968 resultados para Lost to follow-up


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It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.

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BACKGROUND: The retention of patients in antiretroviral therapy (ART) programmes is an important issue in resource-limited settings. Loss to follow up can be substantial, but it is unclear what the outcomes are in patients who are lost to programmes. METHODS AND FINDINGS: We searched the PubMed, EMBASE, Latin American and Caribbean Health Sciences Literature (LILACS), Indian Medlars Centre (IndMed) and African Index Medicus (AIM) databases and the abstracts of three conferences for studies that traced patients lost to follow up to ascertain their vital status. Main outcomes were the proportion of patients traced, the proportion found to be alive and the proportion that had died. Where available, we also examined the reasons why some patients could not be traced, why patients found to be alive did not return to the clinic, and the causes of death. We combined mortality data from several studies using random-effects meta-analysis. Seventeen studies were eligible. All were from sub-Saharan Africa, except one study from India, and none were conducted in children. A total of 6420 patients (range 44 to 1343 patients) were included. Patients were traced using telephone calls, home visits and through social networks. Overall the vital status of 4021 patients could be ascertained (63%, range across studies: 45% to 86%); 1602 patients had died. The combined mortality was 40% (95% confidence interval 33%-48%), with substantial heterogeneity between studies (P<0.0001). Mortality in African programmes ranged from 12% to 87% of patients lost to follow-up. Mortality was inversely associated with the rate of loss to follow up in the programme: it declined from around 60% to 20% as the percentage of patients lost to the programme increased from 5% to 50%. Among patients not found, telephone numbers and addresses were frequently incorrect or missing. Common reasons for not returning to the clinic were transfer to another programme, financial problems and improving or deteriorating health. Causes of death were available for 47 deaths: 29 (62%) died of an AIDS defining illness. CONCLUSIONS: In ART programmes in resource-limited settings a substantial minority of adults lost to follow up cannot be traced, and among those traced 20% to 60% had died. Our findings have implications both for patient care and the monitoring and evaluation of programmes.

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INTRODUCTION Patients who are lost to follow-up (LTFU) while on antiretroviral therapy (ART) pose challenges to the long-term success of ART programs. We describe the extent to which patients considered LTFU are misclassified as true disengagement from care when they are still alive on ART and explain reasons for ART discontinuation using our active tracing program to further improve ART retention programs and policies. METHODS We identified adult ART patients who missed clinic appointment by more than 3 weeks between January 2006 and December 2010, assuming that such patients would miss their doses of antiretroviral drugs. Patients considered LTFU who consented during ART registration were traced by phone or home visits; true ART status after tracing was documented. Reasons for ART discontinuation were also recorded for those who stopped ART. RESULTS Of the 4,560 suspected LTFU cases, 1,384 (30%) could not be traced. Of the 3,176 successfully traced patients, 952 (30%) were dead and 2,224 (70%) were alive, of which 2,183 (99.5%) started ART according to phone-based self-reports or physical verification during in-person interviews. Of those who started ART, 957 (44%) stopped ART and 1,226 (56%) reported still taking ART at the time of interview by sourcing drugs from another clinic, using alternative ART sources or making brief ART interruptions. Among 940 cases with reasons for ART discontinuations, failure to remember (17%), too weak/sick (12%), travel (46%), and lack of transport to the clinic (16%) were frequently cited; reasons differed by gender. CONCLUSION The LTFU category comprises sizeable proportions of patients still taking ART that may potentially bias retention estimates and misdirect resources at the clinic and national levels if not properly accounted for. Clinics should consider further decentralization efforts, increasing drug allocations for frequent travels, and improving communication on patient transfers between clinics to increase retention and adherence.

