Validation of an ICD code for accurately identifying emergency department patients who suffer an out-of-hospital cardiac arrest.

AIM: International classification of disease (ICD-9) code 427.5 (cardiac arrest) is utilized to identify cohorts of patients who suffer out-of-hospital cardiac arrest (OHCA), though the use of ICD codes for this purpose has never been formally validated. We sought to validate the utility of ICD-9 code 427.5 by identifying patients admitted from the emergency department (ED) after OHCA. METHODS: Adult visits to a single ED between January 2007 and July 2012 were retrospectively examined and a keyword search of the electronic medical record (EMR) was used to identify patients. Cardiac arrest was confirmed; and ICD-9 information and location of return of spontaneous circulation (ROSC) were collected. Separately, the EMR was searched for patients who received ICD-9 code 427.5. The kappa coefficient (κ) was calculated, as was the sensitivity and specificity of the code for identifying OHCA. RESULTS: The keyword search identified 1717 patients, of which 385 suffered OHCA and 333 were assigned the code 427.5. The agreement between ICD-9 code and cardiac arrest was excellent (κ = 0.895). The ICD-9 code 427.5 was both specific (99.4%) and sensitive (86.5%). Of the 52 cardiac arrests that were not identified by ICD-9 code, 33% had ROSC before arrival to the ED. When searching independently on ICD-9 code, 347 patients with ICD-9 code 427.5 were found, of which 320 were true arrests. This yielded a positive predictive value of 92% for ICD-9 code 427.5 in predicting OHCA. CONCLUSIONS: ICD-9 code 427.5 is sensitive and specific for identifying ED patients who suffer OHCA with a positive predictive value of 92%

Early hemodynamic assessment using NICOM in patients at risk of developing Sepsis immediately after emergency department triage.

BACKGROUND: One factor leading to the high mortality rate seen in sepsis is the subtle, dynamic nature of the disease, which can lead to delayed detection and under-resuscitation. This study investigated whether serial hemodynamic parameters obtained from a non-invasive cardiac output monitor (NICOM) predicts disease severity in patients at risk for sepsis. METHODS: Prospective clinical trial of the NICOM device in a convenience sample of adult ED patients at risk for sepsis who did not have obvious organ dysfunction at the time of triage. Hemodynamic data were collected immediately following triage and 2 hours after initial measurement and compared in two outcome groupings: (1) admitted vs. dehydrated, febrile, hypovolemicdischarged patients; (2) infectious vs. non-infectious sources. Receiver operator characteristic (ROC) curves were calculated to determine whether the NICOM values predict hospital admission better than a serum lactate. RESULTS: 50 patients were enrolled, 32 (64 %) were admitted to the hospital. Mean age was 49.5 (± 16.5) years and 62 % were female. There were no significant associations between changes in hemodynamic variables and patient disposition from the ED or diagnosis of infection. Lactate was significantly higher in admitted patients and those with infection (p = 0.01, p = 0.01 respectively). The area under the ROC [95 % Confidence Intervals] for lactate was 0.83 [0.64-0.92] compared to 0.59 [0.41-0.73] for cardiac output (CO), 0.68 [0.49-0.80] for cardiac index (CI), and 0.63 [0.36-0.80] for heart rate (HR) for predicting hospital admission. CONCLUSIONS: CO and CI, obtained at two separate time points, do not help with early disease severity differentiation of patients at risk for severe sepsis. Although mean HR was higher in those patients who were admitted, a serum lactate still served as a better predictor of patient admission from the ED

Early hemodynamic assessment using NICOM in patients at risk of developing Sepsis immediately after emergency department triage

BACKGROUND: One factor leading to the high mortality rate seen in sepsis is the subtle, dynamic nature of the disease, which can lead to delayed detection and under-resuscitation. This study investigated whether serial hemodynamic parameters obtained from a non-invasive cardiac output monitor (NICOM) predicts disease severity in patients at risk for sepsis. METHODS: Prospective clinical trial of the NICOM device in a convenience sample of adult ED patients at risk for sepsis who did not have obvious organ dysfunction at the time of triage. Hemodynamic data were collected immediately following triage and 2 hours after initial measurement and compared in two outcome groupings: (1) admitted vs. dehydrated, febrile, hypovolemicdischarged patients; (2) infectious vs. non-infectious sources. Receiver operator characteristic (ROC) curves were calculated to determine whether the NICOM values predict hospital admission better than a serum lactate. RESULTS: 50 patients were enrolled, 32 (64 %) were admitted to the hospital. Mean age was 49.5 (± 16.5) years and 62 % were female. There were no significant associations between changes in hemodynamic variables and patient disposition from the ED or diagnosis of infection. Lactate was significantly higher in admitted patients and those with infection (p = 0.01, p = 0.01 respectively). The area under the ROC [95 % Confidence Intervals] for lactate was 0.83 [0.64-0.92] compared to 0.59 [0.41-0.73] for cardiac output (CO), 0.68 [0.49-0.80] for cardiac index (CI), and 0.63 [0.36-0.80] for heart rate (HR) for predicting hospital admission. CONCLUSIONS: CO and CI, obtained at two separate time points, do not help with early disease severity differentiation of patients at risk for severe sepsis. Although mean HR was higher in those patients who were admitted, a serum lactate still served as a better predictor of patient admission from the ED

Gag-positive reservoir cells are susceptible to HIV-specific cytotoxic T lymphocyte mediated clearance in vitro and can be detected in vivo [corrected].

