Attributable Cost of Clostridium difficile Infection in Pediatric Patients

2017 ◽  
Vol 38 (12) ◽  
pp. 1472-1477 ◽  
Author(s):  
Preeti Mehrotra ◽  
Jisun Jang ◽  
Courtney Gidengil ◽  
Thomas J. Sandora
Keyword(s):  
Logistic Regression ◽  
Clostridium Difficile ◽  
Propensity Score ◽  
Regression Model ◽  
Generalized Linear Model ◽  
Logistic Regression Model ◽  
Propensity Scores ◽  
Healthcare Research ◽  
Design And Methods ◽  
Inpatient Database

OBJECTIVESThe attributable cost of Clostridium difficile infection (CDI) in children is unknown. We sought to determine a national estimate of attributable cost and length of stay (LOS) of CDI occurring during hospitalization in children.DESIGN AND METHODSWe analyzed discharge records of patients between 2 and 18 years of age from the Agency for Healthcare Research and Quality (AHRQ) Kids’ Inpatient Database. We created a logistic regression model to predict CDI during hospitalization based on demographic and clinical characteristics. Predicted probabilities from the logistic regression model were then used as propensity scores to match 1:2 CDI to non-CDI cases. Charges were converted to costs and compared between patients with CDI and propensity-score–matched controls. In a sensitivity analysis, we adjusted for LOS as a confounder by including it in both the propensity score and a generalized linear model predicting cost.RESULTSWe identified 8,527 pediatric hospitalizations (0.53%) with a diagnosis of CDI and 1,597,513 discharges without CDI. In our matched cohorts, the attributable cost of CDI occurring during a hospitalization ranged from $1,917 to $8,317, depending on whether model was adjusted for LOS. When not adjusting for LOS, CDI-associated hospitalizations cost 1.6 times more than non-CDI associated hospitalizations. Attributable LOS of CDI was approximately 4 days.CONCLUSIONSClostridium difficile infection in hospitalized children is associated with an economic burden similar to adult estimates. This finding supports a continued focus on preventing CDI in children as a priority. Pediatric CDI cost analyses should account for LOS as an important confounder of cost.Infect Control Hosp Epidemiol 2017;38:1472–1477

scholarly journals Effect of fluid administration on scene to traffic accident patients by EMS personnel: a propensity score-matched study using population-based ambulance records and nationwide trauma registry in Japan

2021 ◽  
Author(s):  
Yusuke Katayama ◽  
Tetsuhisa Kitamura ◽  
Kosuke Kiyohara ◽  
Kenichiro Ishida ◽  
Tomoya Hirose ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Propensity Score ◽  
Hospital Mortality ◽  
Regression Model ◽  
Traffic Accident ◽  
Logistic Regression Model ◽  
Cardiopulmonary Arrest ◽  
Population Based ◽  
Fluid Administration ◽  
Secondary Outcome

Abstract Purpose The aim of this study was to assess the effect of fluid administration by emergency life-saving technicians (ELST) on the prognosis of traffic accident patients by using a propensity score (PS)-matching method. Methods The study included traffic accident patients registered in the JTDB database from January 2016 to December 2017. The main outcome was hospital mortality, and the secondary outcome was cardiopulmonary arrest on hospital arrival (CPAOA). To reduce potential confounding effects in the comparisons between two groups, we estimated a propensity score (PS) by fitting a logistic regression model that was adjusted for 17 variables before the implementation of fluid administration by ELST at the scene. Results During the study period, 10,908 traffic accident patients were registered in the JTDB database, and we included 3502 patients in this study. Of these patients, 142 were administered fluid by ELST and 3360 were not administered fluid by ELST. After PS matching, 141 patients were selected from each group. In the PS-matched model, fluid administration by ELST at the scene was not associated with discharge to death (crude OR: 0.859 [95% CI, 0.500–1.475]; p = 0.582). However, the fluid group showed statistically better outcome for CPAOA than the no fluid group in the multiple logistic regression model (adjusted OR: 0.231 [95% CI, 0.055–0.967]; p = 0.045). Conclusion In this study, fluid administration to traffic accident patients by ELST was associated not with hospital mortality but with a lower proportion of CPAOA.

scholarly journals The effect of ICP monitoring in severe traumatic brain injury: a propensity score–weighted and adjusted regression approach