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OBJECTIVES: Treatment as prevention depends on retaining HIV-infected patients in care. We investigated the effect on HIV transmission of bringing patients lost to follow up (LTFU) back into care. DESIGN: Mathematical model. METHODS: Stochastic mathematical model of cohorts of 1000 HIV-infected patients on antiretroviral therapy (ART), based on data from two clinics in Lilongwe, Malawi. We calculated cohort viral load (CVL; sum of individual mean viral loads each year) and used a mathematical relationship between viral load and transmission probability to estimate the number of new HIV infections. We simulated four scenarios: 'no LTFU' (all patients stay in care); 'no tracing' (patients LTFU are not traced); 'immediate tracing' (after missed clinic appointment); and, 'delayed tracing' (after six months). RESULTS: About 440 of 1000 patients were LTFU over five years. CVL (million copies/ml per 1000 patients) were 3.7 (95% prediction interval [PrI] 2.9-4.9) for no LTFU, 8.6 (95% PrI 7.3-10.0) for no tracing, 7.7 (95% PrI 6.2-9.1) for immediate, and 8.0 (95% PrI 6.7-9.5) for delayed tracing. Comparing no LTFU with no tracing the number of new infections increased from 33 (95% PrI 29-38) to 54 (95% PrI 47-60) per 1000 patients. Immediate tracing prevented 3.6 (95% PrI -3.3-12.8) and delayed tracing 2.5 (95% PrI -5.8-11.1) new infections per 1000. Immediate tracing was more efficient than delayed tracing: 116 and to 142 tracing efforts, respectively, were needed to prevent one new infection. CONCLUSION: Tracing of patients LTFU enhances the preventive effect of ART, but the number of transmissions prevented is small.

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Evaluation of antiretroviral treatment (ART) programmes in sub-Saharan Africa is difficult because many patients are lost to follow-up. Outcomes in these patients are generally unknown but studies tracing patients have shown mortality to be high. We adjusted programme-level mortality in the first year of antiretroviral treatment (ART) for excess mortality in patients lost to follow-up.

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Background The World Health Organization estimates that in sub-Saharan Africa about 4 million HIV-infected patients had started antiretroviral therapy (ART) by the end of 2008. Loss of patients to follow-up and care is an important problem for treatment programmes in this region. As mortality is high in these patients compared to patients remaining in care, ART programmes with high rates of loss to follow-up may substantially underestimate mortality of all patients starting ART. Methods and Findings We developed a nomogram to correct mortality estimates for loss to follow-up, based on the fact that mortality of all patients starting ART in a treatment programme is a weighted average of mortality among patients lost to follow-up and patients remaining in care. The nomogram gives a correction factor based on the percentage of patients lost to follow-up at a given point in time, and the estimated ratio of mortality between patients lost and not lost to follow-up. The mortality observed among patients retained in care is then multiplied by the correction factor to obtain an estimate of programme-level mortality that takes all deaths into account. A web calculator directly calculates the corrected, programme-level mortality with 95% confidence intervals (CIs). We applied the method to 11 ART programmes in sub-Saharan Africa. Patients retained in care had a mortality at 1 year of 1.4% to 12.0%; loss to follow-up ranged from 2.8% to 28.7%; and the correction factor from 1.2 to 8.0. The absolute difference between uncorrected and corrected mortality at 1 year ranged from 1.6% to 9.8%, and was above 5% in four programmes. The largest difference in mortality was in a programme with 28.7% of patients lost to follow-up at 1 year. Conclusions The amount of bias in mortality estimates can be large in ART programmes with substantial loss to follow-up. Programmes should routinely report mortality among patients retained in care and the proportion of patients lost. A simple nomogram can then be used to estimate mortality among all patients who started ART, for a range of plausible mortality rates among patients lost to follow-up.

