Effects of preterm birth, maternal ART and breastfeeding on 24-month infant HIV-free survival in a randomized trial.

BACKGROUND: IMPAACT 1077BF/FF (PROMISE) compared the safety/efficacy of two HIV antiretroviral therapy (ART) regimens to zidovudine (ZDV) alone during pregnancy for HIV prevention. PROMISE found an increased risk of preterm delivery (<37 weeks) with antepartum triple ART (TDF/FTC/LPV+r or ZDV/3TC/LPV+r) compared with ZDV alone. We assessed the impact of preterm birth, breastfeeding, and antepartum ART regimen on 24-month infant survival. METHODS: We compared HIV-free and overall survival at 24 months for liveborn infants by gestational age, time-varying breastfeeding status, and antepartum ART arm at 14 sites in Africa and India. Kaplan-Meier survival probabilities and Cox proportional hazards ratios were estimated. RESULTS: Three thousand four hundred and eighty-two live-born infants [568 (16.3%) preterm and 2914 (83.7%) term] were included. Preterm birth was significantly associated with lower HIV-free survival [0.85; 95% confidence interval (CI) 0.82-0.88] and lower overall survival (0.89; 95% CI 0.86-0.91) versus term birth (0.96; 95% CI 0.95-0.96). Very preterm birth (<34 weeks) was associated with low HIV-free survival (0.65; 95% CI 0.54-0.73) and low overall survival (0.66; 95% CI 0.56-0.74). Risk of HIV infection or death at 24 months was higher with TDF-ART than ZDV-ART (adjusted hazard ratio 2.37; 95% CI 1.21-4.64). Breastfeeding initiated near birth decreased risk of infection or death at 24 months (adjusted hazard ratio 0.05; 95% CI 0.03-0.08) compared with not breastfeeding. CONCLUSION: Preterm birth and antepartum TDF-ART were associated with lower 24-month HIV-free survival compared with term birth and ZDV-ART. Any breastfeeding strongly promoted HIV-free survival, especially if initiated close to birth. Reducing preterm birth and promoting infant feeding with breastmilk among HIV/antiretroviral drug-exposed infants remain global health priorities.

Systemic inflammation in pregnant women with HIV: relationship with HIV treatment regimen and preterm delivery.

OBJECTIVE: HIV treatment regimen during pregnancy was associated with preterm delivery (PTD) in the PROMISE 1077 BF trial. Systemic inflammation among pregnant women with HIV could help explain differences in PTD by treatment regimen. We assessed associations between inflammation, treatment regimen, and PTD. DESIGN/METHODS: A nested 1 : 1 case-control study ( N  = 362) was conducted within a multicountry randomized trial comparing three HIV regimens in pregnant women: zidovudine alone, or combination antiretroviral therapy (ART) with lopinavir/ritonavir and either zidovudine or tenofovir. Cases were women with PTD (<37 weeks of gestational age). The following inflammatory biomarkers were measured in plasma samples using immunoassays: soluble CD14 (sCD14) and sCD163, intestinal fatty acid-binding protein, interleukin (IL)-6, interferon γ, and tumor necrosis factor α. We fit regression models to assess associations between second trimester biomarkers (measured before ART initiation at 13-23 weeks of gestational age and 4 weeks later), treatment regimen, and PTD. We also assessed whether inflammation was a mediator in the relationship between ART regimen and PTD. RESULTS: Persistently high interleukin-6 was associated with increased PTD. Compared with zidovudine alone, the difference in biomarker concentration between week 0 and week 4 was significantly higher ( P  < 0.05) for both protease inhibitor-based regimens. However, the estimated proportion of the ART effect on increased PTD mediated by persistently high biomarker levels was 5% or less for all biomarkers. CONCLUSION: Persistently high IL-6 during pregnancy was associated with PTD. Although protease inhibitor-based ART was associated with increases in inflammation, factors other than inflammation likely explain the increased PTD in ART-based regimens compared with zidovudine alone.

Intimate partner violence and excess fertility among women of reproductive age in Malawi.