2019 ◽  
Vol 131 (6) ◽  
pp. 1896-1904 ◽  
Author(s):  
Pål Rønning ◽  
Eirik Helseth ◽  
Nils-Oddvar Skaga ◽  
Knut Stavem ◽  
Iver A. Langmoen
Keyword(s):  
Traumatic Brain Injury ◽  
Logistic Regression ◽  
Brain Injury ◽  
Propensity Score ◽  
Regression Model ◽  
Severe Traumatic Brain Injury ◽  
Logistic Regression Model ◽  
Icp Monitoring ◽  
Brain Trauma Foundation ◽  
The Impact

OBJECTIVEThe use of intracranial pressure (ICP) monitoring has been postulated to be beneficial in patients with severe traumatic brain injury (TBI), although studies investigating this hypothesis have reported conflicting results. The objective of this study was to evaluate the effect of inserting an ICP monitor on survival in patients with severe TBI.METHODSThe Oslo University Hospital trauma registry was searched for the records of all patients admitted between January 1, 2002, and December 31, 2013, who fulfilled the Brain Trauma Foundation criteria for intracranial hypertension and who survived at least 24 hours after admission. The impact of ICP monitoring was investigated using both a logistic regression model and a multiple imputed, propensity score–weighted logistic regression analysis.RESULTSThe study involved 1327 patients, in which 757 patients had an ICP monitor implanted. The use of ICP monitors significantly increased in the study period (p < 0.01). The 30-day overall mortality was 24.3% (322 patients), divided into 35.1% (200 patients, 95% confidence interval [CI] 31.3%–39.1%) in the group without an ICP monitor and 16.1% (122 patients, 95% CI 13.6%–18.9%) in the group with an ICP monitor. The impact of ICP monitors on 30-day mortality was found to be beneficial both in the complete case analysis logistic regression model (odds ratio [OR] 0.23, 95% CI 0.16–0.33) and in the adjusted, aggregated, propensity score–weighted imputed data sets (OR 0.22, 95% CI 0.15–0.35; both p < 0.001). The sensitivity analysis indicated that the findings are robust to unmeasured confounders.CONCLUSIONSThe authors found that the use of an ICP monitor is significantly associated with improved survival in patients with severe head injury.

Predicting Clostridium difficile Toxin in Hospitalized Patients With Antibiotic-Associated Diarrhea

2007 ◽  
Vol 28 (4) ◽  
pp. 377-381 ◽  
Author(s):  
Nir Peled ◽  
Silvio Pitlik ◽  
Zmira Samra ◽  
Arkadi Kazakov ◽  
Yoram Bloch ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clostridium Difficile ◽  
Positive Result ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Hospitalized Patients ◽  
Watery Diarrhea ◽  
Toxin A ◽  
Antibiotic Associated Diarrhea ◽  
Assay Result

Objective.Clostridium difficile infection is implicated in 20%-30% of cases of antibiotic-associated diarrhea. Studying hospitalized patients who received antibiotic therapy and developed diarrhea, our objective was to compare the clinical characteristics of patients who developed C. difficile–associated diarrhea (CDAD) with those of patients with a negative result of a stool assay for C. difficile toxin.Methods.A prospective study was done with a cohort of 217 hospitalized patients who had received antibiotics and developed diarrhea. Patients with CDAD were defined as patients who had diarrhea and a positive result for C. difficile toxin A/B by an enzyme immunoassay of stool. The variables that yielded a significant difference on univariate analysis between patients with a positive assay result and patients with a negative assay result were entered into a logistic regression model for prediction of C. difficile toxin.Setting.A 900-bed tertiary care medical center.Results.Of 217 patients, 52 (24%) had a positive result of assay for C. difficile toxin A/B in their stool. The logistic regression model included impaired functional capacity, watery diarrhea, use of a proton pump inhibitor, use of a histamine receptor blocker, leukocytosis, and hypoalbuminemia. The area under the receiver operating characteristic curve for the model as a predictor of a positive result for the stool toxin assay was 0.896 (95% confidence interval, 0.661-1.000; P<.001), with 95% specificity and 68% sensitivity.Conclusions.Our results may help clinicians to predict the risk of CDAD in hospitalized patients with antibiotic-associated diarrhea, to guide careful, specific empirical therapy, and to direct early attention to infection control issues.

scholarly journals Predicting the Risk for Hospital-Onset Clostridium difficile Infection (HO-CDI) at the Time of Inpatient Admission: HO-CDI Risk Score

