Critical care fellowship training in the United States differs based on specific specialty and includes medicine, surgery, anesthesiology, pediatrics, emergency medicine, and neurocritical care training pathways. We provide an update regarding the number and growth of US critical care fellowship training programs, on-duty residents and certified diplomates, and review the different critical care physician training pathways available to residents interested in pursuing a fellowship in critical care. Data were obtained from the Accreditation Council for Graduate Medical Education and specialty boards (American Board of Internal Medicine, American Board of Surgery, American Board of Anesthesiology, American Board of Pediatrics American Board of Emergency Medicine) and the United Council for Neurologic Subspecialties for the last 16 years (2001-2017). The number of critical care fellowship training programs has increased 22.6%, with a 49.4% increase in the number of on-duty residents annually, over the last 16 years. This is in contrast to the period of 1995 to 2000 when the number of physicians enrolled in critical care fellowship programs had decreased or remained unchanged. Although more than 80% of intensivists in the US train in internal medicine critical care Accreditation Council for Graduate Medical Education-approved fellowships, there has been a significant increase in the number of residents from surgery, anesthesiology, pediatrics, emergency medicine, and other specialties who complete specialty fellowship training and certification in critical care. Matriculation in neurocritical care fellowships is rapidly rising with 60 programs and over 1,200 neurocritical care diplomates. Critical care is now an increasingly popular fellowship in all specialties. This rapid growth of all critical care specialties highlights the magnitude of the heterogeneity that will exist between intensivists in the future.
After hospital discharge, patients who had sepsis have increased mortality. We sought to estimate factors associated with postdischarge mortality and how they vary with time after discharge.
Point-of-care transthoracic echocardiography is increasingly being utilized by the intensive care physicians in the management of hemodynamically unstable patients. However, its use in the management of critically ill patients requiring cardiopulmonary mechanical device support remains to be well described. In this case series, we present two case reports where point-of-care echocardiography was successfully used by the intensive care team in diagnosing and managing problems related to cardiopulmonary assist device malposition.
To determine if earlier initiation of renal replacement therapy (RRT) is associated with improved survival in patients with severe acute kidney injury.We performed a retrospective case-control study of propensity-matched groups with multivariable logistic regression using Akaike Information Criteria to adjust for non-matched variables in a surgical ICU in a tertiary care hospital.We matched 169 of 205 (82%) patients with new initiation of RRT (EARLY group) to 169 similar patients who did not initiate RRT on that day (DEFERRED group). Eighteen (11%) of DEFERRED eventually received RRT before discharge. By univariate analysis, ICU mortality was higher in EARLY (n = 60 (36%) vs. n = 23 (14%), p < 0.001) as was hospital mortality (n = 73 (43%) vs. n = 44 (26%), p = 0.001). Of the 18 RRT patients in DEFERRED, 12 (67%) died in ICU and 13 (72%) in hospital. After propensity matching and logistic regression, we found that EARLY initiation of RRT was associated with a more than doubling of ICU mortality (aOR = 2.310, 95% confidence interval = 1.254-4.257, p = 0.007). However, after similar adjustment, there was no difference in hospital mortality (aOR = 1.283, 95% CI = 0.753-2.186, p = 0.360).While ICU mortality was increased in the EARLY group, there was no difference in hospital mortality between EARLY and DEFERRED groups.
During exercise, the sympathetic nervous system is activated and blood pressure and heart rate increase. In heart failure (HF), the muscle metaboreceptor contribution to sympathetic outflow is attenuated and the mechanoreceptor contribution is accentuated. Previous studies suggest that (1) capsaicin stimulates muscle metabosensitive vanilloid receptor subtype 1 (VR1), inducing a neurally mediated pressor response, and (2) activation of ATP-sensitive P2X receptors enhances the pressor response seen when muscle mechanoreceptors are engaged by muscle stretch. Thus, we hypothesized that the pressor response to VR1 stimulation would be smaller and the sensitizing effects of P2X stimulation greater in rats with HF due to chronic myocardial infarction (MI) than in controls.Eight to 14 weeks after coronary ligation, rats with infarcts >35% had an increased left ventricular end-diastolic pressure and a marked increase in heart weight. Capsaicin injected into the arterial supply of the hindlimb increased blood pressure by 39% (baseline, 93.9+/-9.5 mm Hg) in control animals but only by 8% (baseline, 94.8+/-10.1 mm Hg) in rats with large MIs (P<0.05). P2X receptor stimulation by alpha,beta-methylene ATP enhanced the pressor response to muscle stretch by 42% in control animals and by 72% in rats with large MIs (P<0.05).Compared with control animals, cardiovascular responses to VR1 stimulation are blunted and P2X-mediated responses are augmented in rats with HF owing to large MIs.
