Adjustment Model Research Articles

Türkiye's responses to the 2023 earthquakes: An application of family adjustment and adaptation response model

AbstractAfter devastating earthquakes struck Türkiye in February 2023, the country faced the challenge of addressing the psychosocial needs of the survivors. This article uses the Family Adjustment and Adaptation Response (FAAR) model to conceptualize Türkiye's responses to the earthquakes in terms of its demands (i.e., cumulative strains and current stressors), capabilities (i.e., existing resources and coping mechanisms), and meaning/belief systems (i.e., shared meaning, religion/spirituality, and positive outlook/hope). A historical context is provided to better understand the cumulative tensions and resilience of the country, seeking ways to strengthen effective crisis responses in anticipation of an even bigger earthquake in the coming years. Additionally, this article may spark a conversation among family practitioners in different countries about how to collaborate on mobilizing resources during challenging times.

Assessing self–other agreement and dyadic adjustment in marital dyads

In this study, we examined self–other agreement in married couples to examine the association between their perceptions of self and other psychological problems and dyadic adjustment. We also postulated that dyadic adjustment would moderate self–other agreement ratings on low- and high-visibility traits of psychological problems. Using a cross-informant assessment design, 101 married dyads in three marital groups (non-clinical, transplant, and divorcing dyads) provided reciprocal self and other ratings for psychological problems. Self–other agreement indices were quantified using self–other differences scores and Pearson r, qualifying (Q) correlations. The self–other agreement models yielded significant differences in dyadic adjustment across couple types. Couples that demonstrated moderate to elevated levels of self–other agreement for psychological problems had higher levels of dyadic adjustment. Differences in self–other psychological problem ratings were robust predictors of dyadic maladjustment and poor relational quality. Dyadic adjustment was found to moderate self–other agreement for psychological problems, especially for wives’ appraisals and husbands’ attunement to wives’ low-visibility problems. The findings validate the impact of self–other agreement in models of relationship conflict and adjustment. Wive’s other views tended to have large effect sizes in dyadic adjustment. The study’s limitations and recommendations for future research are also discussed.

The comparative role of physical system processes in Hudson Strait ice stream cycling: a comprehensive model-based test of Heinrich event hypotheses

Abstract. Despite their recognized significance on global climate and extensive research efforts, the mechanism(s) driving Heinrich events remain(s) a subject of debate. Here, we use the 3D thermomechanically coupled glacial systems model (GSM) to examine the Hudson Strait ice stream surge cycling and the role of three factors previously hypothesized to play a critical role in Heinrich events: ice shelves, glacial isostatic adjustment, and sub-surface ocean temperature forcings. In contrast to all previous modeling studies examining HEs, the GSM uses a transient last glacial cycle climate forcing, global viscoelastic glacial isostatic adjustment model, and sub-glacial hydrology model. The results presented here are based on a high-variance sub-ensemble retrieved from North American history matching for the last glacial cycle. Over our comparatively wide sampling of the potential parameter space (52 ensemble parameters for climate forcing and process uncertainties), we find two modes of Hudson Strait ice streaming: classic binge–purge versus near-continuous ice streaming with occasional shutdowns and subsequent surge onset overshoot. Our model results indicate that large ice shelves covering the Labrador Sea during the last glacial cycle only occur when extreme calving restrictions are applied. The otherwise minor ice shelves provide insignificant buttressing for the Hudson Strait ice stream. While sub-surface ocean temperature forcing leads to minor differences regarding surge characteristics, glacial isostatic adjustment does have a significant impact. Given input uncertainties, the strongest controls on ice stream surge cycling are the poorly constrained deep geothermal heat flux under Hudson Bay and Hudson Strait and the basal drag law. Decreasing the geothermal heat flux within available constraints and/or using a Coulomb sliding law instead of a Weertman-type power law leads to a shift from the near-continuous streaming mode to the binge–purge mode.

