bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a risk stratification-based model for prediction of acute kidney injury in critically ill patients
Authors: Chen Yu , Feng Fang , Li Min , Chang Xueni , Wei Baohua , Dong Chenming 
Published: August 2019

Abstract
Acute kidney injury (AKI) is a complex syndrome with a variety of possible etiologies and symptoms. It is characterized by high mortality and poor recovery of renal function. The incidence and mortality rates of patients with AKI in intensive care units are extremely high. It is generally accepted that early identification and prompt treatment of AKI are essential to improve outcomes. This study aimed to develop a model based on risk stratification to identify and diagnose early stage AKI for improved prognosis in critically ill patients.
This was a single-center, retrospective, observational study. Based on relevant literature, we selected 13 risk factors (age, sex, hypertension, diabetes, coronary heart disease, chronic kidney disease, total bilirubin, emergency surgery, mechanical ventilation, sepsis, heart failure, cancer, and hypoalbuminemia) for AKI assessment using the Kidney Disease Improving Global Outcomes (KDIGO) diagnostic criteria. Univariate and multivariate analyses were used to determine risk factors for eventual entry into the predictive model. The AKI predictive model was established using binary logistic regression, and the area under the receiver operating characteristic curve (AUROC or AUC) was used to evaluate the predictive ability of the model and to determine critical values.
The AKI predictive model was established using binary logistic regression. The AUROC of the predictive model was 0.81, with a sensitivity of 69.8%, specificity of 83.4%, and positive likelihood ratio of 4.2.
A predictive model for AKI in critically ill patients was established using 5 related risk factors: heart failure, chronic kidney disease, emergency surgery, sepsis, and total bilirubin; however, the predictive ability requires validation.
Factors predicting long-term survival of patients with sepsis on arrival at the emergency department
Authors: Roh Jiyeon , Jo Eun-Jung , Eom Jung Seop , Mok Jeongha , Kim Mi Hyun , Kim Ki Uk , Park Hye-Kyung , Lee Min Ki , Yeom Seokran , Lee Kwangha 
Published: August 2019

Abstract
Predicting long-term outcomes after sepsis is important when caring for patients with this condition. The purpose of the present study was to develop models predicting long-term mortality of patients with sepsis, including septic shock.
Retrospective data from 446 patients with sepsis (60.8% men; median age, 71 years) treated at a single university-affiliated tertiary care hospital over 3 years were reviewed. Binary logistic regression was used to identify factors predicting mortality at 180 and 365 days after arrival at the emergency department. Long-term prognosis scores for the 180- and 365-day models were calculated by assigning points to variables according to their β coefficients.
The 180- and 365-day mortality rates were 40.6% and 47.8%, respectively. Multivariate analysis identified the following factors for inclusion in the 180- and 365-day models: age ≥65 years, body mass index ≤18.5 kg/m2, hemato-oncologic diseases as comorbidities, and ventilator care. Patients with scores of 0 to ≥3 had 180-day survival rates of 83.8%, 70.8%, 42.3%, and 25.0%, respectively, and 365-day survival rates of 72.1%, 64.6%, 36.2%, and 15.9%, respectively (all differences P < .001; log-rank test). The areas under the receiver operating characteristic curves of the 180- and 365-day models were 0.713 (95% confidence interval [CI] 0.668–0.756, P < .001) and 0.697 (95% CI 0.650–0.740, P < .001), respectively.
These long-term prognosis models based on baseline patient characteristics and treatments are useful for predicting the 6- and 12-month mortality rates of patients with sepsis.
High systemic immune-inflammation index predicts poor prognosis in advanced lung adenocarcinoma patients treated with EGFR-TKIs
Authors: Deng Chao , Zhang Na , Wang Yapeng , Jiang Shun , Lu Min , Huang Yan , Ma Jin’an , Hu Chunhong , Hou Tao 
Published: August 2019

