Nevin Manimala

Proc Natl Acad Sci U S A. 2021 Dec 14;118(50):e2102140118. doi: 10.1073/pnas.2102140118.

ABSTRACT

The form of political polarization where citizens develop strongly negative attitudes toward out-party members and policies has become increasingly prominent across many democracies. Economic hardship and social inequality, as well as intergroup and racial conflict, have been identified as important contributing factors to this phenomenon known as “affective polarization.” Research shows that partisan animosities are exacerbated when these interests and identities become aligned with existing party cleavages. In this paper, we use a model of cultural evolution to study how these forces combine to generate and maintain affective political polarization. We show that economic events can drive both affective polarization and the sorting of group identities along party lines, which, in turn, can magnify the effects of underlying inequality between those groups. But, on a more optimistic note, we show that sufficiently high levels of wealth redistribution through the provision of public goods can counteract this feedback and limit the rise of polarization. We test some of our key theoretical predictions using survey data on intergroup polarization, sorting of racial groups, and affective polarization in the United States over the past 50 y.

PMID:34876507 | DOI:10.1073/pnas.2102140118

Proc Natl Acad Sci U S A. 2021 Dec 14;118(50):e2021925118. doi: 10.1073/pnas.2021925118.

ABSTRACT

How can neural networks learn to efficiently represent complex and high-dimensional inputs via local plasticity mechanisms? Classical models of representation learning assume that feedforward weights are learned via pairwise Hebbian-like plasticity. Here, we show that pairwise Hebbian-like plasticity works only under unrealistic requirements on neural dynamics and input statistics. To overcome these limitations, we derive from first principles a learning scheme based on voltage-dependent synaptic plasticity rules. Here, recurrent connections learn to locally balance feedforward input in individual dendritic compartments and thereby can modulate synaptic plasticity to learn efficient representations. We demonstrate in simulations that this learning scheme works robustly even for complex high-dimensional inputs and with inhibitory transmission delays, where Hebbian-like plasticity fails. Our results draw a direct connection between dendritic excitatory-inhibitory balance and voltage-dependent synaptic plasticity as observed in vivo and suggest that both are crucial for representation learning.

PMID:34876505 | DOI:10.1073/pnas.2021925118

BMJ Mil Health. 2021 Dec 7:e002006. doi: 10.1136/bmjmilitary-2021-002006. Online ahead of print.

NO ABSTRACT

PMID:34876478 | DOI:10.1136/bmjmilitary-2021-002006

J Nucl Med Technol. 2021 Dec 7:jnmt.121.263081. doi: 10.2967/jnmt.121.263081. Online ahead of print.

ABSTRACT

Background: While normal ranges for ^99mTc thyroid percentage uptake vary, the seemingly intuitive evaluation of thyroid function does not reflect the complexity of thyroid pathology and biochemical status. The emergence of artificial intelligence (AI) in nuclear medicine has driven problem solving associated with logic and reasoning that warrant re-examination of established benchmarks in thyroid functional assessment. Methods: There were 123 patients retrospectively analysed in the study sample comparing scintigraphic findings to grounded truth established through biochemistry status. Conventional statistical approaches were used in conjunction with an artificial neural network (ANN) to determine predictors of thyroid function from data features. A convolutional neural network (CNN) was also used to extract features from the input tensor (images). Results: Analysis was confounded by sub-clinical hyperthyroidism, primary hypothyroidism, sub-clinical hypothyroidism and T3 toxicosis. Binary accuracy for identifying hyperthyroidism was highest for thyroid uptake classification using a threshold of 4.5% (82.6%), followed by pooled physician 6interpretation with the aid of uptake values (82.3%). Visual evaluation without quantitative values reduced accuracy to 61.0% for pooled physician determinations and 61.4% classifying on the basis of thyroid gland intensity relative to salivary glands. The machine learning (ML) algorithm produced 84.6% accuracy, however, this included biochemistry features not available to the semantic analysis. The deep learning (DL) algorithm had an accuracy of 80.5% based on image inputs alone. Conclusion: Thyroid scintigraphy is useful in identifying hyperthyroid patients suitable for radioiodine therapy when using an appropriately validated cut-off for the patient population (4.5% in this population). ML ANN algorithms can be developed to improve accuracy as second readers systems when biochemistry results are available. DL CNN algorithms can be developed to improve accuracy in the absence of biochemistry results. ML and DL do not displace the role of the physician in thyroid scintigraphy but could be used as second reader systems to minimize errors and increase confidence.

PMID:34876477 | DOI:10.2967/jnmt.121.263081

J Nucl Med Technol. 2021 Dec 7:jnmt.121.261998. doi: 10.2967/jnmt.121.261998. Online ahead of print.

