Latent tuberculosis infection treatment completion in Biscay: differences between regimens and monitoring approaches.

Introduction: Contact tracing and treatment of latent tuberculosis infection (LTBI) is a key element of tuberculosis (TB) control in low TB incidence countries. A TB control and prevention program has been active in the Basque Country since 2003, including the development of the nurse case manager role and a unified electronic record. Three World Health Organization-approved LTBI regimens have been used: isoniazid for 6 months (6H), rifampicin for 4 months (4R), and isoniazid and rifampicin for 3 months (3HR). Centralized follow-up by a TB nurse case manager started in January 2016, with regular telephone follow-up, telemonitoring of blood test results, and monitoring of adherence by electronic review of drugs dispensed in pharmacies. Objective: To estimate LTBI treatment completion and toxicity of different preventive treatment regimens in a real-world setting. Secondary objective: to investigate the adherence to different approaches to preventive treatment monitoring. Methods: A multicentre retrospective cohort study was conducted using data collected prospectively on contacts of patients with TB in five hospitals in Biscay from 2003 to 2022. Results: A total of 3,066 contacts with LTBI were included. The overall completion rate was 66.8%; 86.5% of patients on 3HR (n = 699) completed treatment vs. 68.3% (n = 1,260) of those on 6H (p < 0.0001). The rate of toxicity was 3.8%, without significant differences between the regimens. A total of 394 contacts were monitored by a TB nurse case manager. In these patients, the completion rate was 85% vs. 67% in those under standard care (p < 0.001). A multivariate logistic regression model identified three independent factors associated with treatment completion: being female, the 3HR regimen, and nurse telemonitoring. Conclusion: 3HR was well tolerated and associated with a higher rate of treatment completion. Patients with nurse telemonitoring follow-up had better completion rates.

[Evaluation of a computer predictive model to stratify risk and site of care in community acquired pneumonia]. / Utilidad de un modelo informatizado para estratificación de riesgo y decisión de lugar de tratamiento en la neumonía de la comunidad.

BACKGROUND: CAP is a common disorder with a great variability in clinical practice. The decision regarding the appropriate site of care is the most important for the level of treatment and costs. Recently a hospital in our region ( Hospital de Galdakao) developed a prediction rule based on the Pneumonia Severity Index (PSI) plus some additional criteria (hypoxemia <60, shock, previous correct treatment failure, social problems or inability to maintain oral intake, pleural effusion or unstable comorbidities) with an easy computer program to classify patients to be hospitalized or not. OBJECTIVE: Evaluate that computer program in the emergency department of our hospital. RESULTS: We included between December 02 and December 04,662 prospective patients with CAP admitted to our emergency department, 58 had a different final diagnosis. 285 (47%) were treated on outpatient basis. Readmission rate was 6%. There was no mortality in this group. 319 (53%) patients were hospitalized, 97 were PSI low risk patients (I-II), 61 of them were admitted to hospital because additional criteria. 45% of these "low risk patients" had significant complications. These results are similar to those obtained in Galdakao* CONCLUSIONS: The application of this computer risk stratifying program to assess admission to hospital in CAP is simple useful, secure and can be export to different settings. Additional criteria to PSI are necessary to detect low risk patients that complicate.

Utilidad de un modelo informatizado para estratificación de riesgo y decisión de lugar de tratamiento en la neumonía de la comunidad / Evaluation of a computer predictive model to stratify risk and site of care in community acquired pneumonia

