Prolongación del tiempo QT
Eventos adversos de medicamentos
|Dolor de cabeza|
Variantes ✨Para la evaluación computacionalmente intensiva de las variantes, elija la suscripción estándar paga.
Explicaciones de las sustancias para pacientes.
Se recomienda la monitorización de paroxetina y lorazepam.
Mayor efecto de amortiguación centralMecanismo: Ambas sustancias tienen un efecto depresor del SNC.
Efecto: posible refuerzo mutuo de los efectos amortiguadores centrales como la sedación y la reducción de la vigilancia.
Medidas: Preste atención al aumento de los síntomas depresores centrales, si es necesario reducción de la dosis.
|Paroxetina||1 [0.4,5.57] 1||1|
Los cambios informados en la exposición corresponden a los cambios en la curva de concentración plasmática-tiempo [ AUC ]. No esperamos ningún cambio en la exposición a lorazepam, cuando se combina con paroxetina (100%). No esperamos ningún cambio en la exposición a paroxetina, cuando se combina con lorazepam (100%). El AUC se encuentra entre 0 % y 100 % dependiendo del
Los parámetros farmacocinéticos de la población media se utilizan como punto de partida para calcular los cambios individuales en la exposición debidos a las interacciones.
La lorazepam tiene una alta biodisponibilidad oral [ F ] del 100 %, por lo que el nivel plasmático máximo [Cmax] tiende a cambiar poco durante una interacción. La vida media terminal [ t12 ] es de 14.3 horas y se alcanzan niveles plasmáticos constantes [ Css ] después de aproximadamente 57.2 horas. La unión a proteínas [ Pb ] es moderadamente fuerte al 100 % y el volumen de distribución [ Vd ] es muy grande a 111 litros. El metabolismo no tiene lugar a través de los citocromos comunes y el transporte activo tiene lugar especialmente a través de UGT2B7.
La paroxetina tiene una baja biodisponibilidad oral [ F ] del 100 %, por lo que el nivel plasmático máximo [Cmax] tiende a cambiar fuertemente con una interacción. La vida media terminal [ t12 ] es de 16 horas y se alcanzan niveles plasmáticos constantes [ Css ] después de aproximadamente 64 horas. La unión a proteínas [ Pb ] es moderadamente fuerte al 100 % y el volumen de distribución [ Vd ] es muy grande a 274 litros, por eso, con una tasa de extracción hepática media de 0,9, tanto el flujo sanguíneo hepático [Q] como un cambio en la unión a proteínas [Pb] son relevantes. El metabolismo tiene lugar a través de CYP1A2, CYP2C19, CYP2D6 y CYP3A4, entre otros y el transporte activo tiene lugar especialmente a través de PGP.
|Efectos serotoninérgicos a||2||Ø||++|
Recomendación: Como medida de precaución, se deben tener en cuenta los síntomas de sobreestimulación serotoninérgica, especialmente después de aumentar la dosis y en dosis en el rango terapéutico superior.
Clasificación: La paroxetina modula el sistema serotoninérgico en un grado moderado. El riesgo de síndrome serotoninérgico se puede clasificar como bajo con este medicamento si la dosis se encuentra en el rango habitual. Según nuestro conocimiento, la lorazepam no aumenta la actividad serotoninérgica.
|Kiesel & Durán b||1||Ø||+|
Recomendación: Como precaución, se debe prestar atención a los síntomas anticolinérgicos, especialmente después de aumentar la dosis y en dosis en el rango terapéutico superior.
Clasificación: La paroxetina solo tiene un efecto leve sobre el sistema anticolinérgico. El riesgo de síndrome anticolinérgico con este medicamento es relativamente bajo si la dosis se encuentra en el rango habitual. El efecto anticolinérgico de la lorazepam no es relevante.
Prolongación del tiempo QT
Recomendación: Asegúrese de minimizar los factores de riesgo que puedan influir. Deben compensarse los desequilibrios electrolíticos, como los niveles bajos de calcio, potasio y magnesio. Debe utilizarse la dosis mínima eficaz de paroxetina.
Clasificación: La paroxetina puede prolongar potencialmente el tiempo QT y, si existen factores de riesgo, pueden producirse arritmias del tipo torsades de pointes. No conocemos ningún potencial de prolongación del intervalo QT de la lorazepam.
Efectos adversos generales
|Efectos secundarios||∑ frecuencia||lor||par|
|Dolor de cabeza||22.0 %||n.a.||22.0|
|Eyaculación anormal||20.5 %||n.a.||20.5|
Xerostomía (9.5%): paroxetina
Estreñimiento (9%): paroxetina
Pérdida de apetito (6.5%): paroxetina
Hemorragia gastrointestinal: paroxetina
Temblor (7.5%): paroxetina
Trastorno del sueño: paroxetina
Incautación: lorazepam, paroxetina
Reduccion de la libido (7.5%): paroxetina
Disfunción eréctil (6%): paroxetina
Trastorno del orgasmo (6%): paroxetina
Visión borrosa (5%): paroxetina
Efecto hangover: lorazepam
Efecto rebote: lorazepam
Depresion respiratoria: lorazepam
Síndrome de Stevens-Johnson: paroxetina
Necrolisis epidérmica toxica: paroxetina
Tiempo de sangrado prolongado: paroxetina
Reacción anafiláctica: paroxetina
Con base en sus respuestas e información científica, evaluamos el riesgo individual de efectos secundarios adversos. Estas recomendaciones están destinadas a asesorar a los profesionales y no sustituyen la consulta con un médico. En la versión de prueba restringida (alfa), el riesgo de todas las sustancias aún no se ha evaluado de manera concluyente.
