Exploring fathers' experiences of caring for a child with complex care needs through ethnography and arts-based methodologies.

BACKGROUND: Although the number of children living with complex care needs (CCN) is increasing worldwide, there is limited data on the experience of fathers caring for children with CCN. This paper reports on findings specific to fathers' experiences of caring for their child with CCN and highlights recommendations provided for parents of children with CCN, service providers, and policymakers. The findings emerged from a larger study designed to examine how Canadian families of children with CCN participate in society. METHODS: We used the qualitative research approach of ethnography and arts-based methodologies (ecomaps and photovoice) as well as purposive and snowball sampling techniques. Four parents were engaged as advisors and twenty-nine fathers participated in interviews (all were married or in a relationship; age range of 28 to 55 years). In line with an ethnographic approach, data analysis involved several iterative steps including comparing data from the first, second, and third set of interviews and refining themes. RESULTS: One overarching theme, striving to be there for the child with CCN, was identified. Five supporting themes further exemplified how fathers strived to be there for their child: 1) contributing to the parental team through various roles; 2) building accessibility through adaptation; 3) engaging in activities with the child; 4) expressing admiration and pride in their children; and 5) meaning making. Recommendations for parents included making and nurturing connections and asking for help while recommendations for healthcare and social service providers included communicating authentically with families and listening to parents. Fathers also indicated that leadership and funding for programs of families of children with CCN should be priorities for policymakers. CONCLUSIONS: In addition to documenting fathers' active involvement in their child's care and development, our findings provide new insights into how fathers make participation in everyday life accessible and inclusive for their children. Study findings also point to 1) priority areas for policymakers (e.g., accessible physical environments); 2) factors that are critical for fostering collaborative care teams with fathers; and 3) the need for complex care teams in the adult health care system. Implications for those providing psychosocial support for these families are noted as well as knowledge gaps worthy of future exploration such as the role of diversity or intersectionality in fathering children with CCN.

Automated Segmentation of Kidney Cortex and Medulla in CT Images: A Multisite Evaluation Study.

BACKGROUND: In kidney transplantation, a contrast CT scan is obtained in the donor candidate to detect subclinical pathology in the kidney. Recent work from the Aging Kidney Anatomy study has characterized kidney, cortex, and medulla volumes using a manual image-processing tool. However, this technique is time consuming and impractical for clinical care, and thus, these measurements are not obtained during donor evaluations. This study proposes a fully automated segmentation approach for measuring kidney, cortex, and medulla volumes. METHODS: A total of 1930 contrast-enhanced CT exams with reference standard manual segmentations from one institution were used to develop the algorithm. A convolutional neural network model was trained (n=1238) and validated (n=306), and then evaluated in a hold-out test set of reference standard segmentations (n=386). After the initial evaluation, the algorithm was further tested on datasets originating from two external sites (n=1226). RESULTS: The automated model was found to perform on par with manual segmentation, with errors similar to interobserver variability with manual segmentation. Compared with the reference standard, the automated approach achieved a Dice similarity metric of 0.94 (right cortex), 0.90 (right medulla), 0.94 (left cortex), and 0.90 (left medulla) in the test set. Similar performance was observed when the algorithm was applied on the two external datasets. CONCLUSIONS: A fully automated approach for measuring cortex and medullary volumes in CT images of the kidneys has been established. This method may prove useful for a wide range of clinical applications.

Automated total kidney volume measurements in pre-clinical magnetic resonance imaging for resourcing imaging data, annotations, and source code.

The objective of this study was to validate a fully automated total kidney volume measurement method for pre-clinical rodent trials that is fast, accurate, reproducible, and to provide these resources to the research community. Rodent studies that involve imaging are crucial for monitoring treatment efficacy in diseases such as polycystic kidney disease. Previous studies utilize manual or semi-automated segmentations, which are time consuming and potentially biased. To develop our automated system, a total of 150 axial magnetic resonance images (MRI) from a variety of mouse models were manually segmented and used to train/validate an automated algorithm. To test the longitudinal application of the model, four mutant and four wild-type mice were imaged sequentially over three to twelve weeks via MRI. Segmentations of the kidneys (excluding the renal pelvis) were generated by the automated method and two different readers, with one reader repeating the measurements. Similarity metrics and longitudinal analysis were calculated to assess the performance of the automated compared to the manual methods. The automated approach required no user input, besides a final visual quality control step. Similarity metrics of the automated method versus the manual segmentations were on par with inter- and intra-reader comparisons. Thus, our fully automated approach described here can be safely used in longitudinal, pre-clinical trials that involve the segmentation of rodent kidneys in T2-weighted MRIs.

Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning.

Total kidney volume (TKV) is the main imaging biomarker used to monitor disease progression and to classify patients affected by autosomal dominant polycystic kidney disease (ADPKD) for clinical trials. However, patients with similar TKVs may have drastically different cystic presentations and phenotypes. In an effort to quantify these cystic differences, we developed the first 3D semantic instance cyst segmentation algorithm for kidneys in MR images. We have reformulated both the object detection/localization task and the instance-based segmentation task into a semantic segmentation task. This allowed us to solve this unique imaging problem efficiently, even for patients with thousands of cysts. To do this, a convolutional neural network (CNN) was trained to learn cyst edges and cyst cores. Images were converted from instance cyst segmentations to semantic edge-core segmentations by applying a 3D erosion morphology operator to up-sampled versions of the images. The reduced cysts were labeled as core; the eroded areas were dilated in 2D and labeled as edge. The network was trained on 30 MR images and validated on 10 MR images using a fourfold cross-validation procedure. The final ensemble model was tested on 20 MR images not seen during the initial training/validation. The results from the test set were compared to segmentations from two readers. The presented model achieved an averaged R2 value of 0.94 for cyst count, 1.00 for total cyst volume, 0.94 for cystic index, and an averaged Dice coefficient of 0.85. These results demonstrate the feasibility of performing cyst segmentations automatically in ADPKD patients.

Detection and characterization of mosaicism in autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited, progressive nephropathy accounting for 4-10% of end stage renal disease worldwide. PKD1 and PKD2 are the most common disease loci, but even accounting for other genetic causes, about 7% of families remain unresolved. Typically, these unsolved cases have relatively mild kidney disease and often have a negative family history. Mosaicism, due to de novo mutation in the early embryo, has rarely been identified by conventional genetic analysis of ADPKD families. Here we screened for mosaicism by employing two next generation sequencing screens, specific analysis of PKD1 and PKD2 employing long-range polymerase chain reaction, or targeted capture of cystogenes. We characterized mosaicism in 20 ADPKD families; the pathogenic variant was transmitted to the next generation in five families and sporadic in 15. The mosaic pathogenic variant was newly discovered by next generation sequencing in 13 families, and these methods precisely quantified the level of mosaicism in all. All of the mosaic cases had PKD1 mutations, 14 were deletions or insertions, and 16 occurred in females. Analysis of kidney size and function showed the mosaic cases had milder disease than a control PKD1 population, but only a few had clearly asymmetric disease. Thus, in a typical ADPKD population, readily detectable mosaicism by next generation sequencing accounts for about 1% of cases, and about 10% of genetically unresolved cases with an uncertain family history. Hence, identification of mosaicism is important to fully characterize ADPKD populations and provides informed prognostic information.

Automatic Measurement of Kidney and Liver Volumes from MR Images of Patients Affected by Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: The formation and growth of cysts in kidneys, and often liver, in autosomal dominant polycystic kidney disease (ADPKD) cause progressive increases in total kidney volume (TKV) and liver volume (TLV). Laborious and time-consuming manual tracing of kidneys and liver is the current gold standard. We developed a fully automated segmentation method for TKV and TLV measurement that uses a deep learning network optimized to perform semantic segmentation of kidneys and liver. METHODS: We used 80% of a set of 440 abdominal magnetic resonance images (T2-weighted HASTE coronal sequences) from patients with ADPKD to train the network and the remaining 20% for validation. Both kidneys and liver were also segmented manually. To evaluate the method's performance, we used an additional test set of images from 100 patients, 45 of whom were also involved in longitudinal analyses. RESULTS: TKV and TLV measured by the automated approach correlated highly with manually traced TKV and TLV (intraclass correlation coefficients, 0.998 and 0.996, respectively), with low bias and high precision (<0.1%±2.7% for TKV and -1.6%±3.1% for TLV); this was comparable with inter-reader variability of manual tracing (<0.1%±3.5% for TKV and -1.5%±4.8% for TLV). For longitudinal analysis, bias and precision were <0.1%±3.2% for TKV and 1.4%±2.9% for TLV growth. CONCLUSIONS: These findings demonstrate a fully automated segmentation method that measures TKV, TLV, and changes in these parameters as accurately as manual tracing. This technique may facilitate future studies in which automated and reproducible TKV and TLV measurements are needed to assess disease severity, disease progression, and treatment response.

