatment failure was defined as the occurrence of one or more of the following within 90 days: (1) change in antibiotic therapy, (2) subsequent need for incision and drainage, (3) SSTI at new site, (4) SSTI at same site, (5) emergency department visit, or (6) hospitalization. Cost estimates were obtained from the Agency for Healthcare Research and Quality (AHRQ) and Centers for Medicare and Medicaid Service's National Average Drug Acquisition Costs (NADAC). Patients were considered to have “moderate or complicated” SSTIs if they had a lesion ≥ 5cm in diameter, diabetes mellitus, or both. Patients not exhibiting these characteristics were classified as having “mild or uncomplicated” infections. Ninety-eight patients were enrolled. Most patients were of Hispanic ethnicity and more than half of all patients had a body mass index (BMI) ≥ 30kg/m2. The most common treatment modality was incision and drainage (I&D) plus antibiotics (57%). Treatment failure occurred in 21% of all patients at a mean additional cost of $1,933.71. Patients with moderate or complicated SSTIs who received I&D experienced significantly more treatment failures compared mild or uncomplicated patients who received I&D (36% vs. 10%; p = 0.04). The additional cost of treatment failure in patients with moderate or complicated SSTIs was nearly twice that of patients with mild or uncomplicated SSTIs ($2,093.40 vs. $1,255.02; p = 1.0). Treatment failure occurred sooner, on average, in the moderate or complicated group compared to the mild or uncomplicated group (11.8 days vs. 38.8 days; p = 0.06). Among patients with MRSA SSTIs treated in the primary care setting, the rate of treatment failure is high (21%) and costs are considerable ($1,933.71). / text

ß-hemolytic streptococci persist in 10-25% of patients with acute streptococal tonsillitis (about 10.000-25.000 per year in Sweden) in spite of treatment with a recommended dosage and schedule of Phenoxymethylpenicillin. The aim of the study was to investigate different bacteriological factors involved in treatment failures of streptococcal tonsillitis. Patients included in the study were 33 patients who underwent tonsillectomy, 62 persons included in a tonsillitis epidemic outbreak, 267 tonsillitis patients contacting the ENT-clinic, Sahlgrenska Hospital, Göteborg, and 20 healthy volunteers taking Phenoxymethylpenicillin. It was found that the Steer's steel pin replicator was a useful tool to study interference between a- and ß-hemolytic streptococci and a guantitative differen ce in. the inhibitory capacity of the different a-strains was noted, a-streptococci with a strong inhibitory capacity on ß-streptococci were isolated mainly from individuals seemingly resistant to ß-streptococcal tonsillitis, while from patients with repeated tonsillitis no or low numbers of inhibiting a-streptococci were demonstrated. Patients with clinical treatment failure had less a-streptococci with inhibiting capacity on their own ß-streptococcal strain compared with the healthy carriers. These treatment failures also showed beta-lactamase activity in their saliva pellet significantly more often than patients in the control groups. In volunteers penicillin was released from ordinary sugar coated tablets already in the mouth resulting in a decrease of the a-strep- tococcal flora. A synergistic effect on ß-hemolytic killing by low concentration of penicillin and inhibition of a-streptococci was noted in vitro and in vivo. Penicillin tolerance was registered in most strains from the treatment failure group, but in none of the strains from the group of successfully treated patients. A co-operation between different bacteriological factors (bacterial interference, beta-lactamase production, penicillin tolerance) seems to be important in treatment failures of streptococcal tonsillitis. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 1986, härtill 6 uppsatser</p> / digitalisering@umu

Tuberculosis (TB) is one of the deadliest infectious diseases of our time, with 1.4 million deaths globally, recorded in 2010 (3800 deaths a day) by the World Health Organization (WHO). Currently, South Africa ranks third on the 2011 list of 22 high-burden TB countries in the world and it was estimated that each active-TB person could potentially infect 10–15 people annually. The WHO additionally reported that in the year 2009, 87% of all TB patients worldwide were successfully treated, with a treatment success rate of 74% reported for South Africa. Despite this however, non-adherence to anti-TB treatment is still a major issue, due to it resulting in a global increased prevalence of drug resistant TB and subsequently TB treatment failure. Treatment failure is thought