Navigating the precarious path: Understanding the dualisation of the Italian labour market through the lens of involuntary part-time employment

This article investigates the surge in Involuntary Part-Time (IPT) employment in Italy from 2004 to 2019, exploring its impact on various socio-economic groups and adopting a spatial perspective. The study tests the hypothesis that technological shifts, specifically routine biased technological change (RBTC), and the expansion of household substitution services contribute to IPT growth. There is a widening negative gap in IPT prevalence among marginalized groups - women, young, and less skilled workers. After controlling for sector and occupation, the higher IPT propensity diminishes but remains significant, hinting at persistent discrimination. Additionally, segregation into more exposed occupations and sectors intensifies over time. Leveraging province-level indicators, and using a Partial Adjustment model, there is statistical support for RBTC’s correlation with IPT, especially among women. The impact of household substitution services is notably pronounced for women, highlighting sector segregation.

Association between secondhand smoke and liver injury among US non-smoking adults: Mediation analysis of body mass index in the NHANES.

Liver injury is a primary factor in the pathogenesis of most liver diseases, which can lead to liver failure. Secondhand smoke (SHS) is a serious public problem. This research explored the correlation between SHS and the indicators of liver injury. This cross-sectional study was based on the National Health and Nutrition Examination Survey (NHANES) 2011-2016. The relationship between SHS and indicators of liver injury was explored by the weighted linear regression model and smooth curve fitting. The weighted threshold saturation effect model tested the relationship and inflection point between them. Mediation analyses were used to explore whether body mass index (BMI) mediates the correlation between SHS and liver injury indicators. Our cross-sectional study included 3811 non-smoking participants (aged 20-80 years). The full covariate adjustment model (β= -0.05; 95% CI: -0.08 - -0.02) showed a significant and negative correlation between log cotinine and albumin (ALB). Compared to the unexposed group, the ALB, and total protein (TP) were decreased by 0.16 g/dL, 0.26 g/dL in the heavy exposure group [ALB: -0.16 (-0.26 - -0.05), TP: -0.26 (-0.38 - -0.13)], respectively. Smoothed curve fitting revealed a nonlinear relationship between log cotinine and fibrosis-4 index (FIB-4 score), with the inflection point of log cotinine at -1.72. When log cotinine was < -1.72, the log cotinine significantly and positively correlated with the FIB-4 score (β=0.27; 95% CI: 0.06-0.49). BMI partially mediated the effect of SHS exposure on ALB or TP. SHS has harmful effects on the liver in never-smoking adults. BMI partially mediated the effect of SHS exposure on ALB or TP. More prospective and basic research in the future is necessary to focus on validating our results.

Economic Analysis of the Impact of Waste on the Production and Consumption of Dates in Saudi Arabia

The goal of this study was to determine how the loss of dates affected food security in Saudi Arabia from 2000 to 2021. The researchers achieved this by using food security indicators, economic equations to quantify agricultural resource losses, and econometric analyses to develop a partial adjustment model. The results show that dates are considered a self-sufficient crop as well as an export crop, as the state resorts to exporting the surplus instead of storing it for local consumption. During the study period, there was an increase in the period of sufficiency in date production for local consumption and the period of coverage of imports for local consumption. In 2000, the volume of dates lost increased by approximately 131.22%. The total loss of land and water resources reached 31,918.4 hectares and 324.759 million cubic meters, respectively. The value of the partial adjustment coefficient (λ) indicates that about 81.1% of the imbalance in the equilibrium between the actual and equilibrium levels is adjusted within one year. Loss is considered one of the most important factors that determine food security for dates, in addition to the total value of loans financed to date factories, the total population, and the level of technological progress in the marketing and storage of dates. It was found that a change of 10% in these variables leads to a change in food security for dates of (−2.37%), 0.07, (−15.33%), and 0.58%, respectively, and the adjusted coefficient of determination was estimated at 0.93. This study recommends the following: (1) expanding the use of modern technologies for date post-harvest transportation and storage, and (2) increasing support and loans allocated to date factories to increase warehouses for cooling and storage to accommodate the increase in production and surplus consumption.