Mutations in GANAB, Encoding the Glucosidase IIα Subunit, Cause Autosomal-Dominant Polycystic Kidney and Liver Disease.

Autosomal-dominant polycystic kidney disease (ADPKD) is a common, progressive, adult-onset disease that is an important cause of end-stage renal disease (ESRD), which requires transplantation or dialysis. Mutations in PKD1 or PKD2 (∼85% and ∼15% of resolved cases, respectively) are the known causes of ADPKD. Extrarenal manifestations include an increased level of intracranial aneurysms and polycystic liver disease (PLD), which can be severe and associated with significant morbidity. Autosomal-dominant PLD (ADPLD) with no or very few renal cysts is a separate disorder caused by PRKCSH, SEC63, or LRP5 mutations. After screening, 7%-10% of ADPKD-affected and ∼50% of ADPLD-affected families were genetically unresolved (GUR), suggesting further genetic heterogeneity of both disorders. Whole-exome sequencing of six GUR ADPKD-affected families identified one with a missense mutation in GANAB, encoding glucosidase II subunit α (GIIα). Because PRKCSH encodes GIIß, GANAB is a strong ADPKD and ADPLD candidate gene. Sanger screening of 321 additional GUR families identified eight further likely mutations (six truncating), and a total of 20 affected individuals were identified in seven ADPKD- and two ADPLD-affected families. The phenotype was mild PKD and variable, including severe, PLD. Analysis of GANAB-null cells showed an absolute requirement of GIIα for maturation and surface and ciliary localization of the ADPKD proteins (PC1 and PC2), and reduced mature PC1 was seen in GANAB(+/-) cells. PC1 surface localization in GANAB(-/-) cells was rescued by wild-type, but not mutant, GIIα. Overall, we show that GANAB mutations cause ADPKD and ADPLD and that the cystogenesis is most likely driven by defects in PC1 maturation.

Kidney and cystic volume imaging for disease presentation and progression in the cat autosomal dominant polycystic kidney disease large animal model.

BACKGROUND: Approximately 30% of Persian cats have a c.10063C > A variant in polycystin 1 (PKD1) homolog causing autosomal dominant polycystic kidney disease (ADPKD). The variant is lethal in utero when in the homozygous state and is the only ADPKD variant known in cats. Affected cats have a wide range of progression and disease severity. However, cats are an overlooked biomedical model and have not been used to test therapeutics and diets that may support human clinical trials. To reinvigorate the cat as a large animal model for ADPKD, the efficacy of imaging modalities was evaluated and estimates of kidney and fractional cystic volumes (FCV) determined. METHODS: Three imaging modalities, ultrasonography, computed tomography (CT), and magnetic resonance imaging examined variation in disease presentation and disease progression in 11 felines with ADPKD. Imaging data was compared to well-known biomarkers for chronic kidney disease and glomerular filtration rate. Total kidney volume, total cystic volume, and FCV were determined for the first time in ADPKD cats. Two cats had follow-up examinations to evaluate progression. RESULTS: FCV measurements were feasible in cats. CT was a rapid and an efficient modality for evaluating therapeutic effects that cause alterations in kidney volume and/or FCV. Biomarkers, including glomerular filtration rate and creatinine, were not predictive for disease progression in feline ADPKD. The wide variation in cystic presentation suggested genetic modifiers likely influence disease progression in cats. All imaging modalities had comparable resolutions to those acquired for humans, and software used for kidney and cystic volume estimates in humans proved useful for cats. CONCLUSIONS: Routine imaging protocols used in veterinary medicine are as robust and efficient for evaluating ADPKD in cats as those used in human medicine. Cats can be identified as fast and slow progressors, thus, could assist with genetic modifier discovery. Software to measure kidney and cystic volume in human ADPKD kidney studies is applicable and efficient in cats. The longer life and larger kidney size span than rodents, similar genetics, disease presentation and progression as humans suggest cats are an efficient biomedical model for evaluation of ADPKD therapeutics.