to be caused by a number of factors, however, it still remains largely misunderstood. One aspect of this, that isn't clearly addressed in the literature, is the underlying variation in each patient, resulting in his/her varying reaction to the drug regimen, and hence it’s varying efficacy from one patient to the next. Furthermore, little is known about the underlying variation of the host to the primary TB infection or response to the TB disease state, and how some patients have more effective mechanisms for eliminating the infection, or recovering from the disease. Considering this, a metabolomics research study using GC×GC-TOFMS was conducted, in order to identify potential metabolite markers which may be used to better characterise the underlining mechanisms associated with poor treatment outcomes (treatment failure). The first aim was to evaluate the accuracy and efficiency of the methodology used, as well as to determine the capability and accuracy of the analyst to perform these methods. In order to evaluate the GCxGC-TOFMS analytical repeatability, one QC sample was extracted and injected repeatedly (6 times) onto the GC×GC-TOFMS. Similarly, the analyst's repeatability for performing the organic acid extraction and analyses was also determined, using 10 identical QC samples, which were extracted and injected separately. CV values were subsequently calculated from the collected and processed data as a measure of this. Of all the compounds detected from the 6 QC sample repeats used for GCxGC-TOFMS repeatability, 95.59% fell below a 50% CV value, and 93,7% of all the compounds analysed for analyst repeatability had a CV < 50. Subsequently, using the above metabolomics approach, in addition to a wide variety of univariate and multivariate statistical methods, two patient outcome groups were compared. A sample group cured from TB after 6 months of treatment was compared vs a sample group where treatment failed after the 6 month period. Using urine collected from these two patient groups at various time points, the following metabolomics comparisons where made: 1) at time of diagnosis, before any anti-TB treatment was administrated, 2) during the course of treatment, in order to determine any variance in these groups due to a varying response to the anti-TB drugs, 3) over the duration of the entire 6 months treatment regimen, in order to determine if differences exist between the two groups over time. A clear natural differentiation between the cured and failed outcome groups were obtained at time of diagnosis, and a total of 39 metabolites markers were subsequently identified. These metabolites were classified according to their various origins, and included (1) those associated with the presence of M. tuberculosis bacteria, (2) those resulting from an altered host metabolism due to the TB infection, and (3) metabolites of various exogenous origins. The detailed interpretation of these metabolites suggests that a possible underlying RCD or some sort of mitochondrial dysfunction may be present in the treatment failure group, which may also be induced through an external stimulus, such as alcohol consumption. We hypothesise that this may possibly result in a far greater severity to M. tuberculosis infection in this group, subsequently causing a reduced capacity for a successful treatment outcome, also considering the critical role of the mitochondria in the metabolism of anti-TB drugs. Furthermore, 20 metabolite markers were identified when comparing the two outcome groups during the treatment phase of this metabolomics investigation. A vast majority of these 20 metabolites were also identified as markers for time 0 (time of diagnosis). Additionally, metabolites associated with anti-TB drug induced side effects, were also found to be comparatively increased in the treatment failure group, indicative of more pronounced liver damage, accompanied by metabolites characteristic of a MADD metabolite profile, due to a deficient electron transport flavoprotein, confirming previous experiments done in rats. These side effects have also previously been implicated as a major contributor of poor treatment compliance, and ultimately treatment failure. Lastly, 35 metabolite markers were identified by time dependent statistical analysis and represented those metabolites best describing the variation between the treatment outcome groups over the entire study duration (from diagnosis, to week 26). This time dependent statistical analysis identified markers, using an alternative statistical approach, and confirmed previous findings and added in a better characterisation of treatment failure. Considering the above, we successfully applied a metabolomics approach for identifying metabolites which could ultimately aid in the prediction and monitoring of treatment outcomes. This additionally led to a better understanding and or characterisation of the phenomenon known as treatment failure, as well as the underlying mechanisms related to this occurrence. / MSc (Biochemistry), North-West University, Potchefstroom Campus, 2013

