Abstract 109: Patients with Diabetes Have Decreased Survivability with Good Neurological Outcomes After Out-of-Hospital Cardiac Arrest

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Beatrice Dayea Jang ◽  
Sang Do Shin ◽  
William McClellan ◽  
Bryan McNally
Keyword(s):  
Heart Disease ◽  
Medical Record ◽  
Cerebral Performance Category ◽  
Medical Record Review ◽  
Multivariate Logistic Regression Model ◽  
P Value ◽  
Neurological Outcomes ◽  
Brain Recovery ◽  
History Of ◽  
Record Review

Objectives: This study aims to provide a scientific evidence of the association between diabetes and the probability of OHCA survival with good neurological outcomes. Methods: Korean registry on patients survived to admission after emergency medical services (EMS)-assessed OHCA with cardiac etiology with known diabetes statuses (2009 to 2012) was used. We excluded patients without available hospital outcomes or diabetes. Diabetes was defined when the patients had history of treatment or diagnosis or positive result at laboratory test during hospital stay. Outcomes were survival to discharge with good brain recovery measured by medical record review by medical record review experts using cerebral performance category 1 or 2. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a multivariate logistic regression model adjusting for individual, Utstein, post-resuscitation factors, and comorbidities. Interaction model between diabetes and gender and heart disease were also analyzed. Results: Total 7463 patients including diabetes 1,952 (26.2%), non-diabetes 4,129 (55.3%), and unknown diabetes 1,382 (18.5%) were finally analyzed. Survival to discharge with good brain recovery was 17.7% in non-diabetes, 9.7% in diabetes 16.2% in unknown-diabetes, respectively (p<0.001). Crude OR (95% CI) was 0.50 (0.42-0.59) in diabetes and 0.89 (0.76-1.05) in unknown-diabetes comparing with non-diabetes. Adjusted OR (95% CI) was 0.78 (0.61-0.98) in diabetes and 1.07 (0.75-1.53) in unknown-diabetes comparing with non-diabetes. The adjusted OR measuring the effect of diabetes on survival with good neurological outcomes for male with history of heart disease was 0.32 (0.22-0.48, p-value <0.0001), for male without history of heart disease was 0.55 (0.34-0.89, p-value <0.0001), for female with history of heart disease was 0.60 (0.48-0.76, p-value 0.0152), and for female without history of heart disease was 1.03 (0.71-1.47, p-value 0.8919). Conclusion: This study provides evidence of significant associations of diabetes and decreased OHCA survivability with good neurological outcomes where the association is greater in male and patients with heart disease.

Investigation Of a Cluster Of Inhibitors Among Previously Treated Hemophilia Patients (PTPs) At A Single Hospital In The United States

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1114-1114
Author(s):  
Nafisa Ghaji ◽  
Nigel S Key ◽  
Connie H. Miller ◽  
Brenda Nielsen ◽  
Tyler W. Buckner ◽  
...  
Keyword(s):  
Risk Factors ◽  
Medical Record ◽  
Hospital Admissions ◽  
Medical Record Review ◽  
Odds Ratios ◽  
Period 2 ◽  
History Of ◽  
Time Periods ◽  
Hospital Practices ◽  
Record Review