Image texture features predict renal function decline in patients with autosomal dominant polycystic kidney disease.

Magnetic resonance imaging (MRI) examinations provide high-resolution information about the anatomic structure of the kidneys and are used to measure total kidney volume (TKV) in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD). Height-adjusted TKV (HtTKV) has become the gold-standard imaging biomarker for ADPKD progression at early stages of the disease when estimated glomerular filtration rate (eGFR) is still normal. However, HtTKV does not take advantage of the wealth of information provided by MRI. Here we tested whether image texture features provide additional insights into the ADPKD kidney that may be used as complementary information to existing biomarkers. A retrospective cohort of 122 patients from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study was identified who had T2-weighted MRIs and eGFR values over 70 mL/min/1.73m2 at the time of their baseline scan. We computed nine distinct image texture features for each patient. The ability of each feature to predict subsequent progression to CKD stage 3A, 3B, and 30% reduction in eGFR at eight-year follow-up was assessed. A multiple linear regression model was developed incorporating age, baseline eGFR, HtTKV, and three image texture features identified by stability feature selection (Entropy, Correlation, and Energy). Including texture in a multiple linear regression model (predicting percent change in eGFR) improved Pearson correlation coefficient from -0.51 (using age, eGFR, and HtTKV) to -0.70 (adding texture). Thus, texture analysis offers an approach to refine ADPKD prognosis and should be further explored for its utility in individualized clinical decision making and outcome prediction.

Development and Validation of a Disease-Specific Questionnaire to Assess Patient-Reported Symptoms in Polycystic Liver Disease.

UNLABELLED: Treatment of polycystic liver disease (PLD) focuses on symptom improvement. Generic questionnaires lack sensitivity to capture PLD-related symptoms, a prerequisite to determine effectiveness of therapy. We developed and validated a disease-specific questionnaire that assesses symptoms in PLD (PLD-Q). We identified 16 PLD-related symptoms (total score 0-100 points) by literature review and interviews with patients and clinicians. The developed PLD-Q was validated in Dutch (n = 200) and United States (US; n = 203) PLD patients. We assessed the correlation of PLD-Q total score with European Organization for Research and Treatment of Cancer (EORTC) symptom scale, global health visual analogue scale (VAS) of EQ-5D, and liver volume. To test discriminative validity, we compared PLD-Q total scores of patients with different PLD severity stages (Gigot classification) and PLD-Q total scores of PLD patients with general controls and polycystic kidney disease patients without PLD. Reproducibility was tested by comparing original test scores with 2-week retest scores. In total, 167 Dutch and 124 US patients returned the questionnaire. Correlation between PLD-Q total score and EORTC symptom scale (The Netherlands [NL], r = 0.788; US, r = 0.811) and global health VAS (NL, r = -0.517; US, r = -0.593) was good. There was no correlation of PLD-Q total score with liver volume (NL, r = 0.138; P = 0.236; US, r = 0.254; P = 0.052). Gigot type III individuals scored numerically higher than type II patients (NL, 46 vs. 40; P = 0.089; US, 48 vs. 36; P = 0.055). PLD patients scored higher on the PLD-Q total score than general controls (NL, 42 vs. 17; US, 40 vs. 13 points) and polycystic kidney disease patients without PLD (22 points). Reproducibility of PLD-Q was excellent (NL, r = 0.94; US, 0.96). CONCLUSION: PLD-Q is a valid, reproducible, and sensitive disease-specific questionnaire that can be used to assess PLD-related symptoms in clinical care and future research. (Hepatology 2016;64:151-160).

Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys.

