Measurements of Surgical Volume in Low- and Middle-Income Countries, a Systematic Review.

Background: Surgical volume is a surgical indicator that was described in the Lancet Commission on Global Surgery (LCoGS) and the World Bank World Development Indicators as an important metric for tracking the delivery of surgical care. Objectives: We aimed to characterize the reports on surgical volume (SV) in the existing literature by using a systematic review to assess studies that examine surgical procedures as a ratio of a population (procedures/100,000 population). Methods: The PRISMA guideline was employed in the systematic review of articles that addressed the measurement of SV in low- and middle-income countries (LMICs), with the primary outcome of surgical procedures/100,000 population. Findings: The search result consisted of 6,657 preliminary studies. Following the title and abstract screening, 6,464 articles were excluded, and the remaining 193 were included in the full text review. From the full text review of the 193, only 26 of these articles defined SV as the ratio of number of procedures per population of the catchment/geographical area. The reported SV was a mean of 765, with an SD of 1260 operations per 100,000. The median SV was 180 (min = 0.900, max = 4470). Conclusion: Our findings support the LCoGS assessment of the gap in surgical care. The target for SV is 5000 per 100,000 population, compared to the average of 765 per 100,000 population as found in this review. The challenges for assessing surgical volume gaps are vast, including the nature of written records, which limits SV reports to an absolute number of procedures per year without a reference to the catchment population. For the purpose of tracking SV, we recommend using proxies that account for the capacity of facilities to deliver care regardless of the catchment population.

Kynurenine pathway metabolites selectively associate with impaired associative memory function in depression.

Activation of the kynurenine pathway (KP), an important downstream effect of inflammation, is a driver of depression and neurodegeneration. Damage from the end product of KP activation, quinolinic acid, may be responsible specifically for impairment in hippocampally mediated memory function, among its effects. We hypothesized that associative memory - the ability to recall relationships between items - would be sensitive to KP activation because it is heavily dependent on the hippocampus. We tested a sample of N â€‹= â€‹80 adults with unmedicated depression using a face-name task which assesses the ability to recognize, as well as to recall correct pairings, of faces and names. Plasma samples were analyzed for KP metabolites - tryptophan (TRP), kynurenine (KYN), quinolinic acid (QUIN) and kynurenic acid (KYNA). Using linear models we examined whether the KYN/TRP and QUIN/KYNA ratios predicted performance of recognition memory and associative memory, accounting for item type and the number of learning exposures to items (1 vs. 3). We found that for rearranged items viewed three times, associative memory performance was inversely related to the QUIN/KYNA ratio (p â€‹= â€‹0.01, p â€‹= â€‹0.001 adjusted for age, gender and race/ethnicity). Recognition memory was not associated with KP activation. The results support our hypothesis that KP activation most sensitively impacts hippocampally mediated memory function.

Pupillary Light Reflex Variability as a Predictor of Clinical Outcomes in Subarachnoid Hemorrhage.

BACKGROUND: A change in the pupillary light reflex (PLR) is a sensitive indicator for detecting expanding intracranial lesions. Changes in PLR may be a prognostic marker for patients with intracranial lesions. The purpose of this analysis was to explore how PLR readings, size, constriction velocity (CV), dilation velocity (DV), Neurologic Pupil Index (NPi), and latency predict clinical outcome in patients with subarachnoid hemorrhage. METHODS: This is a secondary analysis of prospectively collected multicenter registry data. The within-subject standard deviation (WSD) of PLR values, NPi, size, CV, DV, and latency were explored as predictors of discharge modified Rankin Scale (mRS) in patients with subarachnoid hemorrhagic. RESULTS: Among 4403 pupillary readings from 82 patients with a diagnosis of subarachnoid hemorrhage, with a mean age of 57.7 years, the admission Glasgow Coma Scale median score was 14 (eye, 4; verbal, 4; motor, 6), and the mRS median was 0 on admission and 4 at discharge. Correlation between standard deviation of PLR values and discharge mRS was moderate and negative (r = -0.3 to -0.47, P < .01). The standard deviations for NPi, size, CV, and DV were significant for predicting discharge mRS (r = 0.23-0.28, P < .05) after controlling for admission Glasgow Coma Scale. CONCLUSION: Patients with higher WSD PLR values showed better outcomes (ie, lower mRS at discharge), suggesting that patients with narrower WSD PLR are at a higher risk for poor outcomes.

Understanding the Relationship Between the Neurologic Pupil Index and Constriction Velocity Values.

The pupillary light reflex (PLR) describes the response when light hits the retina and sends a signal (cranial nerve II) to the Edinger-Westphal Nucleus which via cranial nerve III results in pupillary constriction. The Neurological Pupil indexTM (NPi) and pupil constriction velocity (CV) are two distinct variables that can be observed and measured using a pupillometer. We examine NPi and CV in 27,462 pupil readings (1,617 subjects). NPi values <3.0 and a CV < 0.8 mm/sec were considered abnormal. Regression was used to clarify the effect of pupil size and repeated measures. An odds ratio of abnormal CV given normal NPi (and vice versa) was computed using the glimmixed (SAS) regression. Of 27,462 readings, 49.2% revealed bilaterally normal NPi wtih brisk CV, and 10.8% revealed bilaterally abnormal NPi and slow CV; 9.1% with unilaterally normal NPi and brisk CV where the opposite pupil had an abnormal NPi and slow CV. The remaining 30.9% revealed that one or both PLR had either a normal NPi with slow CV, or abnormal NPi with brisk CV. Brisk CV does not rule out an abnormal PLR; slow CV does not rule in abnormal PLR. Practitioners should consider these implications when interpreting pupillometry readings.