Association of Pseudomonas aeruginosa incident infections with adherence to cystic fibrosis foundation care guidelines.

BACKGROUND: Care guidelines for cystic fibrosis (CF) have been developed to enhance consistent care and to improve health outcomes. We determined if adherence to CF care guidelines predicted P. aeruginosa incidence rates (Pa-IR) at U.S. CF centers in 2018. METHODS: This cross-sectional CF Foundation Patient Registry study included 82 adult and 132 pediatric centers. Adherence to 12 guidelines was defined categorically (guideline met) or as a continuous measure (proportion of patients being treated/evaluated per guideline). Association of adherence to individual guidelines with Pa-IR, accounted for center and patient characteristics relevant to Pa-IR and were modeled using random forests and weighted-least-squares (WLS) analyses. RESULTS: The mean Pa-IR was 0.2 cases/patient-years at risk (SE 0.0074) for all centers combined. Guideline adherence was lowest for ≥4 bacterial cultures/year (54% of centers) and annual oral glucose tolerance test (OGTT) (48% of centers), and highest for annual non-tuberculous mycobacteria (NTM) sputum culture (98%). The mean number of guidelines met was 6.7 and higher for pediatric (7.3) than adult (5.6) centers, (p<0.001). The number of guidelines met correlated negatively with Pa-IR (ß=-0.007, p = 0.043). Macrolide prescription and annual OGTT per guideline were associated with lower and higher Pa-IR, respectively. Centers with lower center-wide lung function, higher proportion of pwCF with low body-mass index, and location in the Southwest had higher Pa-IR. CONCLUSION: Overall adherence to guidelines was high except for performing ≥4 bacterial cultures/year and OGTT. Higher Pa-IR was associated with center characteristics and lower guideline adherence. The lower Pa-IR with greater adherence to guidelines suggests that focusing on quality care can positively impact Pa-IR.

Statistically Adjusting for Wear Time in Randomized Trials of Continuous Glucose Monitors as a Complement to Intent-to-Treat and As-Treated Analyses: Application and Evaluation in Two Trials.

Background: Randomized trials of continuous glucose monitoring (CGM) often estimate treatment effects using standard intent-to-treat (ITT) analyses. We explored how adjusting for CGM-measured wear time could complement existing analyses by estimating the effect of receiving and using CGM 100% of the time. Methods: We analyzed data from two 6-month CGM trials spanning diverse ages, the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) and CGM Intervention in Teens and Young Adults with Type 1 Diabetes (CITY) Studies. To adjust the ITT estimates for CGM use, as measured by wear time, we used an instrumental variable (IV) approach with the treatment assignment as an instrument. Outcomes included (1) time in range ([TIR] 70-180 mg/dL), time below range ([TBR] ≤70 mg/dL), and time above range ([TAR] ≥250 mg/dL). We estimated outcomes based on CGM use in the last 28 days of the trial and the full trial. Findings: In the WISDM study, the wear time rates over the 28-day window and full trial period were 93.1% (standard deviation [SD]: 20.4) and 94.5% (SD: 11.9), respectively. In the CITY study, the wear time rates over the 28-day window and full trial period were 82.2% (SD: 26.5) and 83.1% (SD: 21.5), respectively. IV-based estimates for the effect of CGM on TIR, TBR, and TAR suggested greater improvements in glycemic management than the ITT counterparts. The magnitude of the differences was proportional to the level of wear time observed in the trials. Interpretation: In trials of CGM use, the effect of variable wear time is non-negligible. By providing adherence-adjusted estimates, the IV approach may have additional utility for individual clinical decision-making.

Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study.

BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitoring (BGM). We explored heterogeneous treatment effects of CGM on hypoglycemia by formulating a data-driven decision rule that selects an intervention (ie, CGM vs BGM) to minimize percentage of time <70 mg/dL for each individual WISDM participant. METHOD: The precision medicine analyses used data from participants with complete data (n = 194 older adults, including those who received CGM [n = 100] and BGM [n = 94] in the trial). Policy tree and decision list algorithms were fit with 14 baseline demographic, clinical, and laboratory measures. The primary outcome was CGM-measured percentage of time spent in hypoglycemic range (<70 mg/dL), and the decision rule assigned participants to a subgroup reflecting the treatment estimated to minimize this outcome across all follow-up visits. RESULTS: The optimal decision rule was found to be a decision list with 3 steps. The first step moved WISDM participants with baseline time-below range >1.35% and no detectable C-peptide levels to the CGM subgroup (n = 139), and the second step moved WISDM participants with a baseline time-below range of >6.45% to the CGM subgroup (n = 18). The remaining participants (n = 37) were left in the BGM subgroup. Compared with the BGM subgroup (n = 37; 19%), the group for whom CGM minimized hypoglycemia (n = 157; 81%) had more baseline hypoglycemia, a lower proportion of detectable C-peptide, higher glycemic variability, longer disease duration, and higher proportion of insulin pump use. CONCLUSIONS: The decision rule underscores the benefits of CGM for older adults to reduce hypoglycemia. Diagnostic CGM and laboratory markers may inform decision-making surrounding therapeutic CGM and identify older adults for whom CGM may be a critical intervention to reduce hypoglycemia.