Tuberculosis (TB) is one of the deadliest infectious diseases of our time, with 1.4 million deaths globally, recorded in 2010 (3800 deaths a day) by the World Health Organization (WHO). Currently, South Africa ranks third on the 2011 list of 22 high-burden TB countries in the world and it was estimated that each active-TB person could potentially infect 10–15 people annually. The WHO additionally reported that in the year 2009, 87% of all TB patients worldwide were successfully treated, with a treatment success rate of 74% reported for South Africa. Despite this however, non-adherence to anti-TB treatment is still a major issue, due to it resulting in a global increased prevalence of drug resistant TB and subsequently TB treatment failure. Treatment failure is thought to be caused by a number of factors, however, it still remains largely misunderstood. One aspect of this, that isn't clearly addressed in the literature, is the underlying variation in each patient, resulting in his/her varying reaction to the drug regimen, and hence it’s varying efficacy from one patient to the next. Furthermore, little is known about the underlying variation of the host to the primary TB infection or response to the TB disease state, and how some patients have more effective mechanisms for eliminating the infection, or recovering from the disease. Considering this, a metabolomics research study using GC×GC-TOFMS was conducted, in order to identify potential metabolite markers which may be used to better characterise the underlining mechanisms associated with poor treatment outcomes (treatment failure). The first aim was to evaluate the accuracy and efficiency of the methodology used, as well as to determine the capability and accuracy of the analyst to perform these methods. In order to evaluate the GCxGC-TOFMS analytical repeatability, one QC sample was extracted and injected repeatedly (6 times) onto the GC×GC-TOFMS. Similarly, the analyst's repeatability for performing the organic acid extraction and analyses was also determined, using 10 identical QC samples, which were extracted and injected separately. CV values were subsequently calculated from the collected and processed data as a measure of this. Of all the compounds detected from the 6 QC sample repeats used for GCxGC-TOFMS repeatability, 95.59% fell below a 50% CV value, and 93,7% of all the compounds analysed for analyst repeatability had a CV < 50. Subsequently, using the above metabolomics approach, in addition to a wide variety of univariate and multivariate statistical methods, two patient outcome groups were compared. A sample group cured from TB after 6 months of treatment was compared vs a sample group where treatment failed after the 6 month period. Using urine collected from these two patient groups at various time points, the following metabolomics comparisons where made: 1) at time of diagnosis, before any anti-TB treatment was administrated, 2) during the course of treatment, in order to determine any variance in these groups due to a varying response to the anti-TB drugs, 3) over the duration of the entire 6 months treatment regimen, in order to determine if differences exist between the two groups over time. A clear natural differentiation between the cured and failed outcome groups were obtained at time of diagnosis, and a total of 39 metabolites markers were subsequently identified. These metabolites were classified according to their various origins, and included (1) those associated with the presence of M. tuberculosis bacteria, (2) those resulting from an altered host metabolism due to the TB infection, and (3) metabolites of various exogenous origins. The detailed interpretation of these metabolites suggests that a possible underlying RCD or some sort of mitochondrial dysfunction may be present in the treatment failure group, which may also be induced through an external stimulus, such as alcohol consumption. We hypothesise that this may possibly result in a far greater severity to M. tuberculosis infection in this group, subsequently causing a reduced capacity for a successful treatment outcome, also considering the critical role of the mitochondria in the metabolism of anti-TB drugs. Furthermore, 20 metabolite markers were identified when comparing the two outcome groups during the treatment