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Background Loss to follow-up (LTFU) is common in antiretroviral therapy (ART) programmes. Mortality is a competing risk (CR) for LTFU; however, it is often overlooked in cohort analyses. We examined how the CR of death affected LTFU estimates in Zambia and Switzerland. Methods and Findings HIV-infected patients aged ≥18 years who started ART 2004–2008 in observational cohorts in Zambia and Switzerland were included. We compared standard Kaplan-Meier curves with CR cumulative incidence. We calculated hazard ratios for LTFU across CD4 cell count strata using cause-specific Cox models, or Fine and Gray subdistribution models, adjusting for age, gender, body mass index and clinical stage. 89,339 patients from Zambia and 1,860 patients from Switzerland were included. 12,237 patients (13.7%) in Zambia and 129 patients (6.9%) in Switzerland were LTFU and 8,498 (9.5%) and 29 patients (1.6%), respectively, died. In Zambia, the probability of LTFU was overestimated in Kaplan-Meier curves: estimates at 3.5 years were 29.3% for patients starting ART with CD4 cells <100 cells/µl and 15.4% among patients starting with ≥350 cells/µL. The estimates from CR cumulative incidence were 22.9% and 13.6%, respectively. Little difference was found between naïve and CR analyses in Switzerland since only few patients died. The results from Cox and Fine and Gray models were similar: in Zambia the risk of loss to follow-up and death increased with decreasing CD4 counts at the start of ART, whereas in Switzerland there was a trend in the opposite direction, with patients with higher CD4 cell counts more likely to be lost to follow-up. Conclusions In ART programmes in low-income settings the competing risk of death can substantially bias standard analyses of LTFU. The CD4 cell count and other prognostic factors may be differentially associated with LTFU in low-income and high-income settings.

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OBJECTIVE: To describe the electronic medical databases used in antiretroviral therapy (ART) programmes in lower-income countries and assess the measures such programmes employ to maintain and improve data quality and reduce the loss of patients to follow-up. METHODS: In 15 countries of Africa, South America and Asia, a survey was conducted from December 2006 to February 2007 on the use of electronic medical record systems in ART programmes. Patients enrolled in the sites at the time of the survey but not seen during the previous 12 months were considered lost to follow-up. The quality of the data was assessed by computing the percentage of missing key variables (age, sex, clinical stage of HIV infection, CD4+ lymphocyte count and year of ART initiation). Associations between site characteristics (such as number of staff members dedicated to data management), measures to reduce loss to follow-up (such as the presence of staff dedicated to tracing patients) and data quality and loss to follow-up were analysed using multivariate logit models. FINDINGS: Twenty-one sites that together provided ART to 50 060 patients were included (median number of patients per site: 1000; interquartile range, IQR: 72-19 320). Eighteen sites (86%) used an electronic database for medical record-keeping; 15 (83%) such sites relied on software intended for personal or small business use. The median percentage of missing data for key variables per site was 10.9% (IQR: 2.0-18.9%) and declined with training in data management (odds ratio, OR: 0.58; 95% confidence interval, CI: 0.37-0.90) and weekly hours spent by a clerk on the database per 100 patients on ART (OR: 0.95; 95% CI: 0.90-0.99). About 10 weekly hours per 100 patients on ART were required to reduce missing data for key variables to below 10%. The median percentage of patients lost to follow-up 1 year after starting ART was 8.5% (IQR: 4.2-19.7%). Strategies to reduce loss to follow-up included outreach teams, community-based organizations and checking death registry data. Implementation of all three strategies substantially reduced losses to follow-up (OR: 0.17; 95% CI: 0.15-0.20). CONCLUSION: The quality of the data collected and the retention of patients in ART treatment programmes are unsatisfactory for many sites involved in the scale-up of ART in resource-limited settings, mainly because of insufficient staff trained to manage data and trace patients lost to follow-up.

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BACKGROUND Survival after diagnosis is a fundamental concern in cancer epidemiology. In resource-rich settings, ambient clinical databases, municipal data and cancer registries make survival estimation in real-world populations relatively straightforward. In resource-poor settings, given the deficiencies in a variety of health-related data systems, it is less clear how well we can determine cancer survival from ambient data. METHODS We addressed this issue in sub-Saharan Africa for Kaposi's sarcoma (KS), a cancer for which incidence has exploded with the HIV epidemic but for which survival in the region may be changing with the recent advent of antiretroviral therapy (ART). From 33 primary care HIV Clinics in Kenya, Uganda, Malawi, Nigeria and Cameroon participating in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortia in 2009-2012, we identified 1328 adults with newly diagnosed KS. Patients were evaluated from KS diagnosis until death, transfer to another facility or database closure. RESULTS Nominally, 22% of patients were estimated to be dead by 2 years, but this estimate was clouded by 45% cumulative lost to follow-up with unknown vital status by 2 years. After adjustment for site and CD4 count, age <30 years and male sex were independently associated with becoming lost. CONCLUSIONS In this community-based sample of patients diagnosed with KS in sub-Saharan Africa, almost half became lost to follow-up by 2 years. This precluded accurate estimation of survival. Until we either generally strengthen data systems or implement cancer-specific enhancements (e.g., tracking of the lost) in the region, insights from cancer epidemiology will be limited.