Abstract: No Abstract available
Abstract: The relationship between the selective serotonin reuptake inhibitor paroxetine and the sparteine oxidation polymorphism was investigated in a combined single-dose (30 mg) and steady-state (30 mg/day for 2 weeks) study including a panel of nine extensive metabolizers and eight poor metabolizers of sparteine. The median area under the plasma concentration-time curve (AUC) after the first paroxetine dose was about seven times higher in poor metabolizers than in extensive metabolizers (3910 versus 550 nmol.hr/L), whereas at steady state the median AUCss tau interphenotype difference was only twofold (4410 versus 2550 nmol.hr/L). Plasma half-life and steady-state plasma concentration were significantly longer and higher, respectively, in poor metabolizers than in extensive metabolizers (41 versus 16 hours and 151 versus 81 nmol/L). Paroxetine pharmacokinetics were linear in poor metabolizers and nonlinear only in extensive metabolizers. Sparteine metabolic ratio (MR = 12 hour urinary ratio of sparteine/dehydrosparteine), increased during treatment with paroxetine in subjects who were extensive metabolizers, and after 14 days treatment two extensive metabolizers were phenotyped as poor metabolizers and the remaining extensive metabolizers were changed into extremely slow extensive metabolizers with sparteine MRs of 5.7 to 16.5. The inhibition of sparteine metabolism was rapidly reversed after cessation of paroxetine administration. In the poor metabolizers there were no significant changes in MRs during the study. It is concluded that paroxetine and sparteine metabolism cosegregates, but the interphenotype difference in metabolism was less prominent at steady state than after a single dose, presumably because of saturation of the sparteine oxygenase (CYP2D6) in subjects who were extensive metabolizers. Paroxetine is a potent inhibitor of sparteine oxidation by CYP2D6 in vivo.
Abstract: Paroxetine is well absorbed from the gastrointestinal tract, and appears to undergo first-pass metabolism which is partially saturable. Consistent with its lipophilic amine character, paroxetine is extensively distributed into tissues. Its plasma protein binding at therapeutically relevant concentrations is about 95%. Paroxetine is eliminated by metabolism involving oxidation, methylation, and conjugation. All of these factors lead to wide interindividual variation in the pharmacokinetics of paroxetine. Renal clearance of the compound is negligible. The major metabolites of paroxetine are conjugates which do not compromise its selectivity nor contribute to the clinical response. Ascending single-dose studies reveal that the pharmacokinetics of paroxetine are non-linear to a limited extent in most subjects and to a marked degree in only a few. Also, steady-state pharmacokinetic parameters are not predictable from single-dose data. In many subjects, daily administration of 20-50 mg of paroxetine leads to little or no disproportionality in plasma levels with dose, although in a few subjects this phenomenon is evident. Steady-state plasma concentrations are generally achieved within 7 to 14 days. The terminal half-life is about one day, although there is a wide intersubject variability (e.g. with 30 mg, a range of 7-65 hours was observed in a group of 28 healthy young subjects). In elderly subjects there is wide interindividual variation in steady-state pharmacokinetic parameters, with statistically significantly higher plasma concentrations and slower elimination than in younger subjects, although there is a large degree of overlap in the ranges of corresponding parameters. In severe renal impairment higher plasma levels of paroxetine are achieved than in healthy individuals after single dose. In moderate hepatic impairment the pharmacokinetics after single doses are similar to those of normal subjects. Paroxetine is not a general inducer or inhibitor of hepatic oxidation processes, and has little or no effect on the pharmacokinetics of other drugs examined. Its metabolism and pharmacokinetics are to some degree affected by the induction or inhibition of drug metabolizing enzyme(s). From a pharmacokinetic standpoint, drug interactions involving paroxetine are considered unlikely to be a frequent occurrence. Data available have failed to reveal any correlation between plasma concentrations of paroxetine and its clinical effects (either efficacy or adverse events).
Abstract: Healthy volunteers received single doses of three benzodiazepines (diazepam, 10 mg i.v.; alprazolam, 1.0 mg orally; lorazepam, 2 mg i.v.) on two occasions in random sequence. One trial was a control; for the other, subjects ingested propoxyphene, 65 mg every 6 h, for the duration of the benzodiazepine study. The kinetics of each benzodiazepine were determined from multiple plasma concentrations measured following each dose. For diazepam, propoxyphene produced a small and statistically insignificant prolongation of elimination half-life (43 vs 38 h) and reduction of total clearance (0.41 vs 0.47 ml min-1 kg-1). Propoxyphene significantly prolonged alprazolam half-life (18 vs 12 h, P less than 0.005) and reduced total clearance (0.8 vs 1.3 ml min-1 kg-1, P less than 0.005). Propoxyphene had no apparent influence on lorazepam half-life (13.4 vs 13.5 h) or clearance (1.5 vs 1.4 ml min-1 kg-1). Thus propoxyphene significantly impairs the clearance of alprazolam, biotransformed mainly by the oxidative reaction of aliphatic hydroxylation. Propoxyphene has far less effect on the oxidation of diazepam by N-demethylation, and has no apparent influence on lorazepam conjugation.