ABSTRACT

Background and Aim: Discordance between histopathological grading and dual tracer PET-CT (⁶⁸Ga-DOTATATE and FDG) findings in neuroendocrine tumours (NETs), though not typical, can be encountered in real-world scenario. The aim of this study was to assess patients with discordance between WHO 2017 grade predicted molecular PET-CT imaging and the actual dual tracer PET-CT findings (by exploring their histopathological, immunohistochemical and molecular imaging characteristics), with a view to identifying the prognostic determinants effecting outcome in a peptide receptor radionuclide therapy (PRRT) set-up. Methods: Thirty six patients of histopathologically proven inoperable, locally advanced/metastatic NETs, referred for PRRT were included in this study. The cohort was divided into two broad population groups: (a) those with discordance (between WHO 2017 grade predicted molecular imaging and the dual tracer PET-CT findings) and (b) control (showing both FDG and ⁶⁸Ga-DOTATATE uptake). The cohort was divided based on dual tracer PET-CT into: (i) metabolically FDG non-avid and SSTR expressing tumors, (ii) metabolically active and non-⁶⁸Ga-DOTATATE concentrating (SSTR expressing) and (iii) matched imaging characteristics with WHO 2017 grading system (showing both FDG and ⁶⁸Ga-DOTATATE concentrating disease) for statistical analysis. Statistical analyses were done on SPSS 23.0. Descriptive statistics was used to analyze categorical data, multivariate analysis was used to assess the correlation between different variables with progression free survival (PFS) and overall survival (OS). Kaplan-Meier was used for survival analysis to calculate median survival and to analyze the survival based on WHO 2017 grading and dual tracer PET. Cox proportional hazards regression analysis was used to determine predictors of survival (OS and PFS). Results: In the entire cohort (n = 36), 24 patients (66.7%) showed discordance whereas 12 patients (33.3%) were in the control group. Among the patients showing discordance: 14 patients (38.9%) had metabolically inactive and SSTR expressing disease and remaining 10 patients (27.8%) had FDG concentrating and SSTR non-expressing disease. Those in the control group, 12 patients (33.3%) had intermediate grade NETs and showed matched (⁶⁸Ga-DOTATATE and FDG concentrating lesions) disease. Multivariate analysis in patients with discordant findings demonstrated significant correlation of dual tracer PET with overall survival while no significant correlation could be established between WHO grade and overall survival in the discordant subgroups. No significant correlation could be appreciated between PFS and either dual tracer PET or WHO grading. The Kaplan-Meier survival analysis and Cox proportional hazards regression analysis demonstrated dual tracer PET-CT imaging to be significant prognostic determinant and predictor of outcome respectively. Conclusion: In summary, in NET patients with discordance between the two parameters, dual tracer PET-CT with FDG and ⁶⁸Ga-DOTATATE performed better than WHO grading, differentiation status and immunohistochemistry in prognosticating and predicting outcome.

PMID:34876476 | DOI:10.2967/jnmt.121.261998

Inj Prev. 2021 Dec 7:injuryprev-2021-044412. doi: 10.1136/injuryprev-2021-044412. Online ahead of print.

ABSTRACT

PURPOSE: Demolishing abandoned buildings has been found to reduce nearby firearm violence. However, these effects might vary within cities and across time scales. We aimed to identify potential moderators of the effects of demolitions on firearm violence using a novel approach that combined machine learning and aerial imagery.

METHODS: Outcomes were annual counts of fatal and non-fatal shootings in Rochester, New York, from 2000 to 2020. Treatment was demolitions conducted from 2009 to 2019. Units of analysis were 152×152 m grid squares. We used a difference-in-differences approach to test effects: (A) the year after each demolition and (B) as demolitions accumulated over time. As moderators, we used a built environment typology generated by extracting information from aerial imagery using convolutional neural networks, a deep learning approach, combined with k-means clustering. We stratified our main models by built environment cluster to test for moderation.

RESULTS: One demolition was associated with a 14% shootings reduction (incident rate ratio (IRR)=0.86, 95% CI 0.83 to 0.90, p<0.001) the following year. Demolitions were also associated with a long-term, 2% reduction in shootings per year for each cumulative demolition (IRR=0.98, 95% CI 0.95 to 1.00, p=0.02). In the stratified models, densely built areas with higher street connectivity displayed following-year effects, but not long-term effects. Areas with lower density and larger parcels displayed long-term effects but not following-year effects.

CONCLUSIONS: The built environment might influence the magnitude and duration of the effects of demolitions on firearm violence. Policymakers may consider complementary programmes to help sustain these effects in high-density areas.

PMID:34876475 | DOI:10.1136/injuryprev-2021-044412

BMJ Glob Health. 2021 Dec;6(12):e006788. doi: 10.1136/bmjgh-2021-006788.

ABSTRACT

INTRODUCTION: Despite ongoing maternal health interventions, maternal deaths in Tanzania remain high. One of the main causes of maternal mortality includes postoperative infections. Surgical site infection (SSI) rates are higher in low/middle-income countries (LMICs), such as Tanzania, compared with high-income countries. We evaluated the impact of a multicomponent safe surgery intervention in Tanzania, hypothesising it would (1) increase adherence to safety practices, such as the WHO Surgical Safety Checklist (SSC), (2) reduce SSI rates following caesarean section (CS) and (3) reduce CS-related perioperative mortality rates (POMRs).