Abstract
EGFR-TKIs have been widely used in the first-line treatment of NSCLC patients harboring EGFR mutations. However, the prognosis indicators are limited. In the present study, the prognostic value of systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR), and platelet to lymphocyte ratio (PLR) were assessed in EGFR-Mutant lung adenocarcinoma patients treated with first-generation EGFR-TKIs. Two hundred three patients were included in this retrospective analysis. SII was calculated as platelet counts × neutrophil counts / lymphocyte counts. Receiver operating characteristic (ROC) curve was used to evaluate the optimal cut-off value for SII, NLR, and PLR. Univariate and multivariate survival analysis were performed to identify factors correlated with PFS and OS. Applying cut-offs of ≥1066.935 (SII), ≥4.40 (NLR), and ≥182.595 (PLR), higher NLR was associated with worse Eastern Cooperative Oncology Group performance status (ECOG PS) (P = .006), and higher brain metastasis rate (P = .03), higher PLR was associated with smoking history (P = .037), and worse ECOG PS (P = .001), and higher SII groups were associated with worse ECOG PS (P = .002). In univariate analysis, higher NLR (P < .001), higher PLR (P = .002), and higher SII (P < .001) were associated with worse PFS. Higher NLR (P < .001), and higher SII (P < .001) were associated with worse OS. In multivariate analysis, NLR (HR 1.736;95%CI:1.020–2.954; P = .03), PLR (HR 1.823; 95%CI:1.059–3.137; P = .04), and SII (HR2.577; 95%CI:1.677–3.958; P < .001) were independently correlated with PFS. While only SII (HR 2.802; 95%CI:1.659–4.733; P < .001) was independently correlated with OS. The present study demonstrated that SII is an independent prognostic factor for poor survival of advanced EGFR-Mutant lung adenocarcinoma patients treated with first-generation TKIs.
Leg restlessness preceding the onset of motor symptoms of Parkinson disease
Authors: Suzuki Keisuke , Fujita Hiroaki , Watanabe Yuji , Matsubara Takeo , Kadowaki Taro , Sakuramoto Hirotaka , Hamaguchi Mai , Nozawa Narihiro , Hirata Koichi 
Published: August 2019

Abstract
Patients with Parkinson disease (PD) often show restless legs syndrome (RLS), leg motor restlessness (LMR) and other leg restlessness (OLR) related to sensorimotor symptoms.
Here, we describe 5 patients who presented with leg restlessness as an early manifestation of PD.
In case 1, the patient had leg restlessness that was not LMR or RLS and preceded the onset of motor symptoms by 1 year. In case 2, LMR preceded motor symptoms by 2 years. Case 3 had unilateral RLS symptoms on the left side of the body for 33 years. Two and a half years after the spread of RLS symptoms to the right leg with increased frequency of left-sided RLS symptoms, the patient developed PD at the age of 58 years. In cases 4 and 5, RLS symptoms preceded motor symptoms by 3 months and 1 month, respectively. All patients developed Parkinsonism within 3 years (median, 1.0 year; range 0.083–2.5 years) after initial onset or exacerbation of leg restlessness. All patients had frequent leg restlessness symptoms (6–7 days per week). In our series, the preceding leg restlessness was unilateral and confined to the dominant side of the subsequent Parkinsonism, or preceding leg restlessness was bilateral but dominant on the dominant side of the subsequent Parkinsonism.
Clinicians should be aware that late-onset leg restlessness (>50 years of age) including RLS, LMR, and OLR, particularly if frequent and asymmetrical, can be an early nonmotor manifestation of PD.
Opioid Prescribing After Opioid-related Inpatient Hospitalizations by Diagnosis
Authors: Lagisetty Pooja A. , Lin Lewei A. , Ganoczy Dara , Haffajee Rebecca L. , Iwashyna Theodore J. , Bohnert Amy S.B. 
Published: August 2019

Background:
Any opioid-related hospitalization is an indicator of opioid-related harm and should ideally trigger carefully monitored decreases in opioid prescribing after inpatient stays in many, if not most, cases. However, past studies on opioid prescribing after hospitalizations have largely been limited to overdose related visits. It is unclear whether prescribing is different for other opioid-related indications such as opioid dependence and abuse and how that may compare with hospitalizations for overdose.

Objective:
To examine opioid-prescribing patterns before and after opioid-related hospitalizations for all opioid-related indications, not limited to overdose.

Research Design:
Retrospective cohort analysis of Veterans Health Administration (VHA) administrative claims from 2011 to 2014.

Subjects:
VHA patients who were hospitalized between fiscal years 2011 and 2014 and had at least 1 prescription opioid medication filled through the VHA pharmacy before their hospitalization.