High-accuracy bathymetric method fusing ICESAT-2 datasets and the two-media photogrammetry model

Improving the accuracy of nearshore bathymetric measurements is essential for understanding coastal environments, resource management, and navigation. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) is the first laser satellite that uses the photon-counting technique. The ICESat-2 is equipped with the Advanced Topographic Laser Altimeter System (ATLAS), which enables higher-accuracy measurements of water, ice, and land elevation on Earth. Two-media photogrammetric bathymetry is a type of nearshore bathymetric technology that uses the geometrical characteristics of light rays. With this technique, the accuracy and reliability mainly depend on eliminating systematic errors and ensuring accurate spatial photogrammetric positioning relative to the object being measured. To improve the bathymetric accuracy of two-media photogrammetry, we integrated high-accuracy elevation data from photon datasets as constraining and control parameters. The improved method effectively eliminated systematic errors in two-media photogrammetry during the established joint-block adjustment model. To improve its accuracy and reliability, we employed multispectral WorldView-2 stereo images in our experiments. Furthermore, the bathymetric results were validated and assessed using in situ and photon data. The experimental results show that the highest accuracy achieved with the bathymetric measurements in our study area was a root mean square error (RMSE) of 0.96 m and a mean absolute error of 0.57 m. Using the proposed fusion method, the bathymetric accuracy (as measured using the RMSE) was 1 m higher than that of two-media photogrammetry without the photon datasets.

Ownership structure, adjustment speed toward target leverage and CEO power

PurposeThis study aims to investigate the impact of ownership structure on firm adjustment speed toward the target leverage.Design/methodology/approachThe study employs a partial adjustment model on a sample of 694 publicly listed firms from 2007 to 2021 in Vietnam.FindingsThe study finds that state and foreign ownerships inhibit the speed at which firms approach their optimal level of debt. Interestingly, this negative association is less pronounced in firms managed by powerful CEOs (duality CEOs; highly experienced CEOs; CEOs who they own or their families possess a large number of shares). Further, state and foreign ownership are found to be positively associated with firm performance. This beneficial impact weakens, however, when firms use more debts.Originality/valueThe outcome reveals that having a powerful CEO on board can help businesses in this emerging market counteract the detrimental effects that foreign and state ownership leave on the process of adjusting leverage.

Red-cell omega-3 fatty acids associate with increased hippocampal volume and superior longitudinal cognition in atrial fibrillation

Abstract Background Atrial fibrillation (AF) is associated with cognitive impairment and dementia. Omega-3 Fatty Acids (n-3 FAs) have anti-thrombotic, anti-inflammatory and anti-oxidative properties; however, their neuroprotective effects remain controversial. Here, we report the association of n-3 FAs with both structural (hippocampal volume) and functional (cognition) readouts in a large cohort of AF pts. Purpose a) To determine the association of n-3 FAs and left and right hippocampal volume at baseline in AF pts. b) To assess the predictive value of HV and n-3 FAs for the risk of cognitive impairment after a 7-year follow-up period. Methods This prospective ongoing multicenter Swiss Atrial Fibrillation study (Swiss-AF) included 2,359 pts with documented AF and baseline red-cell n-3 FAs levels, measured by gas chromatography and mass spectrometry. Hippocampal volume (HV) and segmentation based intracranial volume (ICV) were analyzed by FreeSurfer's (v 7.4.0) subregion segmentation module and Sequence Adaptive Multimodal SEGmentation from brain MRI in 1,736 pts. Detailed neurocognitive assessments in pts at baseline and follow up periods were performed. We used mixed-effect linear regression models to determine the association of n-3 FAs and HV. For conversion to cognitive impairment (defined as MoCA score &amp;lt; 26), we performed cox-proportional hazards regression model. Two adjustment models were applied as described in the figures. Results Patients with AF (mean age, 73 years old [±8.5 SD]; 157 women [27%]) with 9569 cognitive evaluations (mean follow-up, 3.6 years [±2.3 SD]) were assessed. At baseline, we observed statistically significant associations between total n-3 FAs levels (EPA + DHA + ALA + DPA) and individual n-3 FAs (EPA, DHA, DPA) with increased HV after adjustment for ICV and other covariates (Fig1A, 1B). After all adjustments, EPA remained associated with both bilateral HV and right HV. Furthermore, we observed a significant association between HV and neurocognitive assessments, as measured both in global (MoCA, CoCo) and specific tests (TMT-A, TMT-B, DSST, SF) (Fig1C). Over time, quartile 4 (Q4, highest n-3) compared to quartile 1 (Q1, lowest), had a 16% lower risk of cognitive impairment (HR, 0.84 [CI 0.75-0.93]; P=0.001) for total n-3 FAs and even 30% lower specifically for EPA (HR, 0.7 [CI 0.63-0.78]; P&amp;lt;0.001). The risk of cognitive impairment was 47% lower (HR, 0.53 [CI 0.45-0.63]; P&amp;lt;0.001) when the highest HV Q4 was compared to lowest HV Q1 (Fig2A). In combination, the highest quartile of bilateral HV and EPA demonstrated an increased probability of being cognitive impairment-free and they had a 72% lower (HR, 0.28 [0.18-0.43]; P&amp;lt;0.001) risk of cognitive impairment (Fig2B). Conclusions 1. Red cell n-3 FAs levels are associated with higher HV in AF pts. 2. Higher baseline levels of n-3 FAs, particularly of EPA, are associated with both an increased HV and a decreased risk of cognitive impairment after 7 years follow up.