PURPOSE: Gender inequity and adverse health outcomes continue to be of concern among women in sub-Saharan Africa. We determined prevalence of intimate partner violence and excess fertility (having more children than desired) in reproductive age women in Malawi. We also explored factors associated with these outcomes and with spousal fertility intentions. PATIENTS AND METHODS: In a cross-sectional study, a total of 360 women and 410 men were recruited using multi-stage sampling from communities in a peri-urban setting in Blantyre District, Southern Malawi in 2021. Women and men were separately interviewed by trained study workers using a structured questionnaire. In addition to descriptive analyses, we used univariate and multivariate logistic regression models to assess associations of risk factors with the outcomes of intimate partner violence and excess fertility. RESULTS: Among women, lifetime prevalence of intimate partner violence was 23.1%, and excess fertility was experienced by 25.6%. Intimate partner violence was associated with male partners alcohol consumption (adjusted odds ratio 2.13; P = 0.019). Women were more likely to report excess fertility if they were older (adjusted odds ratio 2.0, P<0.001, for a 5-year increase). Alcohol consumption by the male partner (adjusted odds ratio 2.14; P = 0.025) and women being able to refuse sex with their male partner (adjusted odds ratio 0.50; P = 0.036) were associated with discordant fertility preferences. CONCLUSIONS: Intimate partner violence, excess fertility, and social and health inequities continue to be prevalent in Malawi. These data suggest the underlying proximal and distal factors associated with these adverse outcomes such as alcohol consumption may be addressed through education, couple interactive communication, and community dialogue. To ensure sustainability and effectiveness, strong leadership involvement, both governmental and non-governmental, is needed.

Breastfeeding Among Women Living With HIV in the Era of Lifelong ART: An Observational Multicountry Study in Eastern and Southern Africa.

BACKGROUND: Lifelong antiretroviral treatment (ART) use is recommended for pregnant and breastfeeding (BF) women living with HIV (WLWH) to prevent perinatal HIV transmission and improve maternal health. We address 2 objectives in this analysis: (1) determine timing and factors associated with BF cessation and (2) assess the impact of BF on health of WLWH on ART. SETTING: This multicountry study included 8 sites in Uganda, Malawi, Zimbabwe, and South Africa. METHODS: This was a prospective study of WLWH on lifelong ART. These women initially participated from 2011 to 2016 in a randomized clinical trial (PROMISE) to prevent perinatal HIV transmission and subsequently reenrolled in an observational study (PROMOTE, 2016-2021) to assess ART adherence, safety, and impact. RESULTS: The PROMOTE cohort included 1987 women on ART. Of them, 752 breastfed and were included in analyses of objective 1; all women were included in analyses of objective 2. The median time to BF cessation varied by country (11.2-19.7 months). Country of residence, age, and health status of women were significantly associated with time to BF cessation (compared with Zimbabwe: Malawi, adjusted hazard ratio [aHR] 0.50, 95% confidence interval [95% CI]: 0.40 to 0.62, P < 0.001; South Africa, aHR 1.49, 95% CI: 1.11 to 2.00, P = 0.008; and Uganda, aHR 1.77, 95% CI: 1.37 to 2.29, P < 0.001). Women who breastfed had lower risk of being "unwell" compared with women who never breastfed (adjusted rate ratio 0.87, 95% CI: 0.81 to 0.95 P = 0.030). CONCLUSION: Women on lifelong ART should be encouraged to continue BF with no concern for their health. Time to BF cessation should be monitored for proper counseling in each country.

Automated diagnosis of EEG abnormalities with different classification techniques.

Automatic seizure detection and prediction using clinical Electroencephalograms (EEGs) are challenging tasks due to factors such as low Signal-to-Noise Ratios (SNRs), high variance in epileptic seizures among patients, and limited clinical data constraints. To overcome these challenges, this paper presents two approaches for EEG signal classification. One of these approaches depends on Machine Learning (ML) tools. The used features are different types of entropy, higher-order statistics, and sub-band energies in the Hilbert Marginal Spectrum (HMS) domain. The classification is performed using Support Vector Machine (SVM), Logistic Regression (LR), and K-Nearest Neighbor (KNN) classifiers. Both seizure detection and prediction scenarios are considered. The second approach depends on spectrograms of EEG signal segments and a Convolutional Neural Network (CNN)-based residual learning model. We use 10000 spectrogram images for each class. In this approach, it is possible to perform both seizure detection and prediction in addition to a 3-state classification scenario. Both approaches are evaluated on the Children's Hospital Boston and the Massachusetts Institute of Technology (CHB-MIT) dataset, which contains 24 EEG recordings for 6 males and 18 females. The results obtained for the HMS-based model showed an accuracy of 100%. The CNN-based model achieved accuracies of 97.66%, 95.59%, and 94.51% for Seizure (S) versus Pre-Seizure (PS), Non-Seizure (NS) versus S, and NS versus S versus PS classes, respectively. These results demonstrate that the proposed approaches can be effectively used for seizure detection and prediction. They outperform the state-of-the-art techniques for automatic seizure detection and prediction. Block diagram of proposed epileptic seizure detection method using HMS with different classifiers.

Community-Acquired Methicillin-Resistant Staphylococcus aureus in Hospitals: Age-Specificity and Potential Zoonotic-Zooanthroponotic Transmission Dynamics.