Deep learning techniques are being rapidly applied to medical imaging tasks-from organ and lesion segmentation to tissue and tumor classification. These techniques are becoming the leading algorithmic approaches to solve inherently difficult image processing tasks. Currently, the most critical requirement for successful implementation lies in the need for relatively large datasets that can be used for training the deep learning networks. Based on our initial studies of MR imaging examinations of the kidneys of patients affected by polycystic kidney disease (PKD), we have generated a unique database of imaging data and corresponding reference standard segmentations of polycystic kidneys. In the study of PKD, segmentation of the kidneys is needed in order to measure total kidney volume (TKV). Automated methods to segment the kidneys and measure TKV are needed to increase measurement throughput and alleviate the inherent variability of human-derived measurements. We hypothesize that deep learning techniques can be leveraged to perform fast, accurate, reproducible, and fully automated segmentation of polycystic kidneys. Here, we describe a fully automated approach for segmenting PKD kidneys within MR images that simulates a multi-observer approach in order to create an accurate and robust method for the task of segmentation and computation of TKV for PKD patients. A total of 2000 cases were used for training and validation, and 400 cases were used for testing. The multi-observer ensemble method had mean ± SD percent volume difference of 0.68 ± 2.2% compared with the reference standard segmentations. The complete framework performs fully automated segmentation at a level comparable with interobserver variability and could be considered as a replacement for the task of segmentation of PKD kidneys by a human.

Automatic total kidney volume measurement on follow-up magnetic resonance images to facilitate monitoring of autosomal dominant polycystic kidney disease progression.

BACKGROUND: Renal imaging examinations provide high-resolution information about the anatomic structure of the kidneys and are used to measure total kidney volume (TKV) in autosomal dominant polycystic kidney disease (ADPKD) patients. TKV has become the gold-standard image biomarker for ADPKD progression at early stages of the disease and is used in clinical trials to characterize treatment efficacy. Automated methods to segment the kidneys and measure TKV are desirable because of the long time requirement for manual approaches such as stereology or planimetry tracings. However, ADPKD kidney segmentation is complicated by a number of factors, including irregular kidney shapes and variable tissue signal at the kidney borders. METHODS: We describe an image processing approach that overcomes these problems by using a baseline segmentation initialization to provide automatic segmentation of follow-up scans obtained years apart. We validated our approach using 20 patients with complete baseline and follow-up T1-weighted magnetic resonance images. Both manual tracing and stereology were used to calculate TKV, with two observers performing manual tracings and one observer performing repeat tracings. Linear correlation and Bland-Altman analysis were performed to compare the different approaches. RESULTS: Our automated approach measured TKV at a level of accuracy (mean difference ± standard error = 0.99 ± 0.79%) on par with both intraobserver (0.77 ± 0.46%) and interobserver variability (1.34 ± 0.70%) of manual tracings. All approaches had excellent agreement and compared favorably with ground-truth manual tracing with interobserver, stereological and automated approaches having 95% confidence intervals ∼ ± 100 mL. CONCLUSIONS: Our method enables fast, cost-effective and reproducible quantification of ADPKD progression that will facilitate and lower the costs of clinical trials in ADPKD and other disorders requiring accurate, longitudinal kidney quantification. In addition, it will hasten the routine use of TKV as a prognostic biomarker in ADPKD.

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images.

OBJECTIVE: The objective of the present study is to develop and validate a fast, accurate, and reproducible method that will increase and improve institutional measurement of total kidney volume and thereby avoid the higher costs, increased operator processing time, and inherent subjectivity associated with manual contour tracing. MATERIALS AND METHODS: We developed a semiautomated segmentation approach, known as the minimal interaction rapid organ segmentation (MIROS) method, which results in human interaction during measurement of total kidney volume on MR images being reduced to a few minutes. This software tool automatically steps through slices and requires rough definition of kidney boundaries supplied by the user. The approach was verified on T2-weighted MR images of 40 patients with autosomal dominant polycystic kidney disease of varying degrees of severity. RESULTS: The MIROS approach required less than 5 minutes of user interaction in all cases. When compared with the ground-truth reference standard, MIROS showed no significant bias and had low variability (mean ± 2 SD, 0.19% ± 6.96%). CONCLUSION: The MIROS method will greatly facilitate future research studies in which accurate and reproducible measurements of cystic organ volumes are needed.

Intense parenting: a qualitative study detailing the experiences of parenting children with complex care needs.