Migration and mental health: the case of postpartum depressive symptoms in Portugal

Abstract Background Postpartum depression (PPD) affects about 17% of healthy mothers within one year of childbirth. The etiology remains unknown, but PPD is influenced by a combination of genetic, physical, psychosocial, and obstetric factors, migration could influence the risk. Methods We analyzed data collected within the scope of baMBINO (Perinatal Health in Migrants: Barriers, Incentives, and Outcomes), a Portuguese prospective cohort study, aimed to investigate the maternity experiences and outcomes of migrant women, defined as foreign-born women, and compared to native women. Among the 5431 women enrolled at delivery, 3006 (55%) were considered eligible for this study and interviewed in their preferred language, within six months of recruitment. The Edinburgh Postnatal Depression Scale (EPDS) was administered during this interview, along with the Migrant-Friendly Maternity Care Questionnaire (MFMCQ). Results 2890 (96%) women were included in the analytical sample for this study. Among women included, 1475 (51%) were migrants or refugees. The proportions of women having EPDS scores ≥ 10 were overall greater among migrants than among native women (7.2% vs. 12.4%, p &amp;lt; 0.001) and the risk remained higher after multiple adjustment models. Conclusions Migration status, poor experience with maternal care and language proficiency increased the risk of PPDS and should be carefully addressed as part of perinatal care.

Resources Price Adjustment in Cloud Computing for Load Balancing and Fairness Between Users and Suppliers

Resource price adjustment is a challenging issue when building a cloud computing system. For this purpose, we present an approach that adopts a market-driven price adjustment model as an economic incentive model and ensures the balance between supply and demand. We show how this model may be adapted and applied to an infrastructure as a service (IaaS) in cloud computing. We place ourselves in the context of the virtual machines market. To achieve competitive equilibrium, prices are adjusted according to a tâtonnement-like process. The prices are computed by a third party, the auctioneer. However, this process requires several assumptions to ensure the existence and stability of competitive equilibrium, not all of which are verified by cloud computing systems. The atomicity and convexity of preferences are not guaranteed by cloud computing systems. These questions will be the subject of our empirical study. We find empirically that the change in the sign of excess demand, indicating the existence of equilibrium, occurs between two similar prices. The experimental results show that the proposed dynamic price adjustment approach is more profitable than fixed-price pricing, allowing dynamic suppliers to become important market agents.

The persisting conundrum of mantle viscosity inferred from mantle convection and glacial isostatic adjustment processes