Resting CD4+T cells infected with HIV persist in the presence of suppressive anti-viral therapy (ART) and are barriers to a cure. One potential curative approach, therapeutic vaccination, is fueled by recognition of the ability of a subset of elite controllers (EC) to control virus without therapy due to robust anti-HIV immune responses. Controllers have low levels of integrated HIV DNA and low levels of replication competent virus, suggesting a small reservoir. As our recent data indicates some reservoir cells can produce HIV proteins (termed GPR cells for Gag-positive reservoir cells), we hypothesized that a fraction of HIV-expressing resting CD4+T cells could be efficiently targeted and cleared in individuals who control HIV via anti-HIV cytotoxic T lymphocytes (CTL). To test this we examined if superinfected resting CD4+T cells from EC express HIV Gag without producing infectious virus and the susceptibility of these cells to CTL. We found that resting CD4+T cells expressed HIV Gag and were cleared by autologous CD8+T cells from EC. Importantly, we found the extent of CTL clearance in our in vitro assay correlates with in vivo reservoir size and that a population of Gag expressing resting CD4+T cells exists in vivo in patients well controlled on therapy

Integrated HIV DNA is preferentially cleared over 2-LTR circles after coculture recreating the EC phenotype in vitro in the absence of spinoculation.

<p>EC resting CD4+T cells were inoculated without spinoculation, cultured for 3 days and cocultured with autologous CD8+T cells or cultured alone for 16 hours. DNA was then isolated. The fold changeis calculated by dividing the copies of the specific HIV DNA intermediate per resting CD4+T cell (i.e. integrated or 2-LTRs) cultured alone by the copies from the same samples cultured with autologous CD8+T cells. For cocultured samples the level measured was multiplied by 10, which is the dilution factor of effectors added to targets. The line represents the median and p value was calculated using the Student's t-test.</p

GPR cells can be detected <i>in vivo</i>.

<p>(A) Representative sort plots and gating strategies from a treated non-controller showing selection of resting CD4+T cells by lineage (except CD4) and activation markers stained in PE (left plot) and the selection of Gag positive and negative cells (right plot). The numbers inside the boxes represent proportion of resting CD4+T cells. Numbers outside of the boxes represent the copies of HIV DNA per cell followed by the number of events collected for each. (B) Summary data from 3 sort experiments where HIV DNA was measured in Gag negative and Gag positive sorted populations from ART-suppressed non-controllers as in (A). A paired Student's t-test was used to determine statistical significance. Lines represent median values. (C) Sort data from one individual was gated more conservatively than the 3 previous sorts for Gag positive cells. The numbers inside the boxes represent percent of resting CD4+T cells. Numbers outside of the boxed represent percent of cells positive for HIV DNA (100% =  ∼1 copy of HIV DNA per cell) followed by the number of events collected for each.</p

Superinfected resting CD4+T cells express HIV proteins without producing detectable viral spread.

<p>(A) Resting CD4+T cells were isolated from frozen PBMC by negative bead depletion and spinoculated with HIV-1_NL4-3. Cells were cultured for 3 days without stimulation in the presence saquinavir (SQV). Resting conditions refer to culture in RPMI+ 10% FCS. After 3 days cells were collected, labeled with a viability dye and activation markers, then fixed and permeabilized and stained for intracellular HIV Gag. (B) Resting CD4+T cells were gated by excluding HLA-DR, CD25 and CD69 and analyzed for the presence of intracellular Gag with or without addition of Raltegravir at the time of infection, using a reverse-transcriptase inhibitor-treated control to set the Gag positive gates. At time 0 and day 3 resting CD4+T were determined to be 99% negative for activation markers. (C) The frequency of cells expressing HIV Gag after <i>in vitro</i> infection and 3 day culture was compared among normal donors (ND, n = 6) and elite controllers (EC, n = 6). (D) One representative experiment in an EC. Total HIV DNA was measured in superinfected resting or activated cells and compared between +SQV and -SQV fractions. (E) Summary data from 4 different EC donors as in C, showing the ratio of total HIV DNA in the -SQV divided by the +SQV fraction. (Lines represent the median and p values were generated using the Students t-test.</p