2015 ◽  
Vol 36 (6) ◽  
pp. 695-701 ◽  
Author(s):  
Ying P. Tabak ◽  
Richard S. Johannes ◽  
Xiaowu Sun ◽  
Carlos M. Nunez ◽  
L. Clifford McDonald
Keyword(s):  
Logistic Regression ◽  
Clostridium Difficile ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Predictive Ability ◽  
Risk Identification ◽  
Inpatient Admission ◽  
Risk Scores ◽  
Retrospective Data Analysis ◽  
Time Of Admission

OBJECTIVETo predict the likelihood of hospital-onset Clostridium difficile infection (HO-CDI) based on patient clinical presentations at admissionDESIGNRetrospective data analysisSETTINGSix US acute care hospitalsPATIENTSAdult inpatientsMETHODSWe used clinical data collected at the time of admission in electronic health record (EHR) systems to develop and validate a HO-CDI predictive model. The outcome measure was HO-CDI cases identified by a nonduplicate positive C. difficile toxin assay result with stool specimens collected >48 hours after inpatient admission. We fit a logistic regression model to predict the risk of HO-CDI. We validated the model using 1,000 bootstrap simulations.RESULTSAmong 78,080 adult admissions, 323 HO-CDI cases were identified (ie, a rate of 4.1 per 1,000 admissions). The logistic regression model yielded 14 independent predictors, including hospital community onset CDI pressure, patient age ≥65, previous healthcare exposures, CDI in previous admission, admission to the intensive care unit, albumin ≤3 g/dL, creatinine >2.0 mg/dL, bands >32%, platelets ≤150 or >420 109/L, and white blood cell count >11,000 mm3. The model had a c-statistic of 0.78 (95% confidence interval [CI], 0.76–0.81) with good calibration. Among 79% of patients with risk scores of 0–7, 19 HO-CDIs occurred per 10,000 admissions; for patients with risk scores >20, 623 HO-CDIs occurred per 10,000 admissions (P<.0001).CONCLUSIONUsing clinical parameters available at the time of admission, this HO-CDI model demonstrated good predictive ability, and it may have utility as an early risk identification tool for HO-CDI preventive interventions and outcome comparisons.Infect Control Hosp Epidemiol 2015;00(0):1–7

Severe contralateral carotid stenosis or occlusion drive 30-day risk after carotid endarterectomy

Vascular ◽  
2021 ◽  
pp. 170853812199361
Author(s):  
Wenyan Zhao ◽  
Faliang Gao ◽  
Cheng Wu ◽  
Deqing Peng ◽  
Xiao Jin ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Propensity Score ◽  
Adverse Events ◽  
Regression Model ◽  
Carotid Endarterectomy ◽  
Carotid Stenosis ◽  
Logistic Regression Model ◽  
Primary Study ◽  
Luminal Narrowing ◽  
Major Adverse Events

Objectives The significant effects on the treatment of severe carotid stenosis by carotid endarterectomy have been widely recognized. However, it is controversial whether patients with severe contralateral carotid stenosis or occlusion (SCSO) can benefit from carotid endarterectomy surgery. This study aimed to estimate the SCSO effects on early outcomes after carotid endarterectomy with selective shunting. Methods Between August 2011 and October 2019, a total of 617 patients who underwent carotid endarterectomy with selective shunting were analyzed. SCSO was defined as >70% luminal narrowing of the contralateral extracranial carotid stenosis or occlusion. Of these patients, 116 were categorized into an SCSO group while the rest were assigned to the non-SCSO group. Primary study outcomes were the occurrence of major adverse events, defined as stroke, all-cause mortality, and myocardial infarction during the perioperative period after carotid endarterectomy. Traditional multivariable logistic regression model and logistic regression model adjusted for propensity scores were used to estimate the SCSO effects on primary outcomes. Interaction and stratified analyses were conducted according to age, sex, comorbidities (hypertension, diabetes), preoperative neurological deficit, preoperative symptoms, and shunt use. Results Mean age was 68.5 ± 9.2 years (86.1% men). Overall major adverse events rate within 30 days was 2.5%. Major adverse events rates in SCSO and non-SCSO groups were 9.5% and 1.6%, respectively. This difference was statistically significant ( p < 0.001). In multivariable regression analysis, patients with SCSO had a higher risk of major adverse events (non-SCSO vs. SCSO: aOR 5.05 [95% CI, 1.78–14.55]). In 342 propensity score matched patients, results were consistent (propensity score: aOR, 3.78 [95% CI, 1.13–12.64]). Conclusions SCSO is an independent predictor of 30-day major adverse events. Whether these patients with SCSO are suitable for carotid endarterectomy should be carefully considered.

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