Abstract: Eleven subjects received acetaminophen (650 mg i.v.) on two occasions in random sequence, with and without concurrent administration of probenecid (500 mg) every 6 hr. Nine subjects similarly received lorazepam (2 mg. i.v.) with and without concurrent probenecid. Acetaminophen half-life was prolonged during probenecid treatment (mean +/- S.E., 4.30 +/- 0.23 vs. 2.51 +/- 0.16 hr; P less than .001) due to markedly decreased clearance (178 +/- 13 vs. 329 +/- 24 ml/min; P less than .001) with no change in volume of distribution (65 +/- 4 vs. 69 +/- 3 l; NS). Urinary excretion of acetaminophen glucuronide during 24 hr was decreased (84 +/- 9 vs. 260 +/- 21 mg of acetaminophen as glucuronide; P less than .001) and acetaminophen sulfate excretion was increased (323 +/- 25 vs. 217 +/- 17 mg of acetaminophen as sulfate; P less than .005) during concurrent probenecid treatment. However, the sum of the two conjugated metabolites was not significantly different (407 +/- 28 vs. 476 +/- 20 mg of acetaminophen as glucuronide plus sulfate excreted per 24 hr; NS). Lorazepam half-life was also prolonged during probenecid treatment (33.0 +/- 3.9 vs. 14.3 +/- 1.08 hr; P less than .001) due to decreased clearance (44.7 +/- 5.4 vs. 80.3 +/- 13.2 ml/min; P less than .001) with no change in volume of distribution (111 +/- 5 vs. 111 +/- 7 l; NS). Formation of the ether glucuronides of acetaminophen and lorazepam is impaired markedly by therapeutic doses of probenecid. Sulfate conjugation is not affected.(ABSTRACT TRUNCATED AT 250 WORDS)
Abstract: No Abstract available
Abstract: Paroxetine is a trans-isomeric phenylpiperidine with antidepressant properties induced by selective inhibition of the neuronal high affinity uptake of serotonin. In comparison with other selective serotonin uptake inhibitors paroxetine is 2 to 23 times more potent. With the exception of a low affinity to muscarinic receptors, which is not relevant for therapeutic effects, it does not interact directly with monoamine neurotransmitter receptors. Paroxetine is applied orally at single daily doses of 20 to 50 mg and well absorbed from the gastrointestinal tract. It undergoes a partially saturated first pass metabolism which reduces the bioavailability at therapeutic doses to about 30-60%. Maximal blood levels are reached 2 to 8 hours after oral administration. In the plasma 95% of the drug are bound to protein. Paroxetine is eliminated after transformation in the liver into pharmacologically inactive metabolites. High affinity to the cytochrome P450 isoenzyme CYP2D6 indicates that interferences occur with other drugs which are metabolized via the same isoenzyme. Although clinical practice has not reported problematic drug interactions so far, comedications with tricyclic antidepressants should be avoided. The most frequent side effects of paroxetine concern nausea and somnolescence. Since cardiotoxicity or other toxic side effects are much less frequent than under tricyclic antidepressants paroxetine seems advantageous in elderly patients. The onset of antidepressant effects requires several weeks as known for all currently available antidepressants. The pharmacokinetic and pharmacodynamic properties of paroxetine taken together indicate that this selective serotonin uptake inhibitor seems advantageous to other antidepressant agents because of its high selectivity and poor toxicity.
Abstract: We report on a case of serotonin syndrome associated to the use of the paroxetine, a serotonin reuptake inhibitor drug. Serotonin syndrome related to this drug not combined with other drugs had not yet been described in literature.
Abstract: OBJECTIVE: To evaluate the kinetics and dynamics of lorazepam during administration as a bolus plus an infusion, using electroencephalography as a pharmacodynamic end point. METHODS: Nine volunteers received a 2-mg bolus loading dose of lorazepam, coincident with the start of a 2 microg/kg/hr zero-order infusion. The infusion was stopped after 4 hrs. Plasma lorazepam concentrations and electroencephalographic activity in the 13- to 30-Hz range were monitored for 24 hrs. RESULTS: The bolus-plus-infusion scheme rapidly produced plasma lorazepam concentrations that were close to those predicted to be achieved at true steady state. Mean kinetic values for lorazepam were as follows: volume of distribution, 126 L; elimination half-life, 13.8 hrs; and clearance, 109 mL/min. Electroencephalographic effects were maximal 0.5 hr after the loading dose, were maintained essentially constant during infusion, and then declined in parallel with plasma concentrations after the infusion was terminated. There was no evidence of tolerance. Plots of pharmacodynamic electroencephalographic effect vs. plasma lorazepam concentration demonstrated counterclockwise hysteresis, consistent with an effect-site equilibration delay. This was incorporated into a kinetic-dynamic model in which hypothetical effect-site concentration was related to pharmacodynamic electroencephalographic effect via the sigmoid Emax model. The analysis yielded the following mean estimates: maximum electroencephalographic effect, 12.7% over baseline; 50% effective concentration, 13.1 ng/mL; and effect-site equilibration half-life, 8.8 mins. CONCLUSION: Despite the delay in effect onset, continuous infusion of lorazepam, preceded by a bolus loading dose, produces a relatively constant sedative effect on the central nervous system, which can be utilized in the context of critical care medicine.