Introducción: La neumonía adquirida en la comunidad (NAC) es una patología muy común y con una gran variabilidad en la práctica clínica. La decisión de hospitalizar o no a un paciente es la más importante en cuanto al nivel de tratamiento y costes. Recientemente un hospital de nuestra comunidad (Hospital de Galdakao) ha desarrollado una regla predictiva basada en el Pneumonia Severity Index (PSI), modificado por varios criterios adicionales (hipoxemia < 60, shock, fracaso de tratamiento previo correcto, problemas sociales o incapacidad para la ingesta oral, derrame pleural o comorbilidad inestable) mediante un sencillo programa informático para ayudar en la decisión de ingresar o no a un paciente. Objetivos: Evaluar la utilidad de ese programa informático en el servicio de urgencias de nuestro hospital. Resultados: Incluimos de forma prospectiva 662 pacientes con NAC que acudieron a urgencias del Hospital de Txagorritxu, entre Diciembre 2002 y Diciembre 2004. De ellos 58 tuvieron un diagnóstico final diferente. El 47% (285) fueron tratados de forma ambulatoria. La tasa de reingresos en este grupo fue del 6% y no hubo ningún éxitus. Fueron hospitalizados 319 pacientes, de ellos 97 pertenecían a clases de riesgo bajo del PSI, 61 de los cuales ingresaron por los criterios adicionales elegidos por nosotros, sufriendo el 45% de ellos complicaciones significativas. Estos resultados son similares a los obtenidos en el estudio del hospital de Galdakao. Conclusiones: La aplicación de este programa informático para estratificar riesgo y ayudar a la decisión de ingreso en la NAC es simple, útil, seguro y puede ser exportado a diferentes ámbitos clínicos. Son necesarios criterios adicionales al PSI para detectar los pacientes de bajo riesgo que tienen alguna complicación

Background: CAP is a common disorder with a great variability in clinical practice. The decision regarding the appropriate site of care is the most important for the level of treatment and costs. Recently a hospital in our region ( Hospital de Galdakao) developed a prediction rule based on the Pneumonia Severity Index (PSI) plus some additional criteria (hypoxemia <60, shock, previous correct treatment failure, social problems or inability to maintain oral intake, pleural effusion or unstable comorbidities) with an easy computer program to classify patients to be hospitalized or not. Objective: Evaluate that computer program in the emergency department of our hospital. Results: We included between December 02 and December 04 662 prospective patients with CAP admitted to our emergency department, 58 had a different final diagnosis. 285 (47%) were treated on outpatient basis. Readmission rate was 6%. There was no mortality in this group. 319 (53%) patients were hospitalized, 97 were PSI low risk patients (I-II), 61 of them were admitted to hospital because additional criteria. 45% of these “low risk patients” had significant complications. These results are similar to those obtained in Galdakao* Conclusions: The application of this computer risk stratifying program to assess admission to hospital in CAP is simple useful, secure and can be export to different settings. Additional criteria to PSI are necessary to detect low risk patients that complicate

[Blood levels of eosinophil cationic protein in patients with allergic rhinitis. Evolution after treatment with corticoids]. / Niveles séricos de proteína catiónica del eosinófilo en pacientes con rinitis alérgica. Evolución tras tratamiento con corticoides.

We analyze changes in eosinophilic cationic protein (ECP) serum levels after treatment with intranasal corticoids. Fifty-three healthy individuals (control group) and 21 patients diagnosed of allergic rhinitis, with or without bronchial asthma, were enrolled at a time when they had only nasal symptoms. Data were collected from skin Prick tests, forced spirometry, methacholine challenge, and complete blood workups, including IgE measurement, eosinophil counts and ECP serum levels determined by immunofluorescence. The patients received intranasal budesonide at a dose of 200 micrograms/24 h. ECP levels and eosinophil counts were determined before (baseline levels) and during treatment (on days 21 and 60). We found significant differences (p < 0.01) in baseline ECP levels of the controls (9.34 +/- 5.76) and patients (16.47 +/- 15.28). These values were significantly lower than baseline 21 and 60 days after treatment, although the changes between days 21 and 60 were not significant. Eosinophil counts did not fall significantly. We also found that eosinophil counts and ECP levels were correlated (r = 0.53) at baseline but not after treatment (r = 0.25). No patient experienced bronchial symptoms during the study. We conclude that ECP serum levels in patients with symptoms of rhinitis are significantly higher than levels in non symptomatic individuals. These levels fall significantly, possibly due to intranasal corticoid treatment, although eosinophil counts remain constant. ECP levels can therefore be used to monitor inflammatory activity in patients with allergic rhinitis.