Abstract Introduction Inhibitors are considered to be the most serious complication of clotting factor concentrate (CFC) therapy in hemophilia. The incidence of inhibitors in PTPs with severe hemophilia is very low (∼ 1 per 1,000 patient years). Four cases of PTP inhibitors that developed during hospital admissions were observed at the University of North Carolina over a 14-month period during 2011 – 2012. Due to concern about the possible role of the CFC used during hospitalization, further investigation by the CDC was requested. Methods A review of hemophilia-related hospital practices and procedures, along with a medical record review of admissions from January 2008 – November 2012 was conducted to: 1) compare inhibitor incidence trends in the time periods before and after January 2011; and 2) assess patient risk factors and evaluate hospital practices relative to inhibitor occurrence. A case was a person who developed an inhibitor during a hospital admission and non-cases were inpatients with no history of inhibitor development. The prevalence of inhibitor risk factors were compared between cases and non-cases and across time periods. Unadjusted odds ratios were used to compare the prevalence of exposures between cases and non-cases and comparisons of means of continuous risk factors used parametric and non-parametric tests as appropriate. Results A check of the FDA's Adverse Event Reporting System (FAERS) revealed no identified problems of the CFC in question. The medical record review revealed 134 admissions in 49 patients (59 in period 1 and 75 in period 2) during the 5-year period (see Figure). No other cases were found during the review; however, one of the index cases was found to have developed the inhibitor as an outpatient leaving 3 cases and 45 non-cases for study. The cases ranged in age from 23 – 69 years. One had severe and one had moderate hemophilia A, while the third case had combined factor V-VIII deficiency with FV and FVIII levels of 7% and 10%, respectively. Compared to non-cases, cases had elevated odds of: an infection (OR, 95% CL=4.4, 0.3–53), continuous factor infusion (CI) (4.2, 0.04–6.4), at least one non-surgical procedure (3.9, 0.1–80.5), and used the only hospital-available CFC (2.7, 0.1–73) during the admission and a product switch prior to admission (3.5, 0.1–105) and a family history of hemophilia (2.4, 0.1–51). In addition, cases had more hospital admissions (mean 6.6 vs. 2.4, p = 0.002) and more total hospital days (mean 39.6 days vs. 14.8 days. p = 0.05) than non-cases. Finally, cases received a greater total dose of CFC than non-cases (mean 101 IU/kg vs. 69 IU/kg, p = 0.003) during admission. Two hospital practices changed in period two: 1) the method of preparation and administration of CI involved less diluent and, therefore, a more concentrated infusion solution; and 2) the hospital pharmacy stocked only one brand of CFC in period 2 whereas several brands were available in period 1. The latter change increased the proportion of inpatients using a different product than that used as an outpatient (i.e., product switch) during period 2. Compared to inpatients admitted during period 1, those in period 2 were: more likely to receive the only available CFC and to have a product switch during the admission (p < 0.001). No difference between time periods was seen in the proportion of patients administered CI (58.8% vs. 56.9%) or who were tested for an inhibitor during admission (25% vs. 22%). Conclusions The investigation results support an increase in incidence of inhibitors among inpatients during period 2 compared to period 1, however, the number of cases was small. Nonetheless, because inhibitors are rare in PTPs, the occurrence of 3 cases in a 14-month period after a 3-year time span with no cases is highly suggestive of an actual increase in occurrence. The apparent increase was unlikely due to enhanced surveillance since rates of inhibitor testing during the two time periods were similar. While the odds ratios for some of the risk factors were elevated, the confidence limits were wide indicative of the lack of study power. Although there was no clear indication of a preventable inciting factor and more investigation is needed, the investigation revealed that this inhibitor cluster occurred in patients who had many complications that required lengthy hospitalizations and intense treatment with CFCs, contributing factors that should be considered in future management of hemophilia patients. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Validation of ICD-10-CM codes for injuries complicating pregnancy, childbirth and the puerperium: a medical record review

2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i9-i12
Author(s):  
Anna Hansen ◽  
Dana Quesinberry ◽  
Peter Akpunonu ◽  
Julia Martin ◽  
Svetla Slavova
Keyword(s):  
Emergency Department ◽  
Medical Record ◽  
International Classification Of Diseases ◽  
Medical Record Review ◽  
Full Sample ◽  
Emergency Department Data ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Record Review

IntroductionThe purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.MethodsA medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an abstraction form to collect information on documented presence of injury and PCP complications. The study estimated the PPVs and the 95% CIs of O9A.2-O9A.4 codes for (1) capturing injuries and (2) capturing injuries complicating PCP.ResultsThe estimated PPV for the codes O9A.2-O9A.4 to identify injury in the full sample was 79.6% (95% CI 73.3% to 85.9%) and the PPV for capturing injuries complicating PCP was 72.0% (95% CI 65.0% to 79.0%). The estimated PPV for an inpatient principal diagnosis O9A.2-O9A.4 to capture injuries was 90.7% (95% CI 82.0% to 99.4%) and the PPV for capturing injuries complicating PCP was 88.4% (95% CI 78.4% to 98.4%). The estimated PPV for any mention of O9A.2-O9A.4 in emergency department data to capture injuries was 95.2% (95% CI 90.6% to 99.9%) and the PPV for capturing injuries complicating PCP was 81.0% (95% CI 72.4% to 89.5%).DiscussionThe O9A.2-O9A.4 codes captured high percentage true injury cases among pregnant and puerperal women.

Rapid Estimation of Hospitalization Charges From a Brief Medical Record Review

Medical Care ◽  
1986 ◽  
Vol 24 (10) ◽  
pp. 961-966 ◽  
Author(s):  
Walter A. Kukull ◽  
Thomas D. Koepsell ◽  
Douglas A. Conrad ◽  
Virginia Immanuel ◽  
Jan Prodzinski ◽  
...  
Keyword(s):  
Medical Record ◽  
Medical Record Review ◽  
Rapid Estimation ◽  
Record Review
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