Stabilized direct learning for efficient estimation of individualized treatment rules.

In recent years, the field of precision medicine has seen many advancements. Significant focus has been placed on creating algorithms to estimate individualized treatment rules (ITRs), which map from patient covariates to the space of available treatments with the goal of maximizing patient outcome. Direct learning (D-Learning) is a recent one-step method which estimates the ITR by directly modeling the treatment-covariate interaction. However, when the variance of the outcome is heterogeneous with respect to treatment and covariates, D-Learning does not leverage this structure. Stabilized direct learning (SD-Learning), proposed in this paper, utilizes potential heteroscedasticity in the error term through a residual reweighting which models the residual variance via flexible machine learning algorithms such as XGBoost and random forests. We also develop an internal cross-validation scheme which determines the best residual model among competing models. SD-Learning improves the efficiency of D-Learning estimates in binary and multi-arm treatment scenarios. The method is simple to implement and an easy way to improve existing algorithms within the D-Learning family, including original D-Learning, Angle-based D-Learning (AD-Learning), and Robust D-learning (RD-Learning). We provide theoretical properties and justification of the optimality of SD-Learning. Head-to-head performance comparisons with D-Learning methods are provided through simulations, which demonstrate improvement in terms of average prediction error (APE), misclassification rate, and empirical value, along with a data analysis of an acquired immunodeficiency syndrome (AIDS) randomized clinical trial.

Barriers implementing infection prevention and control experienced by healthcare workers, people with CF and parents.

BACKGROUND: Barriers to implementing infection prevention and control (IP&C) practices may be experienced by healthcare workers (HCWs) caring for people with CF (PwCF), PwCF, and their families. We hypothesized that these stakeholders from CF centers with early adoption of the updated 2013 IP&C guideline would experience fewer barriers implementing selected recommendations compared to stakeholders from CF centers with delayed adoption. METHODS: In 2018-2019 we surveyed HCWs and PwCF/parents from 25 CF centers to identify knowledge, attitude, and practice barriers. Each center recruited five HCWs with different occupations. Pediatric centers recruited five parents of children <18 years old and five young adults 18-21 years old. Adult centers recruited 10 adults ≥18 years old. We determined respondents' knowledge scores, the proportion who agreed with or perceived health benefits from recommendations, and reported adherence to recommendations. RESULTS: Knowledge scores, perception of health benefits, and adherence to selected practices were similar among participants from centers with early vs. delayed adoption, yet generally lower for inpatient nurses. IP&C practitioners were less likely to perceive health benefits from PwCF wearing masks and HCWs wearing gowns and gloves. Among HCWs, 57% educated >75% of PwCF/parents about IP&C and 43% advised >75% of PwCF/parents to avoid socializing with other PwCF. Among PwCF/parents, 69%, 53%, and 56% reported discussions with their care teams about performing hand hygiene, avoiding socialization, or the 2013 IP&C guideline, respectively. CONCLUSIONS: Our findings suggest opportunities for targeted education for specific HCW occupations and for PwCF and their families.

Development and validation of multivariable prediction models for adverse COVID-19 outcomes in patients with IBD.

