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Mahmut Gümüş MD Chieh-I Chen MPH Cristina Ivanescu PhD Saadettin Kilickap MD Igor Bondarenko MD Mustafa Özgüroğlu MD Miranda Gogishvili MD Haci M. Turk MD Irfan Cicin MD James Harnett PharmD Vera Mastey MS Ulrike Naumann MS Matthew Reaney MS Gerasimos Konidaris MS Medha Sasane PhD Keri J. S. Brady PhD Siyu Li PhD Giuseppe Gullo MD Petra Rietschel MD Ahmet Sezer MD 《Cancer》2023,129(1):118-129
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Loren Saulsberry PhD Ankur Bhargava MD MPH Sharon Zeng BA Jason B. Gibbons PhD Cody Brannan MS Diane S. Lauderdale PhD Robert D. Gibbons PhD 《Health services research》2023,58(4):873-881
Objective
To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level.Data Sources and Study Setting
The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments.Study Design
The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity.Data Collection/Extraction Methods
The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments.Principal Findings
The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.Conclusions
The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes. 相似文献8.
- Children with cancer receive many medications outside the hospital administered by their caregivers.
- The study by Walsh et al. shows the number and types of medication errors in these patients. The study includes data from three different centers.
- Importantly, the study shows the types of errors that cause harm. The authors describe how the harmful errors can be prevented.
- We suggest ways these results can be used to identify which patients and families will benefit from additional attention. Providing more help at clinic and in the home may help prevent harmful medication errors in children with cancer.
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Keith B. Diamond Ivan J. Golub Asad M. Ashraf Samuel J. Swiggett Paul V. Romeo Jack Choueka 《Seminars in Arthroplasty》2022,32(1):15-22
BackgroundWhile studies have demonstrated favorable outcomes in utilization of primary total shoulder arthroplasty (TSA) for the treatment of glenohumeral osteoarthritis (OA), adverse events such as infections can still occur. Periprosthetic joint infections (PJIs) are associated with worse outcomes and patient morbidity. The purpose of this study was to: (1) compare patient demographics amongst TSA patients with and without PJIs following primary TSA; and (2) identify patient-related risk factors for PJIs following primary TSA.MethodsPatients undergoing primary TSA for the treatment of glenohumeral OA were identified using the Mariner administrative claims database by CPT code 23,472. Laterality modifiers were utilized to ensure PJIs were developing in the correct laterality as those patients undergoing primary TSA. Inclusion for the study group consisted of patients who developed PJIs within 2-years after the index procedure, whereas patients who did not develop PJIs served as the comparison cohort. Primary outcomes analyzed included patient demographics and patient-related risk factors for PJIs following primary TSA. A stepwise backwards elimination multivariate binomial logistic regression analyses was performed to determine the odds (OR) of PJIs in patients undergoing primary TSA. A P value less than .05 was considered statistically significant.ResultsThe query yielded 15,396 patients who underwent primary TSA for glenohumeral OA, of which 191 patients developed PJIs and 15,205 did not develop PJIs. The study found statistically significant differences amongst patients who did and did not develop PJIs following primary TSA with respect to age, sex, and presence of comorbid conditions. Risk factors associated with developing PJIs following primary TSA included: pathologic weight loss (OR: 2.06, P < .0001), obesity (OR: 1.56, P = .0001), male sex (OR: 1.52, P = .007), and peripheral vascular disease (OR: 1.46, P = .022).ConclusionAs the number of primary TSAs for the treatment of glenohumeral OA increase worldwide, identifying modifiable risk-factors to reduce the incidence of infection is critical. The study found various modifiable and non-modifiable risk factors associated with developing PJIs following primary TSA. This study is valuable to orthopedists in order to identify and risk-stratify patients with regard to PJI in the setting of primary TSA for OA.Level of EvidenceLevel III; Case-Control Study 相似文献