BACKGROUND: Increased numbers of children with chronic illnesses and/or disabilities who have complex care needs are living at home. Along with the transfer of care to the home setting, parents assume the primary responsibility of their child's complex care needs. Accordingly, it becomes even more important to understand the evolving roles and challenges faced by parents of children with complex care needs in order to better support them. The aim of this paper is to present research findings that add to our understanding of the roles parents assume in parenting their children with complex care needs. METHODS: To arrive at a detailed and accurate understanding of families' perspectives and experiences, the qualitative research design of ethnography was used. In total, 68 parents from 40 families were recruited. Data collection strategies included ethnographic methods of interviewing and photovoice. Several levels of analysis generated a sociocultural theme with subthemes representing how parents experienced raising children with complex care needs within the context of their life situations. RESULTS: Intense parenting as the overarching theme refers to the extra efforts parents had to commit to in raising their children with complex care needs. Parenting was described as labour-intensive, requiring a readiness to provide care at any time. This left parents with minimal time for addressing any needs and tasks not associated with caring for their child. The main theme is supported by four sub-themes: 1) the good parent; 2) more than a nurse; 3) there's just not enough; 4) it takes a toll on the health of parents. CONCLUSIONS: Overall, parents of children with complex care needs take on more roles as well as work more intensely at these roles than parents of healthy children. This, in turn, has led to the need for additional supports and resources for parents. However, to date, parents of children with complex care needs are still lacking adequate services and supports necessary to help them in their role of intense parenting. The findings sensitize professionals to the issues confronted by parents caring for children with complex care needs. Implications for further research and clinical practice are discussed.

Health care costs among patients with hematologic malignancies receiving allogeneic transplants: a US payer perspective.

ABSTRACT: Patients with hematologic malignancies undergoing allogeneic hematopoietic cell transplant (allo-HCT) require extensive care. Using the Merative MarketScan Commercial Claims and Encounters database (2016 Q1-2020 Q2), we quantified the costs of care and assessed real-world complication rates among commercially insured US patients diagnosed with a hematologic malignancy and aged between 12 and 64 years undergoing inpatient allo-HCT. Health care resource use and costs were assessed from 100 days before HCT to 100 days after HCT. Primary hospitalization was defined as the time from HCT until first discharge date. Incidence of complications was assessed using medical billing codes from HCT date to 100 days after HCT. Among the 1082 patients analyzed, allo-HCT grafts included peripheral blood (79%), bone marrow (11%), and umbilical cord blood (3%). In the 100 days after HCT, 52% of the patients experienced acute graft-versus-host disease; 21% had cytomegalovirus infection. The median primary hospitalization length of stay (LOS) was 28 days; 31% required readmission in first 100 days after HCT. Across the transplant period (14 days pretransplant to 100 days posttransplant), 44% of patients were admitted to the intensive care unit with a median LOS of 29 days. Among those with noncapitated health plans (n = 937), median cost of all-cause health care per patient during the transplant period was $331 827, which was driven by primary hospitalization and readmission. Additionally, the predicted median incremental costs per additional day in an inpatient setting increased with longer LOS (eg, $3381-$4071, 10th-20th day.) Thus, decreasing length of primary hospitalization and avoiding readmissions should significantly reduce the allo-HCT cost of care.

Real-world use and clinical impact of an electronic patient-reported outcome tool in patients with solid tumors treated with immuno-oncology therapy.