Heart failure with reduced ejection fraction (HFrEF) is a condition imposing significant health care burden. Given its syndromic nature and often insidious onset, the diagnosis may not be made until clinical manifestations prompt further evaluation. Detecting HFrEF in precursor stages could allow for early initiation of treatments to modify disease progression. Granular data collected during the perioperative period may represent an underutilized method for improving the diagnosis of HFrEF. We hypothesized that patients ultimately diagnosed with HFrEF following surgery can be identified via machine-learning approaches using pre- and intraoperative data.Perioperative data were reviewed from adult patients undergoing general anesthesia for major surgical procedures at an academic quaternary care center between 2010 and 2016. Patients with known HFrEF, heart failure with preserved ejection fraction, preoperative critical illness, or undergoing cardiac, cardiology, or electrophysiologic procedures were excluded. Patients were classified as healthy controls or undiagnosed HFrEF. Undiagnosed HFrEF was defined as lacking a HFrEF diagnosis preoperatively but establishing a diagnosis within 730 days postoperatively. Undiagnosed HFrEF patients were adjudicated by expert clinician review, excluding cases for which HFrEF was secondary to a perioperative triggering event, or any event not associated with HFrEF natural disease progression. Machine-learning models, including L1 regularized logistic regression, random forest, and extreme gradient boosting were developed to detect undiagnosed HFrEF, using perioperative data including 628 preoperative and 1195 intraoperative features. Training/validation and test datasets were used with parameter tuning. Test set model performance was evaluated using area under the receiver operating characteristic curve (AUROC), positive predictive value, and other standard metrics.Among 67,697 cases analyzed, 279 (0.41%) patients had undiagnosed HFrEF. The AUROC for the logistic regression model was 0.869 (95% confidence interval, 0.829-0.911), 0.872 (0.836-0.909) for the random forest model, and 0.873 (0.833-0.913) for the extreme gradient boosting model. The corresponding positive predictive values were 1.69% (1.06%-2.32%), 1.42% (0.85%-1.98%), and 1.78% (1.15%-2.40%), respectively.Machine-learning models leveraging perioperative data can detect undiagnosed HFrEF with good performance. However, the low prevalence of the disease results in a low positive predictive value, and for clinically meaningful sensitivity thresholds to be actionable, confirmatory testing with high specificity (eg, echocardiography or cardiac biomarkers) would be required following model detection. Future studies are necessary to externally validate algorithm performance at additional centers and explore the feasibility of embedding algorithms into the perioperative electronic health record for clinician use in real time.
To assess whether patients prescribed four-factor prothrombin complex concentrate (4FPC) received less plasma during the following 24-hour period than those treated for the same indications who received only plasma.It is unclear whether 4FPC is associated with a reduction in subsequent plasma transfusion. This is important for minimising transfusion-associated risks and for inventory management.We retrospectively studied patients treated for bleeding or coagulopathy. Individuals receiving 4FPC were matched by indication to patients treated with only plasma. Blood products received during 24-hour follow up were compared between 4FPC and plasma-only patients.There was no difference in the number of patients receiving additional plasma (19 (21%) 4FPC patients vs 31 (34%) plasma-only patients, P = .07) nor in the median number of additional plasma units received (0 units for both groups, interquartile range [0, 0] for 4FPC patients vs [0, 1] for plasma-only patients, P = .09). Subgroup analysis comparing patients who received 4FPC for on-label vs off-label indications found no difference in the number of patients receiving plasma nor in the median number of plasma units received.4FPC was prescribed to a diverse set of patients, and administration was not associated with reduced plasma transfusion at our institution.