Abstract: OBJECTIVE: To describe a case of serotonin syndrome due to paroxetine and ethanol. CASE SUMMARY: A 57-year-old white man was brought to the emergency department one day after ingesting paroxetine 3600 mg and a pint of hard liquor. He denied the use of any other drug or herbal products and regular use of alcohol. Upon arrival to the hospital, vital signs were blood pressure 188/103 mm Hg, heart rate 114 beats/min, respiratory rate 28 breaths/min, temperature 36.8 degrees C, and O2 saturation 96% on room air. Findings on physical examination included dilated pupils, facial flushing, diaphoresis, shivering, myoclonic jerks, tremors, and hyperreflexia. A tentative diagnosis of serotonin syndrome was made. Initially, cyproheptadine 8 mg was administered orally with no observable effect. An additional 12 mg was given in 3 doses over 24 hours. Symptoms abated slowly over the next 6 days, during which a thorough evaluation failed to reveal any other potential causes for the patient's condition. Serum paroxetine concentrations at 27.5 and 40 hours after ingestion were 1800 and 1600 ng/mL, respectively (normal 20-200 ng/mL). DISCUSSION: Serotonin syndrome is rarely reported in patients taking only one serotonergic medication. Although serum paroxetine concentrations have not been shown to correlate with efficacy or toxicity, our patient's serum paroxetine concentration was 9 times the upper end of the therapeutic range. Cyproheptadine, which has been suggested as a therapy, did not appear beneficial in this patient. Use of the Naranjo probability scale indicated a probable relationship between the serotonin syndrome and the overdose of paroxetine taken by this patient. CONCLUSIONS: More studies are needed to better assess the role of cyproheptadine and other serotonin antagonists in the management of the serotonin syndrome. Regardless of the use of cyproheptadine or other agents, attention should be paid to fluid status, decontamination, and management of hyperthermia, agitation, and seizures.
Abstract: This investigation aimed to provide evidence on the lack of pharmacokinetic interaction of paroxetine (20 mg/d) and alprazolam (1 mg/d) in combined therapy. In addition, the central effects of both drugs when administered alone and in combination were assessed to rule out any relevant synergistic depressant central effect. Twenty-five healthy young adult volunteers participated in a double-blind, double-dummy, placebo-controlled, repeated dose (15 days), 4-period crossover study. Each subject received each of 4 treatment sequences (ie, paroxetine-alprazolam placebo, alprazolam-paroxetine placebo, paroxetine-alprazolam, and paroxetine placebo-alprazolam placebo) in randomized order. The ratios for area under the curve within a dosing interval and maximum plasma concentration of the paroxetine plus alprazolam sequence to single agent paroxetine were 1.07 (90% confidence interval = 0.99 to 1.16) and 1.05 (90% confidence interval = 0.97 to 1.13), respectively, with no statistically significant differences between the 2 treatments. Similarly, for alprazolam, ratios for the combined to the single treatment sequence were 0.99 (90% confidence interval = 0.93 to 1.05) and 1.00 (90% confidence interval = 0.94 to 1.07) for area under the curve within a dosing interval and maximum plasma concentration, respectively, showing no evidence for interaction. Comparative pharmacodynamics on the combination was assessed using 6 Psychomotor Performance Tests and 5 Visual Analogue Scales focused on mood variables. Alprazolam and paroxetine plus alprazolam induced similar and significant performance impairment and sedation after both single and repeated dose administration, being less evident on day 15. After dosing, paroxetine plus alprazolam showed a lower recovery pattern than alprazolam alone, especially on day 15. No treatment sequence showed cumulative effects after repeated dose administration. Psychomotor Performance Tests and Visual Analogue Scales data suggested lack of pharmacodynamic interactions. Accordingly, study results showed no evidence for pharmacologic interactions between paroxetine and alprazolam at steady state. The most commonly reported adverse event was drowsiness, with a higher incidence under both single and combined alprazolam treatments.
Abstract: The present study investigates the kinetic disposition with focus on the racemization, glucuronidation capacity and the transplacental transfer of lorazepam in term parturients during labor. The study was conducted on 10 healthy parturients aged 18-37 years with a gestational age of 36-40.1 weeks, treated with a single oral dose of 2 mg racemic lorazepam 2-9 h before delivery. Maternal venous blood and urine samples were obtained over a 0-48 h interval and the umbilical cord sample was obtained immediately after clamping. Lorazepam enantiomers were determined in plasma and urine samples by LC-MS/MS using a Chiralcel OD-R column. In vitro racemization of lorazepam required the calculation of the pharmacokinetic parameters as isomeric mixtures. The data were fitted to two-compartment model and the pharmacokinetic parameters are reported as means (95% CI): t(1/2a) 3.2h (2.6-3.7 h), K(a) 0.23 h(-1) (0.19-0.28 h(-1)), t(1/2) 10.4h (9.4-11.3h), beta 0.068 h(-1) (0.061-0.075h(-1)), AUC(0-infinity) 175.3(ngh)/ml (145.7-204.8(ngh)/ml), Cl/F 2.6 ml/(minkg) (2.3-2.9 ml/(minkg)), Vd/F178.8l (146.5-211.1l), Fel 0.3% (0.1-0.5%), and Cl(R) 0.010 ml/(minkg) (0.005-0.015 ml/(minkg)). Placental transfer of lorazepam evaluated as the ratio of vein umbilical/maternal vein plasma concentrations, obtained as an isomeric mixture, was 0.73 (0.52-0.94). Pregnancy changes the pharmacokinetics of lorazepam, with an increase in the apparent distribution volume, an increase in apparent oral clearance, and a reduction of elimination half-life. The increase in oral clearance may indicate an increase in glucuronidation capacity, with a possible reduction in the plasma concentrations of drugs depending on glucuronidation capacity as the major metabolic pathway.
