Predicting Functional Dependency in Patients with Disorders of Consciousness: A TBI-Model Systems and TRACK-TBI Study.

OBJECTIVE: It is not currently possible to predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Our objective was to fit and externally validate a prediction model for 1-year dependency in patients with DoC ≥ 2 weeks after TBI. METHODS: We included adults with TBI enrolled in TBI Model Systems (TBI-MS) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) studies who were not following commands at rehabilitation admission or 2 weeks post-injury, respectively. We fit a logistic regression model in TBI-MS and validated it in TRACK-TBI. The primary outcome was death or dependency at 1 year post-injury, defined using the Disability Rating Scale. RESULTS: In the TBI-MS Discovery Sample, 1,960 participants (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria, and 406 (27%) were dependent 1 year post-injury. In a TBI-MS held out cohort, the dependency prediction model's area under the receiver operating characteristic curve was 0.79 (95% CI 0.74-0.85), positive predictive value was 53% and negative predictive value was 86%. In the TRACK-TBI external validation (n = 124, age 40 [16] years, 77% male, 81% white), the area under the receiver operating characteristic curve was 0.66 (0.53, 0.79), equivalent to the standard IMPACTcore + CT score (p = 0.8). INTERPRETATION: We developed a 1-year dependency prediction model using the largest existing cohort of patients with DoC after TBI. The sensitivity and negative predictive values were greater than specificity and positive predictive values. Accuracy was diminished in an external sample, but equivalent to the IMPACT model. Further research is needed to improve dependency prediction in patients with DoC after TBI. ANN NEUROL 2023;94:1008-1023.

Strategies to improve the experience of patients with brain tumors in the inpatient rehabilitation setting: development of a care coordination checklist.

PURPOSE: To develop a checklist to facilitate coordination of care and communication of patients with brain tumors and assess the benefit of the checklist using a quality improvement survey. MATERIALS AND METHODS: Rehabilitation teams are challenged to respond to the unique needs of patients with brain tumors as this population requires coordinated care across multiple disciplines with frequent communication. To improve care of this patient population in an IRF setting, we developed a novel checklist using a multidisciplinary team of clinicians. Our checklist aims to improve communication between multiple treatment teams, achieve appropriate goals during the IRF stay, involve services as needed and arrange post-discharge services for patients with brain tumors. We then used a quality improvement survey among clinicians to assess the efficacy and general opinion of the checklist. RESULTS: A total of 15 clinicians completed the survey. 66.7% felt that the checklist improved care delivery, and 66.7% felt the checklist improved communication between providers internally and with external institutions. More than half felt the checklist improved the patient experience and care delivery. CONCLUSIONS: A care coordination checklist has the potential to address the unique challenges experienced by patients with brain tumors to improve overall care for this population.IMPLICATIONS FOR REHABILITATIONSuccessful clinical care and rehabilitation of patients with brain tumors requires the coordinated efforts of an interdisciplinary team that often spans multiple care settings.A care coordination checklist has the potential to address the unique challenges experienced by patients with brain tumors to improve overall care for this population in the inpatient rehabilitation setting.

Predicting Functional Dependency in Patients with Disorders of Consciousness: A TBI-Model Systems and TRACK-TBI Study.

Importance: There are currently no models that predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Objective: Fit, test, and externally validate a prediction model for 1-year dependency in patients with DoC 2 or more weeks after TBI. Design: Secondary analysis of patients enrolled in TBI Model Systems (TBI-MS, 1988-2020, Discovery Sample) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI, 2013-2018, Validation Sample) and followed 1-year post-injury. Setting: Multi-center study at USA rehabilitation hospitals (TBI-MS) and acute care hospitals (TRACK-TBI). Participants: Adults with TBI who were not following commands at rehabilitation admission (TBI-MS; days post-injury vary) or 2-weeks post-injury (TRACK-TBI). Exposures: In the TBI-MS database (model fitting and testing), we screened demographic, radiological, clinical variables, and Disability Rating Scale (DRS) item scores for association with the primary outcome. Main Outcome: The primary outcome was death or complete functional dependency at 1-year post-injury, defined using a DRS-based binary measure (DRS Depend ), indicating need for assistance with all activities and concomitant cognitive impairment. Results: In the TBI-MS Discovery Sample, 1,960 subjects (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria and 406 (27%) were dependent at 1-year post-injury. A dependency prediction model had an area under the receiver operating characteristic curve (AUROC) of 0.79 [0.74, 0.85], positive predictive value of 53%, and negative predictive value of 86% for dependency in a held-out TBI-MS Testing cohort. Within the TRACK-TBI external validation sample (N=124, age 40 [16], 77% male, 81% white), a model modified to remove variables not collected in TRACK-TBI, had an AUROC of 0.66 [0.53, 0.79], equivalent to the gold-standard IMPACT core+CT score (0.68; 95% AUROC difference CI: -0.2 to 0.2, p=0.8). Conclusions and Relevance: We used the largest existing cohort of patients with DoC after TBI to develop, test and externally validate a prediction model of 1-year dependency. The model’s sensitivity and negative predictive value were greater than specificity and positive predictive value. Accuracy was diminished in an external sample, but equivalent to the best-available models. Further research is needed to improve dependency prediction in patients with DoC after TBI.