Measures:
Opioid dispensing trajectories after hospitalization by opioid-related indication (ie, opioid dependence and/or abuse vs. overdose) compared with prescribing patterns for non–opioid-related hospitalizations.

Results:
Overall, opioid dosage dropped significantly (66% for dependence/abuse, 42% for overdose, and 3% for nonopioid diagnoses; P<0.001) across all 3 categories when comparing dose 57–63 days after admission to 57–63 days before hospitalization. However, 47% of the patients remained on the same dose or increased their opioid dose at 60 days after an opioid-related hospitalization. After adjusting for covariates, patients with a primary diagnosis of dependence/abuse had higher odds of having their dose discontinued compared with those with overdose: odds ratio (OR) 2.17 (1.19–3.96). Patients with admissions for opioid dependence and/or abuse had a statistically significant higher prevalence of depression, posttraumatic stress disorder, anxiety, and substance use disorders compared with those with an opioid overdose hospitalization.

Conclusions:
Opioid prescribing and patient risk factors before and after opioid-related hospitalizations vary by indication for hospitalization. To reduce costs and morbidity associated with opioid-related hospitalizations, opioid deintensification efforts need to be tailored to indication for hospitalization.
Oxalate Content of Enteral Nutrition Formulas
Authors: Penniston Kristina L. , Palmer Eve A. , Medenwald Riley J. , Johnson Sarah N. , John Leema M. , Beshensky David J. , Saeed Ibrahim A. 
Published: August 2019

ABSTRACTObjectives:Patients requiring oral and/or enteral nutrition support, delivered via nasogastric, gastric, or intestinal routes, have a relatively high incidence of calcium oxalate (CaOx) kidney stones. Nutrition formulas are frequently made from corn and/or or soy, both of which contain ample oxalate. Excessive oxalate intake contributes to hyperoxaluria (>45 mg urine oxalate/day) and CaOx stones especially when unopposed by concomitant calcium intake, gastrointestinal malabsorption is present, and/or oxalate degrading gut bacteria are limiting or absent. Our objective was to assess the oxalate content of commonly used commercial enteral nutrition formulas.Methods:Enteral nutrition formulas were selected from the formulary at our clinical inpatient institution. Multiple samples of each were assessed for oxalate concentration with ion chromatography.Results:Results from 26 formulas revealed highly variable oxalate concentration ranging from 4 to 140 mg oxalate/L of formula. No definitive patterns for different types of formulas (eg, flavored vs unflavored, high protein vs not) were evident. Coefficients of variation for all formulas ranged from 0.68% to 43% (mean ± SD 19% ± 12%; median 18%).Conclusions:Depending on the formula and amount delivered, patients requiring nutrition support could obtain anywhere from 12 to 150 mg oxalate/day or more and are thus at risk for hyperoxaluria and CaOx stones.
Alanyl‐glutamine Heals Indomethacin‐induced Gastric Ulceration in Rats Via Antisecretory and Anti‐apoptotic Mechanisms
Authors: El‐Lekawy Ahmed M. , Abdallah Dalaal M. , El‐Abhar Hanan S. 
Published: August 2019

ABSTRACTObjectives:Alanylglutamine (AG) is a dipeptide that fuels enterocytes and has a coadjuvant role during gut healing. The current study aimed to investigate the potential ulcer‐healing effect of AG in indomethacin‐induced gastropathy.Methods:Animals (n = 10 rats/group) were randomly allocated into 5 groups. Gastric ulcerated rats were administered AG, AG + dexamethasone, or pantoprazole after indomethacin exposure.Results:Comparable to pantoprazole, AG inhibited H+‐K+ATPase pump, and elevated the pH of gastric juice. Moreover, the dipeptide increased the serum/mucosal contents of glucagon‐like peptide‐1 (GLP‐1), pS473‐Akt, and cyclin‐D1. On the contrary, AG abated serum tumor necrosis factor‐α and gastric mucosal content of pS45‐β catenin, pS9‐GSK3β, pS133‐CREB, pS536‐NF‐κB, H2O2, claudin‐1, and caspase‐3. The administration of dexamethasone before AG hampered its effect on almost all the measured parameters.Conclusions:AG confers its antiulcerogenic/antisecretory potentials by repressing the proton pump to increase the gastric juice pH via boosting p‐CREB, p‐Akt, p‐GSK‐3β, and GLP‐1. Also, it inhibits apoptosis through suppressing nuclear factor‐kappa B/tumor necrosis factor‐α/H2O2/claudin‐1 cue. This trajectory contributes to loosen the tight junction priming AG‐mediated GLP‐1/β‐catenin/cyclin‐D1 that results in pronounced increase in gastric mucosa proliferation. Therefore, the crosstalk between multiple pathways orchestrates the action of AG against gastric ulceration.
Hodgkin Lymphoma in an Adolescent With Isolated Bone Marrow and Bone Involvement: A Case Report and a Review of the Literature
Authors: Alkendi Jalila , Renzi Samuele , Manson David , Abdelhaleem Mohamed , Naqvi Ahmed , Punnett Angela 
Published: August 2019