BACKGROUND: Utilization of electronic patient-reported outcome (ePRO) tools to monitor symptoms in patients undergoing cancer treatment has shown clinical benefits. Tennessee Oncology (TO) implemented an ePRO platform in 2019, allowing patients to report their health status online. We conducted a real-world, multicenter, observational, non-interventional cohort study to evaluate utilization of this platform in adults with solid tumors who initiated immuno-oncology (IO) therapy as monotherapy or in combination at TO clinics. METHODS: Patients initiating IO therapy prior to platform implementation were included in a historical control (HC) cohort; those initiating treatment after implementation were included in the ePRO cohort, which was further divided into ePRO users (platform enrollment ≤ 45 days from IO initiation) and non-users. Data were extracted from electronic medical records; patients were followed for up to 6 months (no minimum follow up). Outcomes included patient characteristics, treatment patterns, duration of therapy (DoT), and overall survival (OS). RESULTS: Data were collected for 538 patients in the HC and 1014 in the ePRO cohort; 319 in the ePRO cohort were ePRO users (uptake rate 31%). Baseline age was higher, more patients had stage IV disease at diagnosis, and more received monotherapy (82 vs 52%, respectively) in the HC vs the ePRO cohort. Median follow-up was 181.0 days (range 0.0-182.6) in the HC and 175.0 (0.0-184.0) in the ePRO cohort. Median DoT of index IO regimen was 5.1 months (95% confidence interval [CI], 4.4-NE) in the HC cohort vs not estimable (NE) in the ePRO cohort. Multivariable regression adjusting for baseline differences confirmed lower risk of treatment discontinuation in the ePRO vs HC cohort: hazard ratio (HR) 0.83 (95% CI, 0.71-0.97); p < 0.05. The estimated 6-month OS rate was 65.5% in the HC vs 72.4% in the ePRO cohort (p < 0 .01). Within the ePRO cohort, DoT of index IO regimen and OS did not differ between users and non-users. In ePRO users, patient platform use was durable over 6 months. CONCLUSION: Improvements in DoT and OS were seen after ePRO platform implementation. Conclusions are limited by challenges in separating the impact of platform implementation from other changes affecting outcomes.

Projected Impact of Omidubicel-onlv on Racial/Ethnic Disparities in Allogeneic Hematopoietic Cell Transplantation (Allo-HCT) Outcomes in Hematologic Malignancies.

INTRODUCTION: In a phase III clinical trial (NCT02730299), omidubicel-onlv, a nicotinamide-modified allogeneic hematopoietic progenitor cell therapy, showed rapid hematopoietic and immune recovery compared with standard umbilical cord blood (UCB) transplant across all racial/ethnic groups. METHODS: A decision-tree model was used to project the effect of omidubicel-onlv availability on addressing health disparities in allogeneic hematopoietic cell transplantation (allo-HCT) access and outcomes for patients with hematologic malignancies. The model used a hypothetical population of 10,000 allo-HCT-eligible US adults, for whom matched related donors were not available. Patients received matched or mismatched unrelated donor, haploidentical, UCB transplant, or no transplant. Scenarios with omidubicel-onlv use of 0% (status quo), 10%, 15%, 20%, and 30% were modeled on the basis of proportional reductions in other allo-HCT sources or no transplant by racial/ethnic group. RESULTS: Increased omidubicel-onlv use was associated with a higher proportion of patients undergoing allo-HCT, decreased time to allo-HCT, decreased 1-year non-relapse mortality, and increased 1-year overall survival, particularly among racial minorities. In the scenario modeling 20% omidubicel-onlv use, the proportion of Black patients receiving allo-HCT increased by 129%; increases were also observed in Asian (64%), Hispanic (45%), and other (42%) patient groups. Modeled time to allo-HCT improved among transplanted patients (23%) from 11.4 weeks to 8.8 weeks. One-year OS in the overall population increased by 3%, with improvements ranging from 3% for White patients to 5% for Black patients. CONCLUSION: This study demonstrates that broad access to omidubicel-onlv could increase access to allo-HCT and improve outcomes for patients, with the greatest benefits seen among racial/ethnic minority groups.

Napping during breaks on night shift: critical care nurse managers' perceptions.

BACKGROUND: Fatigue associated with shiftwork can threaten the safety and health of nurses and the patients in their care. Napping during night shift breaks has been shown to be an effective strategy to decrease fatigue and enhance performance in a variety of work environments, but appears to have mixed support within health care. PURPOSE: The purpose of this study was to explore critical care unit managers'perceptions of and experiences with their nursing staff's napping practices on night shift, including their perceptions of the benefits and barriers to napping/not napping in terms of patient safety and nurses'personal health and safety. METHODS: A survey design was used. Forty-seven Canadian critical care unit managers who were members of the Canadian Association of Critical Care Nurses responded to the web-based survey. Data analysis involved calculation of frequencies and percentages for demographic data, use of the Friedman rank test for comparison of managers' perceptions, and content analysis for responses to open-ended questions. RESULTS: The findings of this study offer valuable insights into the complexities and conflicts perceived by managers with respect to napping on night shift breaks by nursing staff Staff and patient health and safety issues, work and break expectations and experiences, and strengths and deficits related to organizational napping resources and policy are considerations that will be instrumental in the development of effective napping strategies and guidelines.