Abstract: Anticholinergic Drug Scale (ADS) scores were previously associated with serum anticholinergic activity (SAA) in a pilot study. To replicate these results, the association between ADS scores and SAA was determined using simple linear regression in subjects from a study of delirium in 201 long-term care facility residents who were not included in the pilot study. Simple and multiple linear regression models were then used to determine whether the ADS could be modified to more effectively predict SAA in all 297 subjects. In the replication analysis, ADS scores were significantly associated with SAA (R2 = .0947, P < .0001). In the modification analysis, each model significantly predicted SAA, including ADS scores (R2 = .0741, P < .0001). The modifications examined did not appear useful in optimizing the ADS. This study replicated findings on the association of the ADS with SAA. Future work will determine whether the ADS is clinically useful for preventing anticholinergic adverse effects.
Abstract: OBJECTIVE: Paroxetine is believed to be a substrate of CYP2D6. However, no information was available indicating drug interaction between paroxetine and inhibitors of CYP2D6. The aim of this study was to examine the effects of terbinafine, a potent inhibitor of CYP2D6, on pharmacokinetics of paroxetine. METHODS: Two 6-day courses of either a daily 150-mg of terbinafine or a placebo, with at least a 4-week washout period, were conducted. Twelve volunteers took a single oral 20-mg dose of paroxetine on day 6 of both courses. Plasma concentrations of paroxetine were monitored up to 48 h after dosing. RESULTS: Compared with the placebo, terbinafine treatment significantly increased the peak plasma concentration (C(max)) of paroxetine, by 1.9-fold (6.4 +/- 2.4 versus 12.1 +/- 2.9 ng/ml, p < 0.001), and the area under the plasma concentration-time curve from zero to 48 h [AUC (0-48)] of paroxetine by 2.5-fold (127 +/- 67 vs 318 +/- 102 ng/ml, p < 0.001). Elimination half-life differed significantly (15.3 +/- 2.4 vs 22.7 +/- 8.8 h, p < 0.05), although the magnitude of alteration (1.4-fold) was smaller than C(max )or AUC. CONCLUSION: The present study demonstrated that the metabolism of paroxetine after a single oral dose was inhibited by terbinafine, suggesting that inhibition of CYP2D6 activity may lead to a change in the pharmacokinetics of paroxetine. However, further study is required to confirm this phenomenon at steady state.
Abstract: A recent in vitro study has shown that paroxetine is a substrate of P-glycoprotein. However, there was no in vivo information indicating the involvement of P-glycoprotein on the pharmacokinetics of paroxetine. The aim of this study was to examine the effects of itraconazole, a P-glycoprotein inhibitor, on the pharmacokinetics of paroxetine. Two 6 day courses of either 200 mg itraconazole daily or placebo with at least a 4 week washout period were conducted. Thirteen volunteers took a single oral 20 mg dose of paroxetine on day 6 of both courses. Plasma concentrations of paroxetine were monitored up to 48 hours after the dosing. Compared with placebo, itraconazole treatment significantly increased the peak plasma concentration (Cmax) of paroxetine by 1.3 fold (6.7 +/- 2.5 versus 9.0 +/- 3.3 ng/mL, P < 0.05) and the area under the plasma concentration-time curve from zero to 48 hours [AUC (0-48)] of paroxetine by 1.5 fold (137 +/- 73 versus 199 +/- 91 ng*h/mL, P < 0.01). Although elimination half-life differed significantly (16.1 +/- 3.4 versus 18.8 +/- 5.9 hours, P < 0.05), the alteration was small (1.1 fold). The present study demonstrated that the bioavailability of paroxetine was increased by itraconazole, suggesting a possible involvement of P-glycoprotein in the pharmacokinetics of paroxetine.
Abstract: Human immunodeficiency virus-infected patients have an increased risk for depression. Despite the high potential for drug-drug interactions, limited data on the combined use of antidepressants and antiretrovirals are available. Theoretically, ritonavir-boosted protease inhibitors may inhibit CYP2D6-mediated metabolism of paroxetine. We wanted to determine the effect of fosamprenavir-ritonavir on paroxetine pharmacokinetics and vice versa and to evaluate the safety of the combination. Group A started with 20 mg paroxetine every day for 10 days; after a wash-out period of 16 days, subjects received paroxetine (20 mg every day) plus fosamprenavir-ritonavir (700/100 mg twice a day) from days 28 to 37. Group B received the regimens in reverse order. On days 10 and 37, pharmacokinetic curves were recorded. Twenty-six healthy subjects (18 females, 8 males) were included. Median (range) age and weight were 44.4 (18.2 to 64.3) years and 68.8 (51.0 to 89.4) kg. Three subjects were excluded (two because of adverse events; one for nonadherence). Addition of fosamprenavir-ritonavir to paroxetine resulted in a significant decrease in paroxetine exposure: the geometric mean ratios (90% confidence intervals) of paroxetine plus fosamprenavir-ritonavir to paroxetine alone were 0.45 (0.41 to 0.49) for the area under the concentration-time curve from 0 to 24 h (AUC(0-24)), 0.49 (0.45 to 0.53) for the maximum concentration of the drug in plasma (C(max)), and 0.75 (0.71 to 0.80) for the apparent elimination half-life (t(1/2)). The free fraction of paroxetine showed a median (interquartile range) increase of 30% (18 to 42%) after the addition of fosamprenavir-ritonavir. The AUC(0-12), C(max), C(min), and t(1/2) of amprenavir and ritonavir were similar to those of historical controls. No serious adverse events occurred. Fosamprenavir-ritonavir reduced total paroxetine exposure by 55%. This is partly explained by protein displacement of paroxetine. We think that this interaction is clinically relevant and that titration to a higher dose of paroxetine may be necessary to accomplish the needed antidepressant effect.