OBJECTIVES: Develop an individualised prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with inflammatory bowel disease (IBD). DESIGN AND SETTING: This study developed and validated prognostic penalised logistic regression models using reports to the international Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease voluntary registry from March to October 2020. Model development was done using a training data set (85% of cases reported 13 March-15 September 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported 16 September-20 October 2020). PARTICIPANTS: We included 2709 cases from 59 countries (mean age 41.2 years (SD 18), 50.2% male). All submitted cases after removing duplicates were included. PRIMARY AND SECONDARY OUTCOME MEASURES: COVID-19 related: (1) Hospitalisation+: composite outcome of hospitalisation, ICU admission, mechanical ventilation or death; (2) Intensive Care Unit+ (ICU+): composite outcome of ICU admission, mechanical ventilation or death; (3) Death. We assessed the resulting models' discrimination using the area under the curve of the receiver operator characteristic curves and reported the corresponding 95% CIs. RESULTS: Of the submitted cases, a total of 633 (24%) were hospitalised, 137 (5%) were admitted to the ICU or intubated and 69 (3%) died. 2009 patients comprised the training set and 700 the test set. The models demonstrated excellent discrimination, with a test set area under the curve (95% CI) of 0.79 (0.75 to 0.83) for Hospitalisation+, 0.88 (0.82 to 0.95) for ICU+ and 0.94 (0.89 to 0.99) for Death. Age, comorbidities, corticosteroid use and male gender were associated with a higher risk of death, while the use of biological therapies was associated with a lower risk. CONCLUSIONS: Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of patients with IBD. A free online risk calculator (https://covidibd.org/covid-19-risk-calculator/) is available for healthcare providers to facilitate discussion of risks due to COVID-19 with patients with IBD.

Development and validation of multivariable prediction models for adverse COVID-19 outcomes in IBD patients.

IMPORTANCE: Risk calculators can facilitate shared medical decision-making 1 . Demographics, comorbidities, medication use, geographic region, and other factors may increase the risk for COVID-19-related complications among patients with IBD 2,3 . OBJECTIVES: Develop an individualized prognostic risk prediction tool for predicting the probability of adverse COVID-19 outcomes in patients with IBD. DESIGN SETTING AND PARTICIPANTS: This study developed and validated prognostic penalized logistic regression models 4 using reports to Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease (SECURE-IBD) from March-October 2020. Model development was done using a training data set (85% of cases reported March 13 - September 15, 2020), and model validation was conducted using a test data set (the remaining 15% of cases plus all cases reported September 16-October 20, 2020). MAIN OUTCOMES AND MEASURES: COVID-19 related:Hospitalization+: composite outcome of hospitalization, ICU admission, mechanical ventilation, or deathICU+: composite outcome of ICU admission, mechanical ventilation, or deathDeathWe assessed the resulting models' discrimination using the area under the curve (AUC) of the receiver-operator characteristic (ROC) curves and reported the corresponding 95% confidence intervals (CIs). RESULTS: We included 2709 cases from 59 countries (mean age 41.2 years [s.d. 18], 50.2% male). A total of 633 (24%) were hospitalized, 137 (5%) were admitted to the ICU or intubated, and 69 (3%) died. 2009 patients comprised the training set and 700 the test set.The models demonstrated excellent discrimination, with a test set AUC (95% CI) of 0.79 (0.75, 0.83) for Hospitalization+, 0.88 (0.82, 0.95) for ICU+, and 0.94 (0.89, 0.99) for Death. Age, comorbidities, corticosteroid use, and male gender were associated with higher risk of death, while use of biologic therapies was associated with a lower risk. CONCLUSIONS AND RELEVANCE: Prognostic models can effectively predict who is at higher risk for COVID-19-related adverse outcomes in a population of IBD patients. A free online risk calculator ( https://covidibd.org/covid-19-risk-calculator/ ) is available for healthcare providers to facilitate discussion of risks due to COVID-19 with IBD patients. The tool numerically and visually summarizes the patient's probabilities of adverse outcomes and associated CIs. Helping physicians identify their highest-risk patients will be important in the coming months as cases rise in the US and worldwide. This tool can also serve as a model for risk stratification in other chronic diseases. KEY POINTS: Question: How well can a multivariable risk model predict the risk of hospitalization, intensive care unit (ICU) stay, or death due to COVID-19 in patients with inflammatory bowel disease (IBD)?Findings: Multivariable prediction models developed using data from an international voluntary registry of IBD patients and available for use online ( https://covidibd.org/ ) have very good discrimination for predicting hospitalization (Test set AUC 0.79) and excellent discrimination for ICU admission (Test set AUC 0.88) and death (Test set AUC 0.94). The models were developed with a training sample of 2009 cases and validated in an independent test sample of 700 cases comprised of a random sub-sample of cases and all cases entered in the registry during a one-month period after model development. Meaning: This risk prediction model may serve as an effective tool for healthcare providers to facilitate conversations about COVID-19-related risks with IBD patients.

Finite element analysis to characterize how varying patellar loading influences pressure applied to cartilage: model evaluation.