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The purpose of this study was to evaluate the results of an anatomic open stabilization procedure. Twenty-three consecutive patients with traumatic, recurrent, anterior glenohumeral instability were managed with a modified open procedure. All had a Bankart lesion. A standardized, true anatomic capsulolabral reconstruction was performed with suture anchors. Two patients were lost to follow-up, and twenty-one were evaluated after 36 months [range, 24-49 months] by an independent observer. Shoulder stability and function were the principal outcome measures. None of the patients had subsequent dislocations. All returned to full working capacity, and 19 reached their previous level of sport activities. The mean loss in active abduction and flexion was 1 degrees, in internal rotation, one vertebral level, and in external rotation, 7 degrees (arm at 90 degrees of abduction). Two patients had a positive anterior apprehension test. No sign of shoulder osteoarthritis was observed. The open anatomic capsulolabral reconstruction provides excellent results and allows the restoration of stability with good function.

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Loss to follow-up (LTFU) is a common problem in many epidemiological studies. In antiretroviral treatment (ART) programs for patients with human immunodeficiency virus (HIV), mortality estimates can be biased if the LTFU mechanism is non-ignorable, that is, mortality differs between lost and retained patients. In this setting, routine procedures for handling missing data may lead to biased estimates. To appropriately deal with non-ignorable LTFU, explicit modeling of the missing data mechanism is needed. This can be based on additional outcome ascertainment for a sample of patients LTFU, for example, through linkage to national registries or through survey-based methods. In this paper, we demonstrate how this additional information can be used to construct estimators based on inverse probability weights (IPW) or multiple imputation. We use simulations to contrast the performance of the proposed estimators with methods widely used in HIV cohort research for dealing with missing data. The practical implications of our approach are illustrated using South African ART data, which are partially linkable to South African national vital registration data. Our results demonstrate that while IPWs and proper imputation procedures can be easily constructed from additional outcome ascertainment to obtain valid overall estimates, neglecting non-ignorable LTFU can result in substantial bias. We believe the proposed estimators are readily applicable to a growing number of studies where LTFU is appreciable, but additional outcome data are available through linkage or surveys of patients LTFU. Copyright © 2013 John Wiley & Sons, Ltd.

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PURPOSE: The dura mater bioprosthesis was developed in the Department of Cardiopneumology of the Hospital das Clínicas of the University of São Paulo Medical School in 1971. Here, we present the clinical results of the dura mater bioprosthesis over 30 years of follow-up. METHODS: We studied 70 consecutive patients who underwent mitral or tricuspid valve replacement with a dura mater bioprosthesis between January 1971 and August 1972. RESULTS: The early mortality was 10% (7 patients). The follow-up was 87% complete (9 patients were lost to follow-up). Two patients were alive and asymptomatic 30 years after valve replacement; 33 patients underwent reoperations due to valve dysfunction, and 19 died during the follow-up period. At 30 years, the actuarial survival was 49.2 ± 8.6%; freedom from rupture, 27.0 ± 10.2%; freedom from calcification, 78.8 ± 8.6%; and freedom from reoperation, 18.8 ± 7.5%. CONCLUSIONS: The dura mater bioprosthesis played an important role in the treatment of patients with mitral and tricuspid valve disease. The low rate of thromboembolism and the long period of follow-up without evidence of valve dysfunction, which occurred for several of our patients, are important characteristics of these bioprosthesis.