Mantle viscosity exerts important controls on the long-term (i.e., >106 years) dynamics of the mantle and lithosphere and the short-term (i.e., 10 to 104 years) crustal motion induced by loading forces including ice melting, sea-level changes, and earthquakes. However, mantle viscosity structures inferred from modeling observations associated with mantle dynamic and loading processes may differ significantly and remain a hotly debated topic over recent decades. In this study, we investigate the effects of mantle viscosity structures on observations of the geoid, mantle structures, and present-day crustal motions and time-varying gravity by considering five representative mantle viscosity structures in models of mantle convection and glacial isostatic adjustment (GIA). These five viscosity models fall into two categories: 1) two viscosity models derived from modeling the geoid in mantle convection models with ∼100 times more viscous lower mantle than the upper mantle, and 2) the other three with less viscosity increase from the upper to lower mantles that are derived from modeling the late Pleistocene and Holocene relative sea level changes and other observations in GIA models. Our convection models use the plate motion history for the last 130 Myrs as the surface boundary conditions and depth- and temperature-dependent viscosity to predict the present-day convective mantle structure of subducted slabs and the intermediate wavelength (degrees 4–12) geoid. Our GIA models using different ice history models (e.g., ICE-6 G and ANU) compute the GIA-induced present-day crustal motions and time-varying gravity. Our calculations demonstrate that while the viscosity models with a higher viscosity in the lower mantle (∼2 × 1022 Pa.s) reproduce the degrees 4–12 geoid and seismic slab structures, they significantly over-predict the geodetic (i.e., GPS and GRACE) observations of crustal motions and time varying gravity. Our calculations also show that while two viscosity models derived from fitting the RSL data with averaged mantle viscosity of ∼1021 Pa.s for the top 1200 km of the mantle reproduce well the geodetic observations independent of ice models, they fail to explain the geoid and seismic slab structures. Therefore, our study highlights the persisting conundrum of mantle viscosity structures derived from different observations. We also discuss a number of possible ways including transient, stress-dependent and 3-D viscosity to resolve this important issue in Geodynamics.

Fast stability enhancement of inverter‐based microgrids using NGO‐LSTM algorithm

AbstractTo improve the stability of the inverter‐based microgrid (MG), this paper employs a novel data‐driven based method to coordinately adjust control parameters of inverters in a fast local manner. During the design process, an offline eigenvalue based optimization problem that is used to calculate the optimal control parameters under various operating conditions is first constructed. In order to reduce reliance on full system information, a feature selection algorithm is utilized to extract the most relevant local measurements that influence the adjustment of each control parameter. Then, regarding local measurements as input variables and optimal control parameters as output variables, based on northern goshawk optimization (NGO) and long short‐term memory (LSTM) network, a novel deep learning algorithm is proposed to train the local parameter adjustment model (LPAM) by learning the mapping relationship between them. During the application, to guarantee the stability of MG all the time, a security region based shielding mechanism is developed, where the improper control parameter adjustment will be replaced by a safe one. The case study indicates that the proposed algorithm has better mapping accuracy than traditional LSTM neural networks and also faster calculation speed than the traditional offline optimization‐based method. The effectiveness and advantages of the proposed method are demonstrated in a modified 9‐bus MG.

A stableness of resistance model for nonresponse adjustment with callback data

Abstract Nonresponse arises frequently in surveys, and follow-ups are routinely made to increase the response rate. In order to monitor the follow-up process, callback data have been used in social sciences and survey studies for decades. In modern surveys, the availability of callback data is increasing because the response rate is decreasing, and follow-ups are essential to collect maximum information. Although callback data are helpful to reduce the bias in surveys, such data have not been widely used in statistical analysis until recently. We propose a stableness of resistance assumption for nonresponse adjustment with callback data. We establish the identification and the semiparametric efficiency theory under this assumption, and propose a suite of semiparametric estimation methods including doubly robust estimators, which generalize existing parametric approaches for callback data analysis. We apply the approach to a Consumer Expenditure Survey dataset. The results suggest an association between nonresponse and high housing expenditures.

Modeling and optimization of two-stage emergency supply chain network under uncertain environment

In order to formulate an effective emergency supply chain network planning scheme, improve the efficiency of emergency organization rescue and realize the reasonable allocation of resources and materials, considering the uncertainty of supply and demand, a distribution mode combining multiple transportation modes is adopted, and the optimization objectives are to minimize network response time, cost and carbon emissions. A two-stage emergency supply chain mixed integer programming model is constructed. At the same time, an adjustable robust optimization model is constructed based on robust optimization theory to enhance the network's ability to cope with uncertain factors, and the constraints with uncertain parameters are transformed through linear duality theory. In order to improve the solution effect of the model, an optimize cuckoo search (OCS) algorithm is proposed, and a benchmark example is introduced to verify the superiority and applicability of the OCS algorithm in solving multi-objective functions. Finally, the emergency material distribution data during the COVID-19 epidemic in Wuhan is used to study the emergency supply chain network decision-making problem with uncertain parameters, and the effective suppression of the robust control coefficient on uncertain disturbances is proved through sensitivity analysis.