Comparison of Common Outcome Measures for Assessing Independence in Patients Diagnosed with Disorders of Consciousness: A Traumatic Brain Injury Model Systems Study.

Patients with disorders of consciousness (DoC) after traumatic brain injury (TBI) recover to varying degrees of functional dependency. Dependency is difficult to measure but critical for interpreting clinical trial outcomes and prognostic counseling. In participants with DoC (i.e., not following commands) enrolled in the TBI Model Systems National Database (TBIMS NDB), we used the Functional Independence Measure (FIM®) as the reference to evaluate how accurately the Glasgow Outcome Scale-Extended (GOSE) and Disability Rating Scale (DRS) assess dependency. Using the established FIM-dependency cut-point of <80, we measured the classification performance of literature-derived GOSE and DRS cut-points at 1-year post-injury. We compared the area under the receiver operating characteristic curve (AUROC) between the DRSDepend, a DRS-derived marker of dependency, and the data-derived optimal GOSE and DRS cut-points. Of 18,486 TBIMS participants, 1483 met inclusion criteria (mean [standard deviation (SD)] age = 38 [18] years; 76% male). The sensitivity of GOSE cut-points of ≤3 and ≤4 (Lower Severe and Upper Severe Disability, respectively) for identifying FIM-dependency were 97% and 98%, but specificities were 73% and 51%, respectively. The sensitivity of the DRS cut-point of ≥12 (Severe Disability) for identifying FIM-dependency was 60%, but specificity was 100%. The DRSDepend had a sensitivity of 83% and a specificity of 94% for classifying FIM-dependency, with a greater AUROC than the data-derived optimal GOSE (≤3, p = 0.01) and DRS (≥10, p = 0.008) cut-points. Commonly used GOSE and DRS cut-points have limited specificity or sensitivity for identifying functional dependency. The DRSDepend identifies FIM-dependency more accurately than the GOSE and DRS cut-points, but requires further validation.

Association of Traumatic Brain Injury With the Risk of Developing Chronic Cardiovascular, Endocrine, Neurological, and Psychiatric Disorders.

