John Dziodzio

Neurologic Outcomes and Postresuscitation Care of Patients With Myoclonus Following Cardiac Arrest.

Objectives: To evaluate the outcomes of cardiac arrest survivors with myoclonus receiving modern postresuscitation care. Design: Retrospective review of registry data. Setting: Cardiac arrest receiving centers in Europe and the United States from 2002 to 2012. Patients: Two thousand five hundred thirty-two cardiac arrest survivors 18 years or older enrolled in the International Cardiac Arrest Registry. Interventions: None. Measurements and Main Results: Eighty-eight percent of patients underwent therapeutic hypothermia and 471 (18%) exhibited myoclonus. Patients with myoclonus had longer time to professional cardiopulmonary resuscitation (8.6 vs 7.0 min; p < 0.001) and total ischemic time (25.6 vs 22.3 min; p < 0.001) and less often presented with ventricular tachycardia/ventricular fibrillation, a witnessed arrest, or had bystander cardiopulmonary resuscitation. Electroencephalography demonstrated myoclonus with epileptiform activity in 209 of 374 (55%), including status epilepticus in 102 of 374 (27%). Good outcome (Cerebral Performance Category 1–2) at hospital discharge was noted in 9% of patients with myoclonus, less frequently in myoclonus with epileptiform activity (2% vs 15%; p < 0.001). Patients with myoclonus with good outcome were younger (53.7 vs 62.7 yr; p < 0.001), had more ventricular tachycardia/ventricular fibrillation (81% vs 46%; p < 0.001), shorter ischemic time (18.9 vs 26.4 min; p = 0.003), more witnessed arrests (91% vs 77%; p = 0.02), and fewer “do-not-resuscitate” orders (7% vs 78%; p < 0.001). Life support was withdrawn in 330 of 427 patients (78%) with myoclonus and poor outcome, due to neurological futility in 293 of 330 (89%), at 5 days (3–8 d) after resuscitation. With myoclonus and good outcome, median ICU length of stay was 8 days (5–11 d) and hospital length of stay was 14.5 days (9–22 d). Conclusions: Nine percent of cardiac arrest survivors with myoclonus after cardiac arrest had good functional outcomes, usually in patients without associated epileptiform activity and after prolonged hospitalization. Deaths occurred early and primarily after withdrawal of life support. It is uncertain whether prolonged care would yield a higher percentage of good outcomes, but myoclonus of itself should not be considered a sign of futility.

Prophylactic antibiotics are associated with a lower incidence of pneumonia in cardiac arrest survivors treated with targeted temperature management

INTRODUCTION Prophylactic antibiotics (PRO) reduce the incidence of early-onset pneumonia in comatose patients with structural brain injury, but have not been examined in cardiac arrest survivors undergoing targeted temperature management (TTM). We investigated the effect of PRO on the development of pneumonia in that population. METHODS We conducted a retrospective cohort study comparing patients treated with PRO to those not receiving PRO (no-PRO) using Northern Hypothermia Network registry data. Cardiac arrest survivors ≥ 18 years of age with a GCS<8 at hospital admission and treated with TTM at 32-34 °C were enrolled in the registry. Differences were analyzed in univariate analyses and with logistic regression models to evaluate independent associations of clinical factors with incidence of pneumonia and good functional outcome. RESULTS 416 of 1240 patients (33.5%) received PRO. Groups were similar in age, gender, arrest location, initial rhythm, and time from collapse to return of spontaneous circulation. PRO patients had less pneumonia (12.6% vs. 54.9%, p < 0.001) and less sepsis (1.2 vs. 5.7%, p < 0.001) compared to no-PRO patients. ICU length of stay (98 vs. 100 h, p = 0.2) and incidence of a good functional outcome (41.1 vs. 36.6%, p = 0.19) were similar between groups. Backwards stepwise logistic regression demonstrated PRO were independently associated with a lower incidence of pneumonia (OR 0.09, 95% 0.06-0.14, p < 0.001) and a similar incidence of good functional outcome. CONCLUSIONS Prophylactic antibiotics were associated with a reduced incidence of pneumonia but a similar rate of good functional outcome.