Dynamics of a Price Adjustment Model with Distributed Delay

This paper deals with the stability and occurrence of Hopf bifurcation of a distributed delay differential cobweb model using the chain trick technique. This is a generalized form of the fixed delay cobweb model to which it is compared using the same parameter values. The results from the delay distribution showed that whenever less weight (γ=0.146) is put on past prices, the current equilibrium price is adjusted upwards while the reverse is observed when a higher weight (γ=0.186) is put on the previous price. It is also observed that if the initial price is set below/above the equilibrium price, the price adjustment either affects the consumers or benefits the suppliers. However, the fixed delay cobweb model does not display the consumers or suppliers benefits of the price dynamics in either direction. These are unique, underlying patterns in price dynamics discovered when using a distributed delay model compared to traditional fixed delay cobweb models. Furthermore, our model challenges the traditional cobweb model’s requirement for divergence, as it is based on the weight assigned to past prices rather than the relationship between the elasticities of supply and demand, which is the determining factor in the classical model. Based on these insights, we recommend that future price adjustment models incorporate distributed delays, as they reveal more intricate price dynamics and provide a more comprehensive understanding of market behavior than fixed delay models.

Expansion high payload imperceptible steganography using parameterized multilayer EMD with clock-adjustment model

Steganography is a widely used technique for protecting data privacy. In such research, the desired attributes always include undetectability, a high embedding payload, and excellent image quality for the stego-image. However, achieving both high image quality and substantial embedding payloads often involves a trade-off. The development of an algorithm that can achieve this balance remains a key focus of these studies. Although progress has been made, there is still room for improvement in optimizing this balance between embedding capacity and image quality in current research. To address this challenge, in this study, we propose a novel steganographic method called the parameterized multilayer EMD with clock adjustment model (PMEMD–CAM). In the proposed method, we generalize the embedding and extraction process, offering a more efficient and flexible way to conceal data via the innovative concept of a CAM. In CAM, the sender can predefine the parameters to determine the number of pointers on a clock and the weight of each pointer. The pixel values in a block subsequently result in an initial clock status, and the corresponding secret data yield a target clock status. The main idea of CAM is to adjust the pointers in the clock with a minimum number of cost steps to achieve the target status for hiding the secret data. Subsequently, the authorized receiver can extract the secret data based on the clock model. In addition, a multilayer embedding strategy is applied to improve the embedding payload. Experimental results demonstrate that the proposed method achieves a high capacity of 4.754 bits per pixel (bpp) with a peak signal-to-noise ratio (exceeding 30 decibels (dB), outperforming existing schemes. Furthermore, our method exhibits resilience against various steganalysis attacks.

Long-term Glycemic Variability Predicts Adverse Outcomes in Diabetic Heart Failure with Preserved Ejection Fraction.

Previous studies have shown associations between glycemic variability (GV) and cardiovascular outcomes in patients with type 2 diabetes. However, the impact of GV on outcomes in patients with heart failure with preserved ejection fraction (HFpEF) has not been investigated. Between 2014 and 2019, we conducted a retrospective cohort analysis using the electronic medical records of a tertiary medical center in Taiwan. Diabetic patients with HFpEF were enrolled. Each individual's coefficient of variability of fasting glucose (FGCV) was determined and the FGCVs were categorized into tertiles. Multivariable Cox regression models and the Kaplan-Meier with log-rank test were used to assess the association between the FGCV and the risk of hospitalization for heart failure (HHF), atrial fibrillation (AF), cardiovascular mortality, and overall mortality. In a cohort comprising 74,835 individuals diagnosed with diabetes, a subset of 753 patients was identified with HFpEF and measurement of FGCV. The median follow-up duration 38.1 months. In the model of full adjustment, the third FGCV tertile was significantly associated with an increased risk of HHF compared to the first tertile (hazard ratio [HR] = 1.32, 95% confidence interval [CI] 1.04-1.69, p = 0.025). Likewise, the highest FGCV tertille was associated with an increased risk of death (HR 1.65, 95% CI: 1.16-2.35, p = 0.005) while it was not associated with increased of AF and cardiovascular mortality. Kaplan-Meier analyses revealed a significant association between FGCV and both HHF and overall mortality (log-rank p = 0.022 and <0.001, respectively). Our study highlights a significant association between increased GV and a higher incidence of HHF as well as an elevated overall mortality rate in individuals with diabetes and HFpEF.