Importance: Increased risk of neurological and psychiatric conditions after traumatic brain injury (TBI) is well-defined. However, cardiovascular and endocrine comorbidity risk after TBI in individuals without these comorbidities and associations with post-TBI mortality have received little attention. Objective: To assess the incidence of cardiovascular, endocrine, neurological, and psychiatric comorbidities in patients with mild TBI (mTBI) or moderate to severe TBI (msTBI) and analyze associations between post-TBI comorbidities and mortality. Design, Setting, and Participants: This prospective longitudinal cohort study used hospital-based patient registry data from a tertiary academic medical center to select patients without any prior clinical comorbidities who experienced TBI from 2000 to 2015. Using the same data registry, individuals without head injuries, the unexposed group, and without target comorbidities were selected and age-, sex-, and race-frequency-matched to TBI subgroups. Patients were followed-up for up to 10 years. Data were analyzed in 2021. Exposures: Mild or moderate to severe head trauma. Main Outcomes and Measures: Cardiovascular, endocrine, neurologic, and psychiatric conditions were defined based on International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10). Associations between TBI and comorbidities, as well as associations between the comorbidities and mortality, were analyzed. Results: A total of 4351 patients with mTBI (median [IQR] age, 45 [29-57] years), 4351 patients with msTBI (median [IQR] age, 47 [30-58] years), and 4351 unexposed individuals (median [IQR] age, 46 [30-58] years) were included in analyses. In each group, 45% of participants were women. mTBI and msTBI were significantly associated with higher risks of cardiovascular, endocrine, neurologic, and psychiatric disorders compared with unexposed individuals. In particular, hypertension risk was increased in both mTBI (HR, 2.5; 95% CI, 2.1-2.9) and msTBI (HR, 2.4; 95% CI, 2.0-2.9) groups. Diabetes risk was increased in both mTBI (HR, 1.9; 95% CI, 1.4-2.7) and msTBI (HR, 1.9; 95% CI, 1.4-2.6) groups, and risk of ischemic stroke or transient ischemic attack was also increased in mTBI (HR, 2.2; 95% CI, 1.4-3.3) and msTBI (HR, 3.6; 95% CI, 2.4-5.3) groups. All comorbidities in the TBI subgroups emerged within a median (IQR) of 3.49 (1.76-5.96) years after injury. Risks for post-TBI comorbidities were also higher in patients aged 18 to 40 years compared with age-matched unexposed individuals: hypertension risk was increased in the mTBI (HR, 5.9; 95% CI, 3.9-9.1) and msTBI (HR, 3.9; 95% CI, 2.5-6.1) groups, while hyperlipidemia (HR, 2.3; 95% CI, 1.5-3.4) and diabetes (HR, 4.6; 95% CI, 2.1-9.9) were increased in the mTBI group. Individuals with msTBI, compared with unexposed patients, had higher risk of mortality (432 deaths [9.9%] vs 250 deaths [5.7%]; P < .001); postinjury hypertension (HR, 1.3; 95% CI, 1.1-1.7), coronary artery disease (HR, 2.2; 95% CI, 1.6-3.0), and adrenal insufficiency (HR, 6.2; 95% CI, 2.8-13.0) were also associated with higher mortality. Conclusions and Relevance: These findings suggest that TBI of any severity was associated with a higher risk of chronic cardiovascular, endocrine, and neurological comorbidities in patients without baseline diagnoses. Medical comorbidities were observed in relatively young patients with TBI. Comorbidities occurring after TBI were associated with higher mortality. These findings suggest the need for a targeted screening program for multisystem diseases after TBI, particularly chronic cardiometabolic diseases.

Predictors of Acute Transfer and Mortality Within 6 Months From Admission to an Inpatient Rehabilitation Facility for Patients With Brain Tumors.

OBJECTIVE: To obtain useful information for clinicians in evaluating patients with brain tumors for transfer to and subsequent care in inpatient rehabilitation facilities (IRFs). DESIGN: Retrospective chart review. SETTING: Inpatient rehabilitation facility. PARTICIPANTS: A total of 208 adults with either initial or recurrent brain tumors who were admitted to an IRF between January 2017 and December 2018 after an acute hospitalization. INTERVENTIONS: None MAIN OUTCOME MEASURES: Transfer from an IRF to an acute care hospital and mortality within 6 months from admission to an IRF. RESULTS: Of the 208 patients who met inclusion criteria, 20.2% were transferred to an acute care hospital during the IRF stay, which was associated with prior chemotherapy, steroid use, and laterality of tumor. In total, 36.9% of patients with brain tumors died within 6 months of an IRF admission that was associated with recurrent tumor diagnosis, prior chemotherapy, prior neurosurgical intervention, prior neurostimulant use, use of steroids, isocitrate dehydrogenase and O6-methyl-guanyl-methyl-transferase biomarkers, and laterality and location of tumor. CONCLUSIONS: Patients with brain tumors have a notable potential for acute hospital transfer and mortality within 6 months of IRF stay, with several tumor- and treatment-related risk factors. This information can help identify functional goals, identify high risk patients, enable closer clinical monitoring, and facilitate focused care discussions at IRFs.

Variation in 30-Day Readmission Rates from Inpatient Rehabilitation Facilities to Acute Care Hospitals.