Abstract: BACKGROUND: Adverse effects of anticholinergic medications may contribute to events such as falls, delirium, and cognitive impairment in older patients. To further assess this risk, we developed the Anticholinergic Risk Scale (ARS), a ranked categorical list of commonly prescribed medications with anticholinergic potential. The objective of this study was to determine if the ARS score could be used to predict the risk of anticholinergic adverse effects in a geriatric evaluation and management (GEM) cohort and in a primary care cohort. METHODS: Medical records of 132 GEM patients were reviewed retrospectively for medications included on the ARS and their resultant possible anticholinergic adverse effects. Prospectively, we enrolled 117 patients, 65 years or older, in primary care clinics; performed medication reconciliation; and asked about anticholinergic adverse effects. The relationship between the ARS score and the risk of anticholinergic adverse effects was assessed using Poisson regression analysis. RESULTS: Higher ARS scores were associated with increased risk of anticholinergic adverse effects in the GEM cohort (crude relative risk [RR], 1.5; 95% confidence interval [CI], 1.3-1.8) and in the primary care cohort (crude RR, 1.9; 95% CI, 1.5-2.4). After adjustment for age and the number of medications, higher ARS scores increased the risk of anticholinergic adverse effects in the GEM cohort (adjusted RR, 1.3; 95% CI, 1.1-1.6; c statistic, 0.74) and in the primary care cohort (adjusted RR, 1.9; 95% CI, 1.5-2.5; c statistic, 0.77). CONCLUSION: Higher ARS scores are associated with statistically significantly increased risk of anticholinergic adverse effects in older patients.
Abstract: The objective of this study was to measure the anticholinergic activity (AA) of medications commonly used by older adults. A radioreceptor assay was used to investigate the AA of 107 medications. Six clinically relevant concentrations were assessed for each medication. Rodent forebrain and striatum homogenate was used with tritiated quinuclidinyl benzilate. Drug-free serum was added to medication and atropine standard-curve samples. For medications that showed detectable AA, average steady-state peak plasma and serum concentrations (C(max)) in older adults were used to estimate relationships between in vitro dose and AA. All results are reported in pmol/mL of atropine equivalents. At typical doses administered to older adults, amitriptyline, atropine, clozapine, dicyclomine, doxepin, L-hyoscyamine, thioridazine, and tolterodine demonstrated AA exceeding 15 pmol/mL. Chlorpromazine, diphenhydramine, nortriptyline, olanzapine, oxybutynin, and paroxetine had AA values of 5 to 15 pmol/mL. Citalopram, escitalopram, fluoxetine, lithium, mirtazapine, quetiapine, ranitidine, and temazepam had values less than 5 pmol/mL. Amoxicillin, celecoxib, cephalexin, diazepam, digoxin, diphenoxylate, donepezil, duloxetine, fentanyl, furosemide, hydrocodone, lansoprazole, levofloxacin, metformin, phenytoin, propoxyphene, and topiramate demonstrated AA only at the highest concentrations tested (patients with above-average C(max) values, who receive higher doses, or are frail may show AA). The remainder of the medications investigated did not demonstrate any AA at the concentrations examined. Psychotropic medications were particularly likely to demonstrate AA. Each of the drug classifications investigated (e.g., antipsychotic, cardiovascular) had at least one medication that demonstrated AA at therapeutic doses. Clinicians can use this information when choosing between equally efficacious medications, as well as in assessing overall anticholinergic burden.
Abstract: OBJECTIVES: To examine the longitudinal relationship between cumulative exposure to anticholinergic medications and memory and executive function in older men. DESIGN: Prospective cohort study. SETTING: A Department of Veterans Affairs primary care clinic. PARTICIPANTS: Five hundred forty-four community-dwelling men aged 65 and older with diagnosed hypertension. MEASUREMENTS: The outcomes were measured using the Hopkins Verbal Recall Test (HVRT) for short-term memory and the instrumental activity of daily living (IADL) scale for executive function at baseline and during follow-up. Anticholinergic medication use was ascertained using participants' primary care visit records and quantified as total anticholinergic burden using a clinician-rated anticholinergic score. RESULTS: Cumulative exposure to anticholinergic medications over the preceding 12 months was associated with poorer performance on the HVRT and IADLs. On average, a 1-unit increase in the total anticholinergic burden per 3 months was associated with a 0.32-point (95% confidence interval (CI)= 0.05-0.58) and 0.10-point (95% CI=0.04-0.17) decrease in the HVRT and IADLs, respectively, independent of other potential risk factors for cognitive impairment, including age, education, cognitive and physical function, comorbidities, and severity of hypertension. The association was attenuated but remained statistically significant with memory (0.29, 95% CI=0.01-0.56) and executive function (0.08, 95% CI=0.02-0.15) after further adjustment for concomitant non-anticholinergic medications. CONCLUSION: Cumulative anticholinergic exposure across multiple medications over 1 year may negatively affect verbal memory and executive function in older men. Prescription of drugs with anticholinergic effects in older persons deserves continued attention to avoid deleterious adverse effects.