Economic Impact of Recurrent Clostridioides difficile Infection in the USA: A Systematic Literature Review and Cost Synthesis.

INTRODUCTION: Up to 35% of patients with a first episode of Clostridioides difficile infection (CDI) develop recurrent CDI (rCDI), and of those, up to 65% experience multiple recurrences. A systematic literature review (SLR) was conducted to review and summarize the economic impact of rCDI in the United States of America. METHODS: English-language publications reporting real-world healthcare resource utilization (HRU) and/or direct medical costs associated with rCDI in the USA were searched in MEDLINE, MEDLINE In-Process, Embase, and the Cochrane Library databases over the past 10 years (2012-2022), as well as in selected scientific conferences that publish research on rCDI and its economic burden over the past 3 years (2019-2022). HRU and costs identified through the SLR were synthesized to estimate annual rCDI-attributable direct medical costs to inform the economic impact of rCDI from a US third-party payer's perspective. RESULTS: A total of 661 publications were retrieved, and 31 of them met all selection criteria. Substantial variability was found across these publications in terms of data source, patient population, sample size, definition of rCDI, follow-up period, outcomes reported, analytic approach, and methods to adjudicate rCDI-attributable costs. Only one study reported rCDI-attributable costs over 12 months. Synthesizing across the relevant publications using a component-based cost approach, the per-patient per-year rCDI-attributable direct medical cost was estimated to range from $67,837 to $82,268. CONCLUSIONS: While real-world studies on economic impact of rCDI in the USA suggested a high-cost burden, inconsistency in methodologies and results reporting warranted a component-based cost synthesis approach to estimate the annual medical cost burden of rCDI. Utilizing available literature, we estimated the average annual rCDI-attributable medical costs to allow for consistent economic assessments of rCDI and identify the budget impact on US payers.

Real-World Outcomes of Trilaciclib Among Patients with Extensive-Stage Small Cell Lung Cancer Receiving Chemotherapy.

INTRODUCTION: Trilaciclib was recently approved in the USA for reducing chemotherapy-induced myelosuppression (CIM) among adults with extensive-stage small cell lung cancer (ES-SCLC) when administered prior to chemotherapy. There is limited understanding of real-world outcomes of trilaciclib. METHODS: A comprehensive literature review was conducted using a keyword search in the MEDLINE, Embase, and conference abstracts. Additional studies were identified through communications with the authors of relevant studies. Published and unpublished real-world studies of trilaciclib- and comparable non-trilaciclib-treated patients with ES-SCLC were included. Evidence on myelosuppressive hematologic adverse events (HAEs), cytopenia-related healthcare utilization, and other reported outcomes (e.g., hospitalizations, dose reduction, and treatment delay) were synthesized. If feasible, outcomes were compared qualitatively between the trilaciclib and historical reference groups, and between first-line trilaciclib initiators and the overall trilaciclib population. Weighted averages were estimated for selected outcomes using sample size as the weight. RESULTS: The literature search identified five unique studies based on eight records-two included trilaciclib only, two non-trilaciclib only, and one both. In trilaciclib cohorts, the weighted average prevalence of grade ≥ 3 myelosuppressive HAEs in ≥ 1 lineage, ≥ 2 lineages, and all three lineages was 40.5%, 14.5%, and 7.5%, respectively. All rates were numerically lower compared to the historical non-trilaciclib cohorts (58.8%, 28.0%, 13.0% respectively). Cytopenia-related healthcare utilization was also lower in the trilaciclib cohorts. In general, first-line trilaciclib initiators had numerically lower myelosuppressive HAEs and cytopenia-related healthcare utilization than the overall trilaciclib patients. CONCLUSIONS: The existing evidence suggests that trilaciclib may reduce single and multilineage grade ≥ 3 myelosuppressive HAEs and cytopenia-related healthcare utilization among patients with ES-SCLC in the real world. It is a promising new treatment for CIM prevention in ES-SCLC and may bring greater benefits to first-line trilaciclib initiators. Future studies are recommended to further evaluate the real-world effectiveness of trilaciclib.