OBJECTIVES: To quantify the rate of readmission from inpatient rehabilitation facilities (IRFs) to acute care hospitals (ACHs) during the first 30 days of rehabilitation stay. To measure variation in 30-day readmission rate across IRFs, and the extent that patient and facility characteristics contribute to this variation. DESIGN: Retrospective analysis of an administrative database. SETTING AND PARTICIPANTS: Adult IRF discharges from 944 US IRFs captured in the Uniform Data System for Medical Rehabilitation database between October 1, 2015 and December 31, 2017. METHODS: Multilevel logistic regression was used to calculate adjusted rates of readmission within 30 days of IRF admission and examine variation in IRF readmission rates, using patient and facility-level variables as predictors. RESULTS: There were a total of 104,303 ACH readmissions out of a total of 1,102,785 IRFs discharges. The range of 30-day readmission rates to ACHs was 0.0%‒28.9% (mean = 8.7%, standard deviation = 4.4%). The adjusted readmission rate variation narrowed to 2.8%‒17.5% (mean = 8.7%, standard deviation = 1.8%). Twelve patient-level and 3 facility-level factors were significantly associated with 30-day readmission from IRF to ACH. A total of 82.4% of the variance in 30-day readmission rate was attributable to the model predictors. CONCLUSIONS AND IMPLICATIONS: Fifteen patient and facility factors were significantly associated with 30-day readmission from IRF to ACH and explained the majority of readmission variance. Most of these factors are nonmodifiable from the IRF perspective. These findings highlight that adjusting for these factors is important when comparing readmission rates between IRFs.

Weekend Admission to Inpatient Rehabilitation Facilities Is Associated With Transfer to Acute Care in a Nationwide Sample of Patients With Stroke.

OBJECTIVE: The aim of the study was to determine the impact of weekend versus weekday admission to an inpatient rehabilitation facility on the risk of acute care transfer in patients with stroke. DESIGN: This was a retrospective analysis using the Uniform Data System for Medical Rehabilitation, a national database comprising data from 70% of US inpatient rehabilitation facilities. A total of 1,051,436 adult (age ≥18 yrs) stroke cases were identified between 2002 and 2014 that met inclusion criteria. Logistic regression models were developed to test for associations between weekend (Friday-Sunday) versus weekday (Monday-Thursday) inpatient rehabilitation facility admission and transfer to acute care (primary outcome) and inpatient rehabilitation facility length of stay (secondary outcome), adjusting for relevant patient, medical, and facility variables. A secondary analysis examined acute care transfer from 2002 to 2009 before passage of the Affordable Care Act (ACA), 2010 to 2012 post-Affordable Care Act, and 2013 to 2014 after implementation of the Hospital Readmissions Reduction Program. RESULTS: Weekend inpatient rehabilitation facility admission was associated with increased odds of acute care transfer (odds ratio = 1.06, 95% confidence interval = 1.04-1.08) and slightly shorter inpatient rehabilitation facility length of stay (P < 0.001). Overall, the risk of acute care transfer decreased after the ACA and Hospital Readmissions Reduction Program. CONCLUSIONS: Weekend admission to inpatient rehabilitation facility may pose a modest increase in the risk of transfer to acute care in patients with stroke. TO CLAIM CME CREDITS: Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME OBJECTIVES: Upon completion of this article, the reader should be able to: (1) Understand disparities in obesity rates among adolescents with mobility disabilities; (2) Describe limitations of current clinical screening methods of obesity in children with mobility disabilities; and (3) Identify potential alternatives for obesity screening in children with mobility disabilities. LEVEL: Advanced ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Neurologic benefits of sports and exercise.

Traumatic brain injury (TBI) is associated with several pathophysiologic changes, including: neurostructural alterations; molecular changes with shifts in circulating neurotrophins; impaired neural metabolism; changes in cerebrovascular autoregulation, vasoreactivity, and neurovascular coupling; and alterations in functional brain connectivity. In animal models of TBI, aerobic exercise reduces neuronal injury, promotes neuronal survival, and enhances the production of neuroprotective trophic factors. However, the timing of exercise initiation is an important consideration as early exercise in the acute postinjury period may impede recovery mechanisms, although evidence for this in humans is lacking. Though human clinical studies are limited, aerobic exercise post-TBI engages cerebrovascular mechanisms and may impart neurophysiologic benefits to mitigate post-TBI pathophysiologic changes. Additionally, subsymptom threshold exercise in humans has been demonstrated to be safe, feasible, and effective in decreasing symptom burden in individuals with mild TBI, and to counteract the detrimental effects of prolonged inactivity, subsequent physical deconditioning, and its negative emotional sequelae. This chapter will explore the potential role of aerobic exercise in neurorecovery after TBI.

Research Frontiers in Traumatic Brain Injury: Defining the Injury.