Abstract: BACKGROUND: Cognitive decline is common in Parkinson's disease (PD). Although some of the aetiological factors are known, it is not yet known whether drugs with anticholinergic activity (AA) contribute to this cognitive decline. Such knowledge would provide opportunities to prevent acceleration of cognitive decline in PD. OBJECTIVE: To study whether the use of agents with anticholinergic properties is an independent risk factor for cognitive decline in patients with PD. METHODS: A community-based cohort of patients with PD (n=235) were included and assessed at baseline. They were reassessed 4 and 8 years later. Cognition was assessed using the Mini-Mental State Examination (MMSE). A detailed assessment of the AA of all drugs prescribed was made, and AA was classified according to a standardised scale. Relationships between cognitive decline and AA load and duration of treatment were assessed using bivariate and multivariate statistical analyses. RESULTS: More than 40% used drugs with AA at baseline. During the 8-year follow-up, the cognitive decline was higher in those who had been taking AA drugs (median decline on MMSE 6.5 points) compared with those who had not taken such drugs (median decline 1 point; p=0.025). In linear regression analyses adjusting for age, baseline cognition and depression, significant associations with decline on MMSE were found for total AA load (standardised beta=0.229, p=0.04) as well as the duration of using AA drugs (standardised beta 0.231, p=0.032). CONCLUSION: Our findings suggest that there is an association between anticholinergic drug use and cognitive decline in PD. This may provide an important opportunity for clinicians to avoid increasing progression of cognitive decline by avoiding drugs with AA. Increased awareness by clinicians is required about the classes of drugs that have anticholinergic properties.
Abstract: We identify here for the first time the low-affinity cytochrome P450 (P450) isoforms that metabolize paroxetine, using cDNA-expressed human P450s measuring substrate depletion and paroxetine-catechol (product) formation by liquid chromatography-tandem mass spectrometry. CYP1A2, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 were identified as paroxetine-catechol-forming P450 isoforms, and CYP2C19 and CYP2D6 were identified as metabolizing P450 isoforms by substrate depletion. Michaelis-Menten constants K(m) and V(max) were determined by product formation and substrate depletion. Using selective inhibitory studies and a relative activity factor approach for pooled and single-donor human liver microsomes, we confirmed involvement of the identified P450 isoforms for paroxetine-catechol formation at 1 and 20 muM paroxetine. In addition, we used the population-based simulator Simcyp to estimate the importance of the identified paroxetine-metabolizing P450 isoforms for human metabolism, taking mechanism-based inhibition into account. The amount of active hepatic CYP2D6 and CYP3A4 (not inactivated by mechanism-based inhibition) was also estimated by Simcyp. For extensive and poor metabolizers of CYP2D6, Simcyp-estimated pharmacokinetic profiles were in good agreement with those reported in published in vivo studies. Considering the kinetic parameters, inhibition results, relative activity factor calculations, and Simcyp simulations, CYP2D6 (high affinity) and CYP3A4 (low affinity) are most likely to be the major contributors to paroxetine metabolism in humans. For some individuals CYP1A2 could be of importance for paroxetine metabolism, whereas the importance of CYP2C19 and CYP3A5 is probably limited.
Abstract: Cases of catatonia in patients with renal failure have been rarely reported. In this report, we describe two renal-insufficient patients with catatonia who had a good response to intramuscular lorazepam whereby the catatonic symptoms were relieved. Case 1 involved a patient with end-stage renal disease and severe pneumonia related respiratory failure. He responded well to intramuscular lorazepam (total dose, 4 mg) whereby the catatonia was elieved. Case 2 involved a patient with alcoholic liver cirrhosis and rhabdomyolysis-related acute renal failure. He showed great improvement with intramuscular lorazepam (2 mg) whereby the catatonia was subsequently relieved. This report demonstrates that intramuscular lorazepam is safe, effective and rapid in relieving catatonia associated with renal function impairment. Neither of the patients had a recurrence of catatonia during a period of 6- months follow-up. In conclusion, intramuscular lorazepam may play an important role in the treatment of catatonia associated with renal insufficiency.
Abstract: BACKGROUND/AIMS: The nature and extent of adverse cognitive effects due to the prescription of anticholinergic drugs in older people with and without dementia is unclear. METHODS: We calculated the anticholinergic load (ACL) of medications taken by participants of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing, a cohort of 211 Alzheimer's disease (AD) patients, 133 mild cognitive impairment (MCI) patients and 768 healthy controls (HC) all aged over 60 years. The association between ACL and cognitive function was examined for each diagnostic group (HC, MCI, AD). RESULTS: A high ACL within the HC group was associated with significantly slower response speeds for the Stroop color and incongruent trials. No other significant relationships between ACL and cognition were noted. CONCLUSION: In this large cohort, prescribed anticholinergic drugs appeared to have modest effects upon psychomotor speed and executive function, but not on other areas of cognition in healthy older adults.