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Vitamin B12 and iron deficiencies are common problems in consultations of general internal medicine. They cause different symptoms that can be non-specific. This article makes it possible, from a clinical frame of reference, to answer the following questions: What value of vitamin B12 should we consider a "deficiency", and what is the role of methylmalonate? What is the role of vitamin B12 oral supplements? How should we interpret values of ferritine? How should iron deficiency be investigated? What is the place of intravenous iron administration?

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INTRODUCTION: HIV-infected pregnant women are very likely to engage in HIV medical care to prevent transmission of HIV to their newborn. After delivery, however, childcare and competing commitments might lead to disengagement from HIV care. The aim of this study was to quantify loss to follow-up (LTFU) from HIV care after delivery and to identify risk factors for LTFU. METHODS: We used data on 719 pregnancies within the Swiss HIV Cohort Study from 1996 to 2012 and with information on follow-up visits available. Two LTFU events were defined: no clinical visit for >180 days and no visit for >360 days in the year after delivery. Logistic regression analysis was used to identify risk factors for a LTFU event after delivery. RESULTS: Median maternal age at delivery was 32 years (IQR 28-36), 357 (49%) women were black, 280 (39%) white, 56 (8%) Asian and 4% other ethnicities. One hundred and seven (15%) women reported any history of IDU. The majority (524, 73%) of women received their HIV diagnosis before pregnancy, most of those (413, 79%) had lived with diagnosed HIV longer than three years and two-thirds (342, 65%) were already on antiretroviral therapy (ART) at time of conception. Of the 181 women diagnosed during pregnancy by a screening test, 80 (44%) were diagnosed in the first trimester, 67 (37%) in the second and 34 (19%) in the third trimester. Of 357 (69%) women who had been seen in HIV medical care during three months before conception, 93% achieved an undetectable HIV viral load (VL) at delivery. Of 62 (12%) women with the last medical visit more than six months before conception, only 72% achieved an undetectable VL (p=0.001). Overall, 247 (34%) women were LTFU over 180 days in the year after delivery and 86 (12%) women were LTFU over 360 days with 43 (50%) of those women returning. Being LTFU for 180 days was significantly associated with history of intravenous drug use (aOR 1.73, 95% CI 1.09-2.77, p=0.021) and not achieving an undetectable VL at delivery (aOR 1.79, 95% CI 1.03-3.11, p=0.040) after adjusting for maternal age, ethnicity, time of HIV diagnosis and being on ART at conception. CONCLUSIONS: Women with a history of IDU and women with a detectable VL at delivery were more likely to be LTFU after delivery. This is of concern regarding their own health, as well as risk for sexual partners and subsequent pregnancies. Further strategies should be developed to enhance retention in medical care beyond pregnancy.

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Objective: Improved treatment has increased the survival of childhood cancer patients in recent decades, but follow-up care is recommended to detect and treat late effects. We investigated relationships between health beliefs and follow-up attendance in adult childhood cancer survivors.Methods: Childhood cancer survivors aged younger than 16 years when diagnosed between 1976 and 2003, who had survived for more than 5 years and were currently aged 20+ years, received a postal questionnaire. We asked survivors whether they attended follow-up in the past year. Concepts from the Health Belief Model (perceived susceptibility and severity of future late effects, potential benefits and barriers to follow-up, general health value and cues to action) were assessed. Medical information was extracted from the Swiss Childhood Cancer Registry.Results: Of 1075 survivors (response rate 72.3%), 250 (23.3%) still attended regular follow-up care. In unadjusted analyses, all health belief concepts were significantly associated with follow-up (p < 0.05). Adjusting for other health beliefs, demographic, and medical variables, only barriers (OR = 0.59; 95% CI: 0.43-0.82) remained significant. Younger survivors, those with lower educational background, diagnosed at an older age, treated with chemotherapy, radiotherapy, or bone marrow transplantation and with a relapse were more likely to attend follow-up care.Conclusions: Our study showed that more survivors at high risk of cancer-and treatment-related late effects attend follow-up care in Switzerland. Patient-perceived barriers hinder attendance even after accounting for medical variables. Information about the potential effectiveness and value of follow-up needs to be available to increase the attendance among childhood cancer survivors. Copyright (C) 2010 John Wiley & Sons, Ltd.