With the continued advancement in technology, such as increasingly sophisticated neuroimaging parameters, and the ongoing development of various scientific fields, like serum and blood biomarkers, genetics, and physiology, traumatic brain injury (TBI) research is a dynamic field of study. TBI remains a significant public health concern and research has continued to grow exponentially over the past decade. This review provides an overview of the frontiers of TBI research, from sports concussion to severe TBI, from acute and subacute injury to long-term/chronic outcomes, from assessment and management to prognosis, specifically examining recent neuroimaging, biomarkers, genetics, and physiologic studies.

Functional Status Outperforms Comorbidities as a Predictor of 30-Day Acute Care Readmissions in the Inpatient Rehabilitation Population.

OBJECTIVES: Functional status is associated with patient outcomes, but is rarely included in hospital readmission risk models. The objective of this study was to determine whether functional status is a better predictor of 30-day acute care readmission than traditionally investigated variables including demographics and comorbidities. DESIGN: Retrospective database analysis between 2002 and 2011. SETTING: 1158 US inpatient rehabilitation facilities. PARTICIPANTS: 4,199,002 inpatient rehabilitation facility admissions comprising patients from 16 impairment groups within the Uniform Data System for Medical Rehabilitation database. MEASUREMENTS: Logistic regression models predicting 30-day readmission were developed based on age, gender, comorbidities (Elixhauser comorbidity index, Deyo-Charlson comorbidity index, and Medicare comorbidity tier system), and functional status [Functional Independence Measure (FIM)]. We hypothesized that (1) function-based models would outperform demographic- and comorbidity-based models and (2) the addition of demographic and comorbidity data would not significantly enhance function-based models. For each impairment group, Function Only Models were compared against Demographic-Comorbidity Models and Function Plus Models (Function-Demographic-Comorbidity Models). The primary outcome was 30-day readmission, and the primary measure of model performance was the c-statistic. RESULTS: All-cause 30-day readmission rate from inpatient rehabilitation facilities to acute care hospitals was 9.87%. C-statistics for the Function Only Models were 0.64 to 0.70. For all 16 impairment groups, the Function Only Model demonstrated better c-statistics than the Demographic-Comorbidity Models (c-statistic difference: 0.03-0.12). The best-performing Function Plus Models exhibited negligible improvements in model performance compared to Function Only Models, with c-statistic improvements of only 0.01 to 0.05. CONCLUSION: Readmissions are currently used as a marker of hospital performance, with recent financial penalties to hospitals for excessive readmissions. Function-based readmission models outperform models based only on demographics and comorbidities. Readmission risk models would benefit from the inclusion of functional status as a primary predictor.

Functional Status Outperforms Comorbidities in Predicting Acute Care Readmissions in Medically Complex Patients.

OBJECTIVE: To examine functional status versus medical comorbidities as predictors of acute care readmissions in medically complex patients. DESIGN: Retrospective database study. SETTING: U.S. inpatient rehabilitation facilities. PARTICIPANTS: Subjects included 120,957 patients in the Uniform Data System for Medical Rehabilitation admitted to inpatient rehabilitation facilities under the medically complex impairment group code between 2002 and 2011. INTERVENTIONS: A Basic Model based on gender and functional status was developed using logistic regression to predict the odds of 3-, 7-, and 30-day readmission from inpatient rehabilitation facilities to acute care hospitals. Functional status was measured by the FIM(®) motor score. The Basic Model was compared to six other predictive models-three Basic Plus Models that added a comorbidity measure to the Basic Model and three Gender-Comorbidity Models that included only gender and a comorbidity measure. The three comorbidity measures used were the Elixhauser index, Deyo-Charlson index, and Medicare comorbidity tier system. The c-statistic was the primary measure of model performance. MAIN OUTCOME MEASURES: We investigated 3-, 7-, and 30-day readmission to acute care hospitals from inpatient rehabilitation facilities. RESULTS: Basic Model c-statistics predicting 3-, 7-, and 30-day readmissions were 0.69, 0.64, and 0.65, respectively. The best-performing Basic Plus Model (Basic+Elixhauser) c-statistics were only 0.02 better than the Basic Model, and the best-performing Gender-Comorbidity Model (Gender+Elixhauser) c-statistics were more than 0.07 worse than the Basic Model. CONCLUSIONS: Readmission models based on functional status consistently outperform models based on medical comorbidities. There is opportunity to improve current national readmission risk models to more accurately predict readmissions by incorporating functional data.

A randomized trial of home versus clinic-based sexually transmitted disease screening among men.