Background:
Primary presentation of Hodgkin lymphoma (HL) with bone and/or bone marrow involvement is a rare entity. Diagnostic criteria, treatment approaches, and follow-up strategies for these patients have not been standardized.

Observation:
We report a unique case of bone and bone marrow HL in an adolescent male without lymph node involvement.

Conclusions:
It is important to keep HL in the differential diagnosis of isolated and multifocal bone lesions. Evidence is needed to define the best management of these patients.
Implementation of the Fetal Monitor Safety Nurse Role
Authors: Griggs Kellie M. , Woodard Elizabeth K. 
Published: August 2019

Abstract

Background:
The fetal monitor safety nurse role was created as a supplemental support for nurses assessing fetal heart rate tracings in response to an adverse event. An experienced labor and delivery nurse without a patient care assignment was designated to continuously assess all active fetal monitoring tracings, via an electronic display away from the main nurses' station, as an adjunct to the care and assessment of the nurse with primary responsibility for the patient.

Purpose:
The purpose of this project was to evaluate the views of nurses who served as fetal monitor safety nurses about various aspects of the role.

Methods:
Nurses who served as fetal monitor safety nurses were invited to attend a small group session where they completed a survey about the role and then received information on the importance of fetal monitoring safety. Two weeks later, they were asked to take the survey again to evaluate potential changes in viewpoints.

Results:
Thirty nurses attended small group sessions and completed the survey. Of those, 22 nurses completed the post survey 2 weeks later. There was minimal change in nurses' views of the fetal monitor safety nurse role after attending the small group sessions. Nurses expressed comfort in notifying peers about concerns related to the fetal heart rate tracing and perceived overall safety benefits; however, they felt that safe staffing measures were not in place to support the role. Concerns were expressed about a nurse being in a nondirect patient care position during times of high census and acuity.

Clinical Implications:
The fetal monitoring safety nurse may be an innovative potential solution to minimize risk of adverse events during labor that are related to accurate assessment of electronic fetal monitoring data and timely and appropriate interventions. More data are needed on improvements in fetal outcomes and adverse events potentially related to the fetal monitor safety nurse role. Budgetary support and adequate nurse staffing are required to make the role operationally feasible and safe. Valuing and seeking nurses' input as bedside experts about perinatal safety initiatives should be a part of implementing new practices.
Effects of Healthcare-Associated Infections on Length of PICU Stay and Mortality
Authors: Hatachi Takeshi , Inata Yu , Moon Kazue , Kawamura Atsushi , Yoshida Kota , Kinoshita Makie , Shimizu Yoshiyuki , Takeuchi Muneyuki 
Published: August 2019

Objectives:
To identify the effects of healthcare-associated infections on length of PICU stay and mortality.

Design:
Retrospective, single-center, observational study.

Setting:
PICU of a tertiary children’s hospital.

Patients:
Consecutive patients who stayed greater than 48 hours in the PICU between January 2013 and December 2017.

Interventions:
None.