A finite element analysis (FEA) modeling technique has been developed to characterize how varying the orientation of the patellar tendon influences the patellofemoral pressure distribution. To evaluate the accuracy of the technique, models were created from MRI images to represent five knees that were previously tested in vitro to determine the influence of hamstrings loading on patellofemoral contact pressures. Hamstrings loading increased the lateral and posterior orientation of the patellar tendon. Each model was loaded at 40°, 60°, and 80° of flexion with quadriceps force vectors representing the experimental loading conditions. The orientation of the patellar tendon was represented for the loaded and unloaded hamstrings conditions based on experimental measures of tibiofemoral alignment. Similar to the experimental data, simulated loading of the hamstrings within the FEA models shifted the center of pressure laterally and increased the maximum lateral pressure. Significant (p < 0.05) differences were identified for the center of pressure and maximum lateral pressure from paired t-tests carried out at the individual flexion angles. The ability to replicate experimental trends indicates that the FEA models can be used for future studies focused on determining how variations in the orientation of the patellar tendon related to anatomical or loading variations or surgical procedures influence the patellofemoral pressure distribution.

Limited benefit of hamstrings forces for the anterior cruciate ligament-deficient knee: an in vitro study.

The hamstrings are considered stabilizers of the anterior cruciate ligament-deficient knee; however, anterior cruciate ligament injury primarily influences tibiofemoral kinematics near full extension, where the hamstrings have the least influence on kinematics. Ten knees were tested at multiple flexion angles in vitro to directly compare the influence of anterior cruciate ligament injury and hamstrings activation on tibiofemoral kinematics. Tibiofemoral kinematics were measured for three testing conditions: (1) anterior cruciate ligament intact, with forces applied through the quadriceps muscles (596 N), (2) anterior cruciate ligament cut, with forces applied through the quadriceps, and (3) anterior cruciate ligament cut, with forces applied through the quadriceps and hamstrings (200 N). Based on repeated measures comparisons performed at each flexion angle, cutting the anterior cruciate ligament significantly (p < 0.05) increased tibial anterior translation, medial translation, and internal rotation at 0 degrees and 15 degrees of flexion by approximately 2.5 mm, 1 mm, and 2 degrees, respectively. Internal rotation also increased significantly at 30 degrees. With the anterior cruciate ligament cut, loading the hamstrings significantly decreased anterior translation, medial translation, and internal rotation at 45 degrees, by approximately 2 mm, 2 mm, and 4 degrees, respectively. Loading the hamstrings caused kinematic changes in the opposite direction of the anterior cruciate ligament injury, but the changes occurred at deeper flexion angles than those at which anterior cruciate ligament injury influenced tibiofemoral kinematics.

All-epiphyseal ACL reconstruction improves tibiofemoral contact: an in vitro study.

BACKGROUND: Anterior cruciate ligament (ACL) injury alters tibiofemoral contact during function, with a posterior shift of the point of contact on the tibia. An all-epiphyseal approach to ACL reconstruction is performed in pediatric patients to improve tibiofemoral contact without disturbing the physis. The hypothesis of the study is that all-epiphyseal ACL reconstruction will shift contact anteriorly on the tibia, as compared with the ACL-deficient knee. METHODS: Ten cadaver knees were tested with the ACL cut and with an all-epiphyseal reconstruction. The knees were set at multiple flexion angles (0, 15, 30, and 45 degrees) and loaded with a quadriceps force of 596 N in combination with an anterior force of 100 N, with the quadriceps loaded in isolation, and with the quadriceps loaded in combination with a hamstrings force of 200 N. Sensors under the menisci characterized the center of force on the tibia. Paired t tests were used to identify significant (P<0.05) differences between the reconstructed and cut conditions for all loading conditions at all flexion angles. RESULTS: On the medial plateau, the average center of force was 2 to 5 mm more anterior for the reconstructed condition than for the ACL cut, with the difference significant for all test conditions. The largest differences between the ACL conditions occurred for the combination of quadriceps forces plus an anterior force. On the lateral plateau, the anterior shift in the center of force from the ACL cut to reconstructed condition was significant for all flexion angles except 0 degree for all loading conditions, with an average difference of approximately 2 mm for all significant differences. CONCLUSIONS: All-epiphyseal ACL reconstruction shifts contact anteriorly on the tibia compared with the injured knee. CLINICAL RELEVANCE: The anterior shift of contact on the femur related to all-epiphyseal ACL reconstruction reduces changes related to ACL injury, which could reduce the risk of cartilage damage and meniscal injuries without violating the growth plate in pediatric patients.