Caudal block vs. transversus abdominis plane block for pediatric surgery: a systematic review and meta-analysis

BackgroundThe caudal block and transversus abdominis plane block (TAP) are commonly used in combination with general anesthesia for pediatric lower abdominal, inguinal, and genitourinary surgeries. There is limited data directly comparing the impact of these techniques on recovery. In this meta-analysis, we compare the duration of postoperative analgesia between these two techniques.ObjectiveThis review examined the duration of analgesia in pediatric patients (age 0–18 years) undergoing surgery who received caudal or TAP block after induction of general anesthesia. The primary outcome was duration of analgesia, defined as the time to first rescue analgesic dose. Secondary outcomes included number of rescue analgesic doses, acetaminophen usage within 24 h postoperatively, 24 h pain score area under the curve, and postoperative nausea and vomiting.Evidence reviewWe systematically searched Pubmed, Central, EMBASE, CINAHL, Google Scholar, Web of Science citation index, the US clinical trials register, and abstracts from prominent 2020–2022 anesthesia conferences for randomized controlled trials that compared these blocks and reported analgesia duration.FindingsTwelve RCTs inclusive of 825 patients were identified. TAP block was associated with longer analgesia duration (Mean difference = 1.76 h, 95% CI: 0.70–2.81, p = 0.001) and reduced doses of rescue analgesic within 24 h (Mean difference = 0.50 doses, 95% CI: 0.02–0.98, p = 0.04). No statistically significant differences were detected in other outcomes.ConclusionThis meta-analysis suggests that TAP block provides greater duration of analgesia than caudal block after pediatric surgeries. TAP block was also associated with fewer rescue analgesic doses in the first 24 h without increased pain scores.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=380876, identifier: CRD42022380876

PROTOCOL: New York State Race, Ethnicity, and Insurance Disparities in Follow-up Prostate Cancer Screening

Using de-identified reports from the Statewide Planning and Research Cooperative System (SPARCS) data, this descriptive study will identify the impact of socioeconomic status (SES) metrics on the follow-up prostate cancer screening care within 3 years of index prostate cancer screening test in NYS. The socioeconomic status metrics will be subclassified into race, insurance, and ethnicity and each of these sub-components will be evaluated for its impact on the follow-up cancer screening care. The exclusion criteria for this study includes patients records with unknown age, age \u3c55 or \u3e75, previous history of prostate cancer or radical prostatectomy, previous prostate biopsy, female sex, lives outside NYS, unknown or missing data on race, ethnicity, or insurance status, or multi-ethnic patients. For the included patients, initial prostate cancer screening, follow-up screening, characteristics (e.g., age, SES), and risk profiles will be evaluated. Moreover, patients diagnosed with prostate cancer or receiving prostatectomy will be reported. Additionally, the following hypotheses will be tested: H(0): Among patients with a baseline PSA test, socioeconomic status (SES) metrics (i.e., vulnerability based upon race/insurance/ethnicity) may pose as barriers to follow-up prostate cancer screening care within 3 years of index prostate cancer screening test (e.g., Vulnerability = V = Black, Hispanic, and Self-pay Insurance) o H(0): Among patients with a baseline PSA test, race does not impact the likelihood of follow-up prostate cancer screening care within 3 years of index prostate cancer screening test (e.g., R-FC) o H(0): Among patients with a baseline PSA test, insurance does not impact the likelihood of follow-up prostate cancer screening care within 3 years of index prostate cancer screening test (e.g., I-FC) o H(0): Among patients with a baseline PSA test, ethnicity does not impact the likelihood of follow-up prostate cancer screening care within 3 years of index prostate cancer screening test (e.g., E-FC

“Feature Detection” vs. “Predictive Coding” Models of Plant Behavior

In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity may be in principle testable, and subject to empirical scrutiny. Our main thesis is that adaptive behavior can only take place by way of a mechanism that predicts the environmental sources of sensory stimulation. We propose to test for anticipation in plants experimentally by contrasting two empirical hypotheses: ‘feature detection’ and ‘predictive coding’. We spell out what these contrasting hypotheses consist of by way of illustration from the animal literature, and consider how to transfer the rationale involved to the plant literature

Dynamical predictions of insular hubs for social cognition and their application to stroke

The insular cortex (IC) is considered a rich hub for context-sensitive emotions/social cognition. Patients with focal IC stroke provide unique opportunities to study socio-emotional processes. Nevertheless, Couto et al. (2013b) have recently reported controversial results regarding IC involvement in emotion and social cognition. Similarly, patients with similar lesions show high functional variability, ranging from almost totally preserved to strongly impaired behavior. Critical evidence suggests that the variability of these patients in the above domains can be explained by enhanced neuroplasticity, compensatory processes, and functional remapping after stroke. Therefore, socio-emotional processes would depend on long-distance connections between the IC and frontotemporal regions. We propose that predictive coding and effective connectivity represent a novel approach to explore functional connectivity and assess compensatory, contralateral, and subsidiary network differences among focal stroke patients. This approach would help explain why socio-emotional performance is so variable within this population.Fil: Limongi, Roberto. Universidad Diego Portales; ChileFil: Tomio, Ailin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Diego Portales; Chile. Universidad Autónoma del Caribe; Colombia. Australian Research Council; Australi