Iftekharuddin, Anika

Abstract Hemorrhagic shock is a common emergency that accounts for more than 10% of global mortality and up to 40% of trauma-related mortality. The Advanced Trauma Life Support (ATLS) guidelines outline resuscitation strategies in patients with massive hemorrhage based on clinical trial and observational data. Early intervention with fluids and/or blood products is recommended during resuscitation as key to maintaining vascular patency, stabilizing a patient’s blood pressure, maintaining tissue oxygenation, and limiting shock. From a transfusion perspective, there is wide heterogeneity in the quality of blood products due to donor and manufacturing variation. The optimal transfusion strategy for massive hemorrhage remains unclear. In silico models of resuscitation may offer a means to evaluate the effectiveness and safety of various resuscitation protocols. Here we describe a stochastic multicompartment model of fluid balance and resuscitation that includes (i) cardiovascular hemodynamics, (ii) body fluid compartments and capillary solute exchange, (iii) the ability to alter hemorrhage, resuscitation, and hemostasis parameters, and (iv) tissue oxygenation and capillary-alveolar gas exchange. Building upon deterministic frameworks, this stochastic model more faithfully reflects the clinical heterogeneity of bleeding patients at a level I trauma center. This allows for a proof of concept in silico trial comparing crystalloids, conventional component therapy (CCT), i.e. red cell, platelet and plasma components, to cold-stored low titer group O whole blood (LTOWB). In an in silico cohort of ATLS class III (>30% and ≤40% blood volume lost) hemorrhage, LTOWB resuscitation reduced the time spent in the critical hemostatic window (platelet count <50x109/L, INR≥2, hemoglobin (Hgb) <8 g/dL and fibrinogen <150 mg/dL) compared with CCT (90.59 vs. 147.62 minutes; p=0.04), with no difference in predicted event-free survival (t = 240 minutes; cardiac < 1.5, fluid overload > 10% or SBP > 150% of the starting SBP, or Hgb < 3.0 g/dL). In a separate cohort of ATLS class IV (>40% blood volume lost) hemorrhage, LTOWB yielded a higher predicted event-free survival (74%) versus the CCT arm (69%, p < 0.01). We demonstrate how this in silico platform can function as a digital twin for hemorrhagic trauma enabling precision transfusion strategies, and in parallel, an operational twin to support blood banks to forecast blood product demand and inform massive transfusion protocols and clinical trial design.

Reversible cerebral vasoconstriction syndrome (RCVS) represents a group of conditions that show reversible multifocal narrowing or constriction of the cerebral arteries that supply blood to the brain. The initial manifestation of RCVS often includes a “thunderclap” headache that is sudden, severe, and often disabling. Stimulants, selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and antipsychotics with serotonergic activity can alter the cerebral arterial tone, trigger vasoconstriction, and place patients at risk of a cerebrovascular accident. Thus, psychiatric medications are commonly discontinued on admission for RCVS, and psychiatry is often consulted for input on acute medication management and longitudinal treatment options. Currently, there is a dearth of literature on managing psychiatric medications in RCVS, resulting in variable practice patterns that place patients at risk of withdrawal, decompensation, and relapse. In this article, we provide a case example and aim to consolidate the limited data surrounding the management of psychiatric illness with comorbid RCVS in our discussion. There is a clear concern about worsening and even potentially lethal consequences due to serotonin or stimulant-induced vasospasm both during an acute episode and in long-term management of RCVS. We discuss the underlying pathophysiologic mechanisms proposed for serotonergic-, noradrenergic-, and dopaminergic-induced cerebral vasospasm and how this correlates with the clinical management of patients on psychiatric medications. These data will then be organized to create a risks versus benefits outline to equip psychiatrists to make decisions about when to stop and when to restart psychiatric medications in the setting of RCVS.