phase of this metabolomics investigation. A vast majority of these 20 metabolites were also identified as markers for time 0 (time of diagnosis). Additionally, metabolites associated with anti-TB drug induced side effects, were also found to be comparatively increased in the treatment failure group, indicative of more pronounced liver damage, accompanied by metabolites characteristic of a MADD metabolite profile, due to a deficient electron transport flavoprotein, confirming previous experiments done in rats. These side effects have also previously been implicated as a major contributor of poor treatment compliance, and ultimately treatment failure. Lastly, 35 metabolite markers were identified by time dependent statistical analysis and represented those metabolites best describing the variation between the treatment outcome groups over the entire study duration (from diagnosis, to week 26). This time dependent statistical analysis identified markers, using an alternative statistical approach, and confirmed previous findings and added in a better characterisation of treatment failure. Considering the above, we successfully applied a metabolomics approach for identifying metabolites which could ultimately aid in the prediction and monitoring of treatment outcomes. This additionally led to a better understanding and or characterisation of the phenomenon known as treatment failure, as well as the underlying mechanisms related to this occurrence. / MSc (Biochemistry), North-West University, Potchefstroom Campus, 2013

Selective antiretroviral! (ARV) drugs are primarily metabolized by cytochrome P450 (CYP) enzymes, characteristically predisposed to variation, and are therefore primarily responsible for ARV pharmacokinetic variability and associated drug interactions. For the majority of ARV drugs, the therapeutic window is narrow and imminent toxicities due to CYP inhibition or sub-therapeutic drug levels as a result of CYP induction is inevitable. Animals provide a metabolism replica to conduct detailed investigations. We endeavored to establish a rat model to screen for variability in metabolism of selective ARV drugs responsible for treatment failure and drug interactions, over time in the liver and serum. Male Sprague-Dawley rats (n = 24) were divided into 6 groups: methylcellulose, 160mg/kg/day (n = 24) (control); efavirenz, 160mg/kg/day (n = 18); ritonavir, 20 mg/kg/day (n = 18); ritonavir, 20 mg/kg/day and verapamil 5 mg/kg/day (n = 18); Kaletra® (ritonavir/lopinavir), 20 mg/kg/day, (n = 18); Kaletra® (ritonavir/lopinavir), 20 mg/kg/day and verapamil 5 mg/kg/day (n = 18). Treatment duration varied from one day (single dose), 7 or 21 days. Blood samples were collected after decapitation on days 1, 7 and 21. A sensitive and rapid liquid chromatograph (LC) interfaced to a quadrupoie mass spectrometer (MS) and coupled with electrospray ionization (ESI) method was employed for the blood sample determinations. One single injection was required to simultaneously quantify efavirenz, lopinavir and ritonavir within the linear concentration range of 78 - 5000 ng/ml. Efavirenz blood levels increased statistically significantly (p < 0.05) from day 1 to day 21 with distinct steady state achievement prior to day 7. The levels of ritonavir increased statistically significantly (p < 0.05) from day 7 to 21 when administered alone and statistically significantly (p < 0.01) from day 1 to 21 when administered as the ritonavir/lopinavir combination. The levels of lopinavir also increased statistically significantly (p<0.01) from day 1 and 21 in the ritonavir/lopinavir combination. However, the inclusion of a P-glycoprotein inhibitor, verapamil, increased both the ritonavir (administered alone) and lopinavir blood levels significantly (p < 0.05) at day 1. The ritonavir levels were also significantly increased on day 21 (p < 0.05). When verapamil was added to the ritonavir/lopinavir combination the levels of ritonavir increased statistically significantly (p < 0.01) from day 1 to 21. A rat model can be used to detect changes in metabolism over time as measured by blood levels. The influence of drug interactions, such as verapamil, on ARV drug metabolism can be investigated by this model. These results will be substantiated by PCR liver results in the future. / Thesis (M.Sc. (Pharmacology))--North-West University, Potchefstroom Campus, 2009.