Feasibility of bispectral index monitoring to guide early post-resuscitation cardiac arrest triage ☆ ☆☆

INTRODUCTION Triage after resuscitation from cardiac arrest is hindered by reliable early estimation of brain injury. We evaluated the performance of a triage model based on early bispectral index (BIS) findings and cardiac risk classes. METHODS Retrospective evaluation of serial patients resuscitated from cardiac arrest, unable to follow commands, and undergoing hypothermia. Patients were assigned to a cardiac risk group: STEMI, VT/VF shock, VT/VF no shock, or PEA/asystole, and to a neurological dysfunction group, based on the BIS score following first neuromuscular blockade (BISi), and classified as BISi>20, BISi 10-20, or BISi<10. Cause of death was described as neurological or circulatory. RESULTS BISi in 171 patients was measured at 267(±177)min after resuscitation and 35(±1.7)°C. BISi<10 suffered 82% neurological-cause and 91% overall mortality, BISi 10-20 35% neurological and 55% overall mortality, and BISi>20 12% neurological and 36% overall mortality. 33 patients presented with STEMI, 15 VT/VF-shock, 41 VT/VF-no shock, and 80 PEA/asystole. Among BISi>20 patients, 75% with STEMI underwent urgent cardiac catheterization (cath) and 94% had good outcome. When BISi>20 with VT/VF and shock, urgent cath was infrequent (33%), and 4 deaths (44%) were uniformly of circulatory etiology. Of 56 VT/VF patients without STEMI, 24 were BISi>20 but did not undergo urgent cath - 5(20.8%) of these had circulatory-etiology death. Circulatory-etiology death also occurred in 26.5% BIS>20 patients with PEA/asystole. When BISi<10, a neurological etiology death dominated independent of cardiac risk group. CONCLUSIONS Neurocardiac triage based on very early processed EEG (BIS) is feasible, and may identify patients appropriate for individualized post-resuscitation care. This and other triage models warrant further study.

Valproate for agitation in critically ill patients: A retrospective study

Purpose: The purpose was to describe the use of valproate therapy for agitation in critically ill patients, examine its safety, and describe its relationship with agitation and delirium. Materials and methods: This retrospective cohort study evaluated critically ill adults treated with valproate for agitation from December 2012 through February 2015. Information on valproate prescribing practices and safety was collected. Incidence of agitation, delirium, and concomitant psychoactive medication use was compared between valproate day 1 and valproate day 3. Concomitant psychoactive medication use was analyzed using mixed models. Results: Fifty‐three patients were evaluated. The median day of valproate therapy initiation was ICU day 7, and it was continued for a median of 7 days. The median maintenance dose was 1500 mg/d (23 mg/kg/d). The incidence of agitation (96% vs 61%, P < .0001) and delirium (68% vs 49%, P = .012) significantly decreased by valproate day 3. Treatment with opioids (77% vs 65%, P = .02) and dexmedetomidine (47% vs 24%, P = .004) also decreased. In mixed models analyses, valproate therapy was associated with reduced fentanyl equivalents (−185 &mgr;g/d, P = .0003) and lorazepam equivalents (−2.1 mg/d, P = .0004). Hyperammonemia (19%) and thrombocytopenia (13%) were the most commonly observed adverse effects. Conclusions: Valproate therapy was associated with a reduction in agitation, delirium, and concomitant psychoactive medication use within 48 hours of initiation.

Derivation and Validation of the CREST Model for Very Early Prediction of Circulatory Etiology Death in Patients Without ST-Segment–Elevation Myocardial Infarction After Cardiac Arrest