Measurements and Main Results:
Data were retrospectively collected from medical records. We identified occurrences of common healthcare-associated infections, including bloodstream infection, pneumonia, and urinary tract infection, defined according to the 2008 definitions of the Centers for Disease Control and Prevention and National Healthcare Safety Network. We assessed the effects of each healthcare-associated infection on length of PICU stay and PICU mortality using multivariable analysis. Among 1,622 admissions with a PICU stay greater than 48 hours, the median age was 299 days and male patients comprised 51% of admissions. The primary diagnostic categories were cardiovascular (58% of admissions), respiratory (21%), gastrointestinal (8%), and neurologic/muscular (6%). The median length of PICU stay was 6 days, and the PICU mortality rate was 2.5%. A total of 167 healthcare-associated infections were identified, including 67 bloodstream infections (40%), 43 pneumonias (26%), and 57 urinary tract infections (34%). There were 152 admissions with at least one healthcare-associated infection (9.4% of admissions with a stay > 48 hr). On multivariable analysis, although each healthcare-associated infection was not significantly associated with mortality, bloodstream infection was associated with an extra length of PICU stay of 10.2 days (95% CI, 7.9–12.6 d), pneumonia 14.2 days (11.3–17.2 d), and urinary tract infection 6.5 days (4.0–9.0 d). Accordingly, 9.7% of patient-days were due to these three healthcare-associated infections among patients with a stay greater than 48 hours.

Conclusions:
Although healthcare-associated infections were not associated with PICU mortality, they were associated with extra length of PICU stay. As 9.7% of patient-days were due to healthcare-associated infections, robust prevention efforts are warranted.
Are Nonprofit Hospitals Addressing the Most Critical Community Health Needs That They Identify in Their Community Health Needs Assessments?
Authors: Franz Berkeley , Cronin Cory E. , Singh Simone 
Published: August 2019

Context:
Virtually all nonprofit hospitals are in compliance with the Affordable Care Act's new Community Health Needs Assessments requirements.

Objective:
To assess what needs have emerged in the Community Health Needs Assessments hospitals complete nationally, the degree to which identified needs reflect the most pressing community health issues, and the extent to which hospitals address identified needs.

Design:
Using both bivariate and logistic regressions, we analyzed the Community Health Needs Assessments and implementation strategies of nonprofit hospitals to determine whether identified needs overlapped with county health-ranking indicators of need and whether institutional or community-level factors predicted hospital willingness to address identified needs.

Participants:
We included a 20% random sample of US nonprofit hospitals (n = 496).

Main Outcome Measures:
Our main outcome measures were whether nonprofit hospitals addressed each of the most common needs.

Results:
Mental health, access to care, obesity, substance abuse, diabetes, cancer, and the social determinants of health were the most commonly identified needs across the sample. The rate at which hospitals chose to address each of these needs in their implementation strategies, however, varied considerably, ranging from 56% (cancer) to 85% (obesity). We found that several institutional and community characteristics predicted hospital willingness to address each need; whether the community ranked a need as number 1 was a better predictor of hospital investment than the severity of the need, as measured by county health-rankings data.

Conclusions:
These findings may help inform local, state, and federal policy makers as they consider interventions aimed at encouraging hospitals to invest in improving the health of their communities.
Identifying Novel Predictors of State Legislative Action to Address Obesity
Authors: Arons Abigail , Pomeranz Jennifer , Hamad Rita 
Published: August 2019

Objective:
There is wide variation in the number and types of obesity policies enacted across states, and prior studies suggest that partisan factors may not fully explain this variation. In this exploratory analysis, we examined the association of a broad array of state-level factors with the number and types of obesity policies across states.

Design:
We analyzed 32 predictor variables across 7 categories of state-level characteristics. We abstracted data from 1652 state obesity policies introduced during 2009-2014. We used multilevel regression models and principal component analysis to examine the association between state-level characteristics and policy outcomes.

Main Outcome Measures:
Our outcome measures included whether bills involved topics that were public health–oriented or business interest–oriented, whether bills were enacted into law, and the number of introduced bills and enacted laws per state.

Results:
Numerous state-level characteristics were associated with obesity-related bill introduction and law enactment, and different state characteristics were associated with public health–oriented versus business interest–oriented policies. For example, state-level demographics, economic factors, policy environment, public programs, and the prevalence of obesity's downstream consequences were associated with the number of public health laws whereas obesity prevalence and policy environment were associated with the number of business interest laws.

Conclusions:
Our results support the hypothesis that a variety of factors contribute to a complex state obesity policymaking environment, highlighting the need for future research to disentangle these key predictors.