Selective antiretroviral! (ARV) drugs are primarily metabolized by cytochrome P450 (CYP) enzymes, characteristically predisposed to variation, and are therefore primarily responsible for ARV pharmacokinetic variability and associated drug interactions. For the majority of ARV drugs, the therapeutic window is narrow and imminent toxicities due to CYP inhibition or sub-therapeutic drug levels as a result of CYP induction is inevitable. Animals provide a metabolism replica to conduct detailed investigations. We endeavored to establish a rat model to screen for variability in metabolism of selective ARV drugs responsible for treatment failure and drug interactions, over time in the liver and serum. Male Sprague-Dawley rats (n = 24) were divided into 6 groups: methylcellulose, 160mg/kg/day (n = 24) (control); efavirenz, 160mg/kg/day (n = 18); ritonavir, 20 mg/kg/day (n = 18); ritonavir, 20 mg/kg/day and verapamil 5 mg/kg/day (n = 18); Kaletra® (ritonavir/lopinavir), 20 mg/kg/day, (n = 18); Kaletra® (ritonavir/lopinavir), 20 mg/kg/day and verapamil 5 mg/kg/day (n = 18). Treatment duration varied from one day (single dose), 7 or 21 days. Blood samples were collected after decapitation on days 1, 7 and 21. A sensitive and rapid liquid chromatograph (LC) interfaced to a quadrupoie mass spectrometer (MS) and coupled with electrospray ionization (ESI) method was employed for the blood sample determinations. One single injection was required to simultaneously quantify efavirenz, lopinavir and ritonavir within the linear concentration range of 78 - 5000 ng/ml. Efavirenz blood levels increased statistically significantly (p < 0.05) from day 1 to day 21 with distinct steady state achievement prior to day 7. The levels of ritonavir increased statistically significantly (p < 0.05) from day 7 to 21 when administered alone and statistically significantly (p < 0.01) from day 1 to 21 when administered as the ritonavir/lopinavir combination. The levels of lopinavir also increased statistically significantly (p<0.01) from day 1 and 21 in the ritonavir/lopinavir combination. However, the inclusion of a P-glycoprotein inhibitor, verapamil, increased both the ritonavir (administered alone) and lopinavir blood levels significantly (p < 0.05) at day 1. The ritonavir levels were also significantly increased on day 21 (p < 0.05). When verapamil was added to the ritonavir/lopinavir combination the levels of ritonavir increased statistically significantly (p < 0.01) from day 1 to 21. A rat model can be used to detect changes in metabolism over time as measured by blood levels. The influence of drug interactions, such as verapamil, on ARV drug metabolism can be investigated by this model. These results will be substantiated by PCR liver results in the future. / Thesis (M.Sc. (Pharmacology))--North-West University, Potchefstroom Campus, 2009.

Diss. (sammanfattning) Linköping : Univ., 2003. / Härtill 5 uppsatser.

Introdução: Os Benzodiazepínicos estão entre as drogas mais prescritas no mundo. Possuem características ansiolíticas, hipnóticas, miorelaxantes e anticonvulsivantes. Estudos prévios evidenciam inadequações nas prescrições de benzodiazepínicos, como uso equivocado para quadros inespecíficos, tratamento prolongado e abuso por idosos. Benzodiazepínicos podem trazer sérios efeitos adversos, sobretudo em idosos, como sonolência diurna, deterioro da memória e funções cognitivas, desequilíbrio e quedas. Objetivos: Analisar a prevalência do uso de benzodiazepínicos nos pacientes do Centro de Atenção Psicossocial (CAPS) de Campo Bom-RS em um período de 24 meses (Junho de 2013 a Maio de 2015), faixa etária, frequência de dispensações, dosagens, CIDs e especialidades dos médicos prescritores; bem como possíveis relações com a função cognitiva, afetiva, e quedas em idosos. Métodos: Estudo transversal, com informações coletadas e tabuladas a partir dos prontuários e prescrições médicas do CAPS Campo Bom, bem como do seu sistema informatizado de gerenciamento (Software Multi 24 Horas). Foram obtidos dados como idade, gênero, identificação dos CIDs; bem como informações sobre prescrições de Benzodiazepínicos, como frequência, quantidade, tipo de medicamento, posologia, profissional prescritor e demais medicamentos utilizados. Critério de inclusão: utilização de qualquer benzodiazepínico disponível na rede SUS: Clonazepam 0,5mg, Clonazepam 2,5 mg/ml, Clonazepam 2mg e Diazepam 5mg. Foram aplicados os testes MEEM e GDS nos pacientes idosos, em entrevistas individuais, nas quais também se avaliou a escolaridade, ocorrência e frequência de quedas, além das comorbidades auto relatadas. Para construção do banco de dados foi utilizado o Software Microsoft® Office Excel® 2007, e para análise estatística o Software PASW V18 (SPSS®). Resultados: O número total de pacientes ativos identificados no CAPS foi de 855 indivíduos, sendo 543 (63,5%) mulheres e 84 idosos (9,8%). A prevalência de utilização de BZD nesta população representou 47,2% (n=404 indivíduos). Foram identificadas 12.680 prescrições