Hepatic infarction in pregnancy: a systematic review.

OBJECTIVE: Hepatic infarction is a rare complication of pregnancy most often associated with hemolysis, elevated liver enzymes, and low platelets syndrome. The objective of this review is to identify risk factors, present signs and symptoms, identify methods of diagnosis, and identify best management practices on the basis of published case reviews. DATA SOURCES: PubMed and MEDLINE (Ovid) databases were searched for citations regarding hepatic infarction in pregnancy or the postpartum period from database inception until the study date of December 18, 2023. Key words included "liver infarction" or "hepatic infarction" and "pregnancy" or "obstetrics." STUDY ELIGIBILITY CRITERIA: Case reviews or case series published in the English language were included. Our study was registered with the Prospective Register of Systematic Reviews (registration number CRD42023488176) and was conducted in accordance with the published Prospective Register of Systematic Reviews and Meta-analyses Of Observational Studies in Epidemiology guidelines. METHODS: Included papers were evaluated for bias using a previously published tool. RESULTS: A total of 38 citations documenting 50 pregnancies published between 1979 and 2023 were included. Of these, 34% had a history of hypertensive disease, 26% had antiphospholipid syndrome, and 22% had a history of thrombus. Of those without a preexisting diagnosis of antiphospholipid syndrome, 24% tested positive during hospitalization. Most patients presented with epigastric or right upper quadrant pain (78%), and 32% and 16% had severe blood pressure or mild blood pressure, respectively. Sixty-four percent of patients presented with transaminitis. Forty-six percent of patients delivered preterm, and 32% of pregnancies ended in intrauterine fetal demise, abortion, or early termination of pregnancy for maternal benefit. Computed tomography scans were used to confirm diagnosis of hepatic infarction in 58% of cases, magnetic resonance imaging in 14%, and ultrasound in 6%. In cases that described management, treatment was always multimodal, including antihypertensives (18%), therapeutic anticoagulation (45%), blood product transfusion (36%), plasma exchange or intravenous immunoglobulin (20%), and steroids (39%). Transfer to the intensive care unit was required in 20% of cases. CONCLUSION: Hepatic infarction should be considered in all cases of hemolysis, elevated liver enzymes, and low platelets syndrome, but specifically in patients with a history of antiphospholipid syndrome who present with epigastric or right upper quadrant pain. The diagnosis can usually be confirmed with a computed tomography scan alone, and management should be prompt with supportive care, therapeutic anticoagulation, and steroids.

Preliminary study: quantification of chronic pain from physiological data.

Introduction: It is unknown if physiological changes associated with chronic pain could be measured with inexpensive physiological sensors. Recently, acute pain and laboratory-induced pain have been quantified with physiological sensors. Objectives: To investigate the extent to which chronic pain can be quantified with physiological sensors. Methods: Data were collected from chronic pain sufferers who subjectively rated their pain on a 0 to 10 visual analogue scale, using our recently developed pain meter. Physiological variables, including pulse, temperature, and motion signals, were measured at head, neck, wrist, and finger with multiple sensors. To quantify pain, features were first extracted from 10-second windows. Linear models with recursive feature elimination were fit for each subject. A random forest regression model was used for pain score prediction for the population-level model. Results: Predictive performance was assessed using leave-one-recording-out cross-validation and nonparametric permutation testing. For individual-level models, 5 of 12 subjects yielded intraclass correlation coefficients between actual and predicted pain scores of 0.46 to 0.75. For the population-level model, the random forest method yielded an intraclass correlation coefficient of 0.58. Bland-Altman analysis shows that our model tends to overestimate the lower end of the pain scores and underestimate the higher end. Conclusion: This is the first demonstration that physiological data can be correlated with chronic pain, both for individuals and populations. Further research and more extensive data will be required to assess whether this approach could be used as a "chronic pain meter" to assess the level of chronic pain in patients.