METHODS: We conducted a pre-cross-sectional/post-cross-sectional study design to evaluate WHO SSC utilisation, SSI rates and CS-related POMR before and 18 months after implementation. Our interventions included training of inter-professional surgical teams, promoting use of the WHO SSC and introducing an infection prevention (IP) bundle for all CS patients. We assessed use of WHO SSC and SSI rates through random sampling of 279 individual CS patient files. We reviewed registers and ward round reports to obtain the number of CS performed and CS-related deaths. We compared proportions of individuals with a characteristic of interest during pre-implementation and post implementation using the two-proportion z-test at p≤0.05 using STATA V.15.

RESULTS: The SSC utilisation rate for CS increased from 3.7% (5 out of 136) to 95.1% (136 out of 143) with p<0.001. Likewise, the proportion of women with SSI after CS reduced from 14% during baseline to 1% (p=0.002). The change in SSI rate after the implementation of the safe surgery interventions is statistically significant (p<0.001). The CS-related POMR decreased by 38.5% (p=0.6) after the implementation of safe surgery interventions.

CONCLUSION: Our findings show that our intervention led to improved utilisation of the WHO SSC, reduced SSIs and a drop in CS-related POMR. We recommend replication of the interventions in other LMICs.

PMID:34876458 | DOI:10.1136/bmjgh-2021-006788

BMJ Health Care Inform. 2021 Dec;28(1):e100458. doi: 10.1136/bmjhci-2021-100458.

ABSTRACT

OBJECTIVES: Acute kidney injury (AKI) affects up to one-quarter of hospitalised patients and 60% of patients in the intensive care unit (ICU). We aim to understand the baseline characteristics of patients who will develop distinct AKI trajectories, determine the impact of persistent AKI and renal non-recovery on clinical outcomes, resource use, and assess the relative importance of AKI severity, duration and recovery on survival.

METHODS: In this retrospective, longitudinal cohort study, 156 699 patients admitted to a quaternary care hospital between January 2012 and August 2019 were staged and classified (no AKI, rapidly reversed AKI, persistent AKI with and without renal recovery). Clinical outcomes, resource use and short-term and long-term survival adjusting for AKI severity were compared among AKI trajectories in all cohort and subcohorts with and without ICU admission.

RESULTS: Fifty-eight per cent (31 500/54 212) had AKI that rapidly reversed within 48 hours; among patients with persistent AKI, two-thirds (14 122/22 712) did not have renal recovery by discharge. One-year mortality was significantly higher among patients with persistent AKI (35%, 7856/22 712) than patients with rapidly reversed AKI (15%, 4714/31 500) and no AKI (7%, 22 117/301 466). Persistent AKI without renal recovery was associated with approximately fivefold increased hazard rates compared with no AKI in all cohort and ICU and non-ICU subcohorts, independent of AKI severity.

DISCUSSION: Among hospitalised, ICU and non-ICU patients, persistent AKI and the absence of renal recovery are associated with reduced long-term survival, independent of AKI severity.

CONCLUSIONS: It is essential to identify patients at risk of developing persistent AKI and no renal recovery to guide treatment-related decisions.

PMID:34876451 | DOI:10.1136/bmjhci-2021-100458

BMJ Open. 2021 Dec 7;11(12):e050656corr1. doi: 10.1136/bmjopen-2021-050656corr1.

NO ABSTRACT

PMID:34876439 | DOI:10.1136/bmjopen-2021-050656corr1

BMJ Open. 2021 Dec 7;11(12):e055327. doi: 10.1136/bmjopen-2021-055327.

ABSTRACT

OBJECTIVE: This study aimed to assess the length of stay in health facilities after childbirth and associated maternal and neonatal factors in Ethiopia.

DESIGN: A cross-sectional study.

SETTING: Ethiopia.

PARTICIPANTS: 2260 mothers who participated in the 2016 Ethiopian Demographic and Health Survey were included in the study.

OUTCOME: Length of stay in health facilities after childbirth was the outcome variable of the study.

RESULT: In Ethiopia, the mean duration of postpartum stay for mothers in health facilities was 21.96 (19.97-23.94) hours. Nine hundred and sixty-eight (34.80%) women remained in health institutions for ≥24 hours after delivery. Gestational age, birth weight and mode of delivery were significantly associated with length of stay. Gestational age was found to be inversely associated with length of stay. Mothers who had a vaginal delivery were 8.89% (adjusted HR (AHR) 8.89, 95% CI (4.28 to 18.46), p<0.001) more likely to discharge earlier from health facilities after delivery, compared with those who had a caesarian section. Women with larger size neonates during birth were 19% (AHR=0.81, 95% CI (0.67 to 0.96), p=0.019) more likely to stay longer in health facilities than women with average size neonates. Women with a smaller size neonate during birth were 16% (AHR=0.84, 95% CI (0.70 to 0.99), p=0.040) more likely to stay longer at a health facility, compared with those with an average size neonate.

CONCLUSION: A small percentage of Ethiopian mothers stayed in health facilities for 24 hours or more after delivery. Encouraging mothers to stay in health facilities for the recommended period after childbirth can play a significant role in reducing maternal and neonatal deaths.

PMID:34876438 | DOI:10.1136/bmjopen-2021-055327