médicas dispensadas e, deste total, a prevalência de prescrições de benzodiazepínicos foi de 21,7% (n=2.748). Dentre os pacientes que receberam BZD, 297 (73,5%) eram mulheres e 59 idosos (14,6%), dos quais 56 foram entrevistados. Dentre os idosos entrevistados, 42 (75,0%) possuíram significativa sintomatologia depressiva (GDS≥5) e 32 (57,1%) apresentaram duas ou mais quedas no período de 1 ano. Dezoito pacientes idosos demonstraram fazer uso de dois ou mais BZDs. Houve correlação linear negativa entre os escores do MEEM e do GDS (r = - ,416; p=,002). Houve também uma correlação linear negativa entre o escore do MEEM e número de quedas em idosos (r = -,327 p=,016). Conclusões: Os benzodiazepínicos corresponderam a 21,7 % do total de prescrições do CAPS e do total dos indivíduos 47,2% receberam benzodiazepínicos. Proporcionalmente aos homens, as mulheres tenderam a receber mais prescrições de benzodiazepínicos (p<.001). A prevalência de significativa sintomatologia depressiva nos idosos usuários do CAPS foi alta (75,0%), assim como a incidência de quedas, sendo que mais da metade dos idosos caiu 2 ou mais vezes no período. Identificou-se uma correlação linear negativa entre a função cognitiva como avaliada pelo MEEM e a sintomatologia depressiva avaliada pelo GDS; bem como houve uma correlação linear negativa entre o MEEM e o número de quedas em idosos. / Introduction: Benzodiazepines are among the most prescribed drugs in the world, they have characteristics such as anxiolytic, hypnotic, muscle relaxants and anticonvulsants. Studies have pointed out distortions in benzodiazepines’ prescriptions, such as misuse for unspecific cases, prolonged treatment and use by elderly. Such medications may cause serious damage, particularly in the elderly, and its continued use causes side effects such as daytime somnolence, imbalance, memory and cognitive function loss, increased incidence of falls. Objectives: To assess the prevalence of benzodiazepine use among patients of the Center for Psychosocial Care in Campo Bom-RS within the period of June 2013 to May 2015. The variables analyzed were: age, frequency of dispensations, dosages, ICDs and specialties of prescribing doctors; as well as possible correlations between cognitive function, emotional function and falls in the elderly. Methods: Cross-sectional study, with data collected and tabulated from medical records and prescriptions, as well as from the management system from CAPS (Software Multi 24 hours). Data obtained was age, gender, ICDs identification; as well as frequency of prescriptions, quantity and type of medication, dosage, prescribing professional, others used drugs. Inclusion criteria: Use of any benzodiazepine available in the Health Unic System: Clonazepam 0,5 mg, Clonazepam 2,5 mg/ml, Clonazepam 2 mg and Diazepam 5mg. MMSE and GDS tests have been applied in the elderly, through individual interviews, in which we found about educational level, occurrence and frequency of falls and other self-reported comorbidities. The software Microsoft® Excel® 2007 was used to build database, and for statistical analysis the software PASW V18 (SPSS) was used. Results: The total number of active patients identified at CAPS was 855 individuals, of these 543 were women (63.5%) and 84 elderly (9.8%). The prevalence of benzodiazepines’ use in this population was 47.2 % (n = 404). We have found 12.680 prescriptions dispensed and the prevalence of benzodiazepines’ prescriptions was 21.7 % (n = 2.748). Among patients who received benzodiazepines, 297 (73.5%) were women and 59 elderly (14.6%), of these 56 were interviewed. From the interviewed patients, 42 (75.0%) had significant depressive symptomatology (GDS≥5) and 32 (57.1%) have suffered two or more falls. Eighteen elderly patients demonstrated to use two or more benzodiazepines. There was a negative linear correlation between MMSE and GDS scores (r = -.416, p =.002). There was also a negative linear correlation between MMSE scores and number of falls in elderly (r = -.327 p =. 016). Conclusions: Benzodiazepines accounted for 21.7% of the total CAPS’ prescriptions, and 47.2% individuals treated at CAPS received benzodiazepines. Women tended to receive more prescriptions of benzodiazepines (p <.001) than men. The prevalence of significant depressive symptomatology in the elderly was very high (75.0%). As well as the incidence of falls, since more than half of the elderly patients presented two or more falls in the period. We identified a negative linear correlation between cognitive function as assessed by MMSE and depressive symptoms assessed by the GDS; and there was a negative linear correlation between MMSE and the number of falls in the elderly.