Importance of risk adjusting central line-associated bloodstream infection rates in children.

Central line-associated bloodstream infection (CLABSI) is one of the most prevalent pediatric healthcare-associated infections and is used to benchmark hospital performance. Pediatric patients have increased in acuity and complexity over time. Existing approaches to risk adjustment do not control for individual patient characteristics, which are strong predictors of CLABSI risk and vary over time. Our objective was to develop a risk adjustment model for CLABSI in hospitalized children and compare observed to expected rates over time. We conducted a prospective cohort study using electronic health record data at a quaternary Children's Hospital. We included hospitalized children with central catheters. Risk factors identified from published literature were considered for inclusion in multivariable modeling based on association with CLABSI risk in bivariable analysis and expert input. We calculated observed and expected (risk model-adjusted) annual CLABSI rates. Among 16,411 patients with 520,209 line days, 633 patients experienced 796 CLABSIs. The final model included age, behavioral health condition, non-English speaking, oncology service, port catheter type, catheter dwell time, lymphatic condition, total parenteral nutrition, and number of organ systems requiring ICU level care. For every organ system receiving ICU level care the odds ratio for CLABSI was 1.24 (95% CI 1.12-1.37). Although not statistically different, observed rates were lower than expected rates for later years. Failure to adjust for patient factors, particularly acuity and complexity of disease, may miss clinically significant differences in CLABSI rates, and may lead to inaccurate interpretation of the impact of quality improvement efforts.

Social Determinants of Health and Risk-Adjusted Sepsis Mortality in the Nationwide Veterans Affairs Healthcare System.

Traditional risk prediction and risk adjustment models have focused on clinical characteristics, but accounting for social determinants of health (SDOH) and complex health conditions could improve understanding of sepsis outcomes and our ability to predict outcomes, treat patients, and assess quality of care. To evaluate the impact of SDOH and health scales in sepsis mortality risk prediction and hospital performance assessment. Observational cohort study. One hundred twenty-nine hospitals in the nationwide Veterans Affairs (VA) Healthcare System between 2017 and 2021. Veterans admitted through emergency departments with community-acquired sepsis. Individual- and community-level SDOH (race, housing instability, marital status, Area Deprivation Index [ADI], and rural residence) and two health scales (the Care Assessment Need [CAN] score and Claims-Based Frailty Index [CFI]). The primary outcome was 90-day mortality from emergency department arrival; secondary outcomes included 30-day mortality and in-hospital mortality. Among 144,889 patients admitted to the hospital with community-acquired sepsis, 139,080 were men (96.0%), median (IQR) age was 71 (64-77) years, and median (IQR) ADI was 60 (38-81). Multivariable regression models had good calibration and discrimination across models that adjusted for different sets of variables (e.g., AUROC, 0.782; Brier score, 1.33; and standardized mortality rate, 1.00). Risk-adjusted hospital performance was similar across all models. Among 129 VA hospitals, three hospitals shifted from the lowest or highest quintile of performance when comparing models that excluded SDOH to models that adjusted for all variables. Models that adjusted for ADI reported odds ratios (CI) of 1.00 (1.00-1.00), indicating that ADI does not significantly predict sepsis mortality in this cohort of patients. In patients with community-acquired sepsis, adjusting for community SDOH variables such as ADI did not improve 90-day sepsis mortality predictions in mortality models and did not substantively alter hospital performance within the VA Healthcare System. Understanding the role of SDOH in risk prediction and risk adjustment models is vital because it could prevent hospitals from being negatively evaluated for treating less advantaged patients. However, we found that in VA hospitals, the potential impact of SDOH on 90-day sepsis mortality was minimal.