BACKGROUND: Preventing sexually transmitted diseases (STD) such as Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) remains a public health challenge. The U.S. Preventive Services Task Force suggests STD screening among men will likely lead to a decrease in infection rates of women. However, innovative approaches are necessary to increase the traditionally low rates of male screening. The purpose of this study is to compare the acceptability and effectiveness of home-based versus clinic-based urine screening for CT and GC in men. METHODS: We conducted a randomized clinical trial of 200 men aged 18 to 45 years who reside in St. Louis, MO. Men were enrolled via telephone and randomly assigned to receive a free urine CT/GC screening kit either in-person at the research clinic or to have it mailed to the participant's preferred address. Participants completed questionnaires at baseline and 10 to 12 weeks postenrollment. The primary outcome was whether STD screening was completed. RESULTS: Sixty percent (120/200) completed STD screening. Men assigned to home-based screening were 60% more likely to complete screening compared with clinic-based screening (72% vs. 48%, RRadj = 1.6, 95% CI = 1.3, 2.00). We identified 4 cases of CT or GC in the home-based group compared with 3 cases of CT in the clinic group. Men who completed screening were significantly more likely to be white, younger, and college educated. CONCLUSIONS: Home-based screening for CT and GC among men is more acceptable than clinic-based screening and resulted in higher rates of screening completion. Incorporating home-based methods as adjuncts to traditional STD screening options shows promise in improving STD screening rates in men.

Baseline correlates of inconsistent and incorrect condom use among sexually active women in the contraceptive CHOICE Project.

BACKGROUND: : To provide protection against sexually transmitted infections and pregnancy, condoms must be used consistently and correctly. However, a significant proportion of couples in the United States fail to do so. Our objective was to determine the demographic and behavioral correlates of inconsistent and incorrect condom use among sexually active, condom-using women. METHODS: : Analysis of baseline data from a prospective cohort of sexually active, condom-using women in the Contraceptive CHOICE Project (n = 2087) using self-reported demographic and behavioral characteristics. Poisson regression was used to determine the relative risk of inconsistent and incorrect condom use after adjusting for variables significant in the univariate analysis. RESULTS: : Inconsistent and incorrect condom use was reported by 41% (n = 847) and 36% (n = 757) of women, respectively. A greater number of unprotected acts was most strongly associated with reporting 10 or more sex acts in the past 30 days, younger age at first intercourse, less perceived partner willingness to use condoms, and lower condom use self-efficacy. Incorrect condom use was associated with reporting 10 or more sex acts in the past 30 days, greater perceived risk for future STIs, and inconsistent condom use. CONCLUSIONS: : Inconsistent and incorrect condom use is common among sexually active women. Targeted educational efforts and prevention strategies should be implemented among women at highest risk for STIs and unintended pregnancies to increase consistent and correct condom use.

Home versus clinic-based specimen collection for Chlamydia trachomatis and Neisseria gonorrhoeae.

Sexually transmitted infections (STIs) are a major public health concern that must be addressed with innovative screening methods to supplement traditional approaches. Home-based screening with self-collected urine or vaginal specimens is a highly feasible and acceptable method, and shows promise in improving STI screening rates in both men and women. Home collection kits have been offered in a variety of settings, with results ranging from very modest improvements in screening rates to 100-fold increases beyond the rates observed with clinic-based screening. This article describes and evaluates the effectiveness and limitations of various home screening strategies used for the detection of STIs.

Screening for sexually transmitted infections at home or in the clinic?

PURPOSE OF REVIEW: The aim is to assess the evidence in support of home-based versus clinic-based screening for sexually transmitted infections. RECENT FINDINGS: Home-based screening for sexually transmitted infections has been shown to be a feasible approach for men and women from a variety of settings, including high-risk, low-income, and resource-poor communities. In recent studies, the testing rate with home-based screening was up to 11 times greater than the testing rate with clinic-based screening. For most individuals, self-collection and testing of urine or vaginal specimens at home was considered to be easy, acceptable, and often preferred over testing at a clinic. There is limited evidence with regard to the cost effectiveness of home-based versus clinic-based screening for sexually transmitted infections. However, a study from the United States concluded that home-based screening is cost saving. SUMMARY: Improvements in screening rates for sexually transmitted infections can be achieved with home-based screening methods. Making low-cost home test kits available may encourage at-risk young individuals with less access to clinic care, who may not otherwise be screened, to self-test for sexually transmitted infections.