Abstract: INTRODUCTION: Many psychotropic drugs can delay cardiac repolarization and thereby prolong the rate-corrected QT interval (QTc). A prolonged QTc often arouses concern in clinical practice, as it can be followed, in rare cases, by the life-threatening polymorphic ventricular tachyarrhythmia called torsade de pointes (TdP). METHOD: We searched PubMed for pertinent literature on the risk of QTc prolongation and/or TdP associated with commonly used psychotropic drugs. RESULTS: Thioridazine and ziprasidone confer the highest risk of QTc prolongation and/or TdP. There is also a clinically significant risk associated with haloperidol given intravenously in high doses. TdP has been reported in a few cases in association with the use of newer antipsychotic drugs (mainly quetiapine and amisulpride), most of the tri- and tetracyclic antidepressants, and the selective monoamine reuptake inhibitors citalopram, fluoxetine, paroxetine, and venlafaxine. As a rule, however, QTc prolongation and/or TdP occur only in the presence of multiple additional risk factors, such as age over 65 years, pre-existing cardiovascular disease, bradycardia, female sex, hypokalemia, hypomagnesemia, a supratherapeutic or toxic serum concentration, or the simultaneous administration of other drugs that delay repolarization or interfere with drug metabolism. CONCLUSION: Before prescribing a psychotropic drug, the physician should carefully assess its risks and benefits to avoid this type of adverse reaction, particularly when additional risk factors are present. The ECG and electrolytes should be regularly monitored in patients taking psychotropic drugs.
Abstract: BACKGROUND: Anticholinergic drugs are often involved in explicit criteria for inappropriate prescribing in older adults. Several scales were developed for screening of anticholinergic drugs and estimation of the anticholinergic burden. However, variation exists in scale development, in the selection of anticholinergic drugs, and the evaluation of their anticholinergic load. This study aims to systematically review existing anticholinergic risk scales, and to develop a uniform list of anticholinergic drugs differentiating for anticholinergic potency. METHODS: We performed a systematic search in MEDLINE. Studies were included if provided (1) a finite list of anticholinergic drugs; (2) a grading score of anticholinergic potency and, (3) a validation in a clinical or experimental setting. We listed anticholinergic drugs for which there was agreement in the different scales. In case of discrepancies between scores we used a reputed reference source (Martindale: The Complete Drug Reference®) to take a final decision about the anticholinergic activity of the drug. RESULTS: We included seven risk scales, and evaluated 225 different drugs. Hundred drugs were listed as having clinically relevant anticholinergic properties (47 high potency and 53 low potency), to be included in screening software for anticholinergic burden. CONCLUSION: Considerable variation exists among anticholinergic risk scales, in terms of selection of specific drugs, as well as of grading of anticholinergic potency. Our selection of 100 drugs with clinically relevant anticholinergic properties needs to be supplemented with validated information on dosing and route of administration for a full estimation of the anticholinergic burden in poly-medicated older adults.
Abstract: OBJECTIVE: To report QT prolongation potential in selective serotonin reuptake inhibitors (SSRIs) in order to advise clinicians on safe use of SSRIs other than citalopram in light of citalopram warnings. DATA SOURCES: Primary literature and case reports were identified through a systematic search. Data from drug manufacturers, package inserts, and the ArizonaCERT database were also utilized. STUDY SELECTION AND DATA EXTRACTION: English-language studies and case reports were included. DATA SYNTHESIS: Studies demonstrate possible dose-related clinically significant QT prolongation with escitalopram. Fluoxetine, fluvoxamine, and sertraline at traditional doses demonstrate a lack of clinically significant increases in QTc in the majority of studies. Further, paroxetine monotherapy shows a lack of clinically significant QTc prolongation in all studies. However, case reports or reporting tools still link these SSRIs with QTc prolongation. Fluoxetine, escitalopram, and sertraline used in post-acute coronary syndrome patients did not demonstrate risk of QTc prolongation. CONCLUSION: For clinicians who choose not to use citalopram due to recent Food and Drug Administration (FDA) recommendations, other antidepressants within this class may be considered. When citalopram is not utilized based on risk factors for TdP, use of escitalopram is not likely the safest alternative. Based on current literature, fluoxetine, fluvoxamine, and sertraline appear to have similar, low risk for QT prolongation, and paroxetine appears to have the lowest risk. However, there are significant limitations in interpreting the studies, including varying definitions of significant QT prolongation. Therefore, choice of an alternative SSRI should be based on individual risk factors for arrhythmias and other patient-specific factors.
Abstract: Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd.
Abstract: Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.
Abstract: The aim of this work was to predict the extent of Cytochrome P450 2D6 (CYP2D6)-mediated drug-drug interactions (DDIs) in different CYP2D6 genotypes using physiologically-based pharmacokinetic (PBPK) modeling. Following the development of a new duloxetine model and optimization of a paroxetine model, the effect of genetic polymorphisms on CYP2D6-mediated intrinsic clearances of dextromethorphan, duloxetine, and paroxetine was estimated from rich pharmacokinetic profiles in activity score (AS)1 and AS2 subjects. We obtained good predictions for the dextromethorphan-duloxetine interaction (Ratio of predicted over observed area under the curve (AUC) ratio (R) 1.38-1.43). Similarly, the effect of genotype was well predicted, with an increase of area under the curve ratio of 28% in AS2 subjects when compared with AS1 (observed, 33%). Despite an approximately twofold underprediction of the dextromethorphan-paroxetine interaction, an Rof 0.71 was obtained for the effect of genotype on the area under the curve ratio. Therefore, PBPK modeling can be successfully used to predict gene-drug-drug interactions (GDDIs). Based on these promising results, a workflow is suggested for the generic evaluation of GDDIs and DDIs that can be applied in other situations.