Background: No practical tool quantitates the risk of circulatory-etiology death (CED) immediately after successful cardiopulmonary resuscitation in patients without ST-segment–elevation myocardial infarction. We developed and validated a prediction model to rapidly determine that risk and facilitate triage to individualized treatment pathways. Methods: With the use of INTCAR (International Cardiac Arrest Registry), an 87-question data set representing 44 centers in the United States and Europe, patients were classified as having had CED or a combined end point of neurological-etiology death or survival. Demographics and clinical factors were modeled in a derivation cohort, and backward stepwise logistic regression was used to identify factors independently associated with CED. We demonstrated model performance using area under the curve and the Hosmer-Lemeshow test in the derivation and validation cohorts, and assigned a simplified point-scoring system. Results: Among 638 patients in the derivation cohort, 121 (18.9%) had CED. The final model included preexisting coronary artery disease (odds ratio [OR], 2.86; confidence interval [CI], 1.83–4.49; P⩽0.001), nonshockable rhythm (OR, 1.75; CI, 1.10–2.77; P=0.017), initial ejection fraction<30% (OR, 2.11; CI, 1.32–3.37; P=0.002), shock at presentation (OR, 2.27; CI, 1.42–3.62; P<0.001), and ischemic time >25 minutes (OR, 1.42; CI, 0.90–2.23; P=0.13). The derivation model area under the curve was 0.73, and Hosmer-Lemeshow test P=0.47. Outcomes were similar in the 318-patient validation cohort (area under the curve 0.68, Hosmer-Lemeshow test P=0.41). When assigned a point for each associated factor in the derivation model, the average predicted versus observed probability of CED with a CREST score (coronary artery disease, initial heart rhythm, low ejection fraction, shock at the time of admission, and ischemic time >25 minutes) of 0 to 5 was: 7.1% versus 10.2%, 9.5% versus 11%, 22.5% versus 19.6%, 32.4% versus 29.6%, 38.5% versus 30%, and 55.7% versus 50%. Conclusions: The CREST model stratified patients immediately after resuscitation according to risk of a circulatory-etiology death. The tool may allow for estimation of circulatory risk and improve the triage of survivors of cardiac arrest without ST-segment–elevation myocardial infarction at the point of care.

Inadequacy of Headache Management After Subarachnoid Hemorrhage

BACKGROUND Headache profoundly affects management of spontaneous subarachnoid hemorrhage but is poorly characterized. OBJECTIVE To characterize headache after spontaneous subarachnoid hemorrhage. METHODS Medical records of patients with Hunt and Hess grades I-III subarachnoid hemorrhage admitted from 2011 to 2013 were reviewed. Demographics, clinical and radiographic features, medications, and pain scores were recorded through day 14 after hemorrhage. Headache pain was characterized on the basis of a numeric rating scale and analgesic use. Severe headache was defined as 2 or more days with maximum pain scores of 8 or greater or need for 3 or more different analgesics for 2 or more days. Univariate and multivariable models were used to analyze factors associated with severe headache. RESULTS Of the 77 patients in the sample, 57% were women; median age was 57 years. Severe headache (73% overall) was associated nonlinearly with Hunt and Hess grade: grade I, 58%; grade II, 88%; and grade III, 56% (P = .01), and with Hijdra score: score 0-10, 56%; score 11-20, 86%; score 21-30, 76% (P = .03). By univariate analysis, patients with low Hijdra scores were less likely to have severe headache (27% vs 57%; P = .02). In a multivariable model, younger age and higher Hijdra score tended to be associated with severe headache. CONCLUSIONS Headache after spontaneous subarachnoid hemorrhage was often severe, necessitating multiple opioid and nonopioid analgesics. Many patients reported persistent headache and inadequate pain control.

Neurologic Outcomes and Post-resuscitation Care of Patients With Myoclonus Following Cardiac Arrest

*Department of Critical Care Services, Maine Medical Center, Portland, ME; †Division of Critical Care, University of Oslo, Oslo, Norway; ‡Department of Surgical Sciences, Anesthesiology, and Intensive Care, Uppsala University, Uppsala, Sweden; §Department of Anesthesia and Intensive Care, Centre de Hospitalier de Luxembourg, Luxembourg; kSarver Heart Center, University of Arizona, Tucson, AZ; ¶Minneapolis Heart Institute, Division of Cardiology, Minneapolis, MN; #Department of Clinical Sciences, Lund University, Lund, Sweden; and **Department of Anesthesia and Intensive Care, Helsingborg Hospital, Helsingborg, Sweden. Copyright