Methicillin-resistant Staphylococcus aureus (MRSA) lineages are a devastating clinical and public health issue. Data on local lineage profiles are limited. We report on the frequency of community-acquired and hospital-acquired cases (CA-MRSA, HA-MRSA). We studied 147 isolates from King Khalid tertiary care hospitals (KKH), each from a case in a patient and including 33 patients at the Maternity and Children's Hospital (MCH). Of the 147 isolates, 87 males (59%) and 60 females (41%) were in KKH. The overwhelming majority (80%; n = 119/147) were CA-MRSA in KKH. Intriguingly, despite significant differences between males (70%) and females (53%), lineage-acquisition remained age-specific around 58-60 years in both genders. However, while CA-MRSA dominated early in life (0-20, 70% MCH), it increased with age in KKH adults; 21-50 (28%), >50 (59%) until the overall 80% (n = 144/180). Major specimens included skin-wounds, surgeries (70.3%), blood (13.5%), sputum (8.8%), very rarely urine (4.1%), and nasal (3.4%), albeit most patients showed severe enteritis and necrotizing pneumonia. Antibiograms showed high beta lactam resistances, including amoxicillin-clavulanate (83%), oxacillin (84%), cefoxitin FOX (100%), penicillin and ampicillin (~100%), as well as high resistance (82%) to carbapenem. Fortunately, high susceptibility was seen to non-beta lactams and, to a lesser extent, gentamicin, erythromycin, and fusidic acid; 33%, 34%, and 38%, respectively, in KKH. A similar pattern was seen in MCH except for a low resistance pattern to gentamicin CN, clindamycin CD, erythromycin E, and tobramycin TOB; 34%, 31%, 39%, and 41%, respectively, except for fusidic acid. These findings have significant clinical implications for MRSA patient management strategies. Clinical- and lineage-profiles imply host-selection and zoonotic-zooanthroponotic transmission dynamics. Future molecular typing, sequencing, and characterization of dominant clone(s) is imperative.

Simultaneous Super-Resolution and Classification of Lung Disease Scans.

Acute lower respiratory infection is a leading cause of death in developing countries. Hence, progress has been made for early detection and treatment. There is still a need for improved diagnostic and therapeutic strategies, particularly in resource-limited settings. Chest X-ray and computed tomography (CT) have the potential to serve as effective screening tools for lower respiratory infections, but the use of artificial intelligence (AI) in these areas is limited. To address this gap, we present a computer-aided diagnostic system for chest X-ray and CT images of several common pulmonary diseases, including COVID-19, viral pneumonia, bacterial pneumonia, tuberculosis, lung opacity, and various types of carcinoma. The proposed system depends on super-resolution (SR) techniques to enhance image details. Deep learning (DL) techniques are used for both SR reconstruction and classification, with the InceptionResNetv2 model used as a feature extractor in conjunction with a multi-class support vector machine (MCSVM) classifier. In this paper, we compare the proposed model performance to those of other classification models, such as Resnet101 and Inceptionv3, and evaluate the effectiveness of using both softmax and MCSVM classifiers. The proposed system was tested on three publicly available datasets of CT and X-ray images and it achieved a classification accuracy of 98.028% using a combination of SR and InceptionResNetv2. Overall, our system has the potential to serve as a valuable screening tool for lower respiratory disorders and assist clinicians in interpreting chest X-ray and CT images. In resource-limited settings, it can also provide a valuable diagnostic support.

A Sequalae of Lineage Divergence in Staphylococcus aureus from Community-Acquired Patterns in Youth to Hospital-Associated Profiles in Seniors Implied Age-Specific Host-Selection from a Common Ancestor.

The rapidly changing epidemiology of Staphylococcus aureus and evolution of strains with enhanced virulence is a significant issue in global healthcare. Hospital-associated methicillin-resistant S. aureus (HA-MRSA) lineages are being completely replaced by community-associated S. aureus (CA-MRSA) in many regions. Surveillance programs tracing the reservoirs and sources of infections are needed. Using molecular diagnostics, antibiograms, and patient demographics, we have examined the distributions of S. aureus in Ha'il hospitals. Out of 274 S. aureus isolates recovered from clinical specimens, 181 (66%, n = 181) were MRSA, some with HA-MRSA patterns across 26 antimicrobials with almost full resistances to all beta-lactams, while the majority were highly susceptible to all non-beta-lactams, indicating the CA-MRSA type. The rest of isolates (34%, n = 93) were methicillin-susceptible, penicillin-resistant MSSA lineages (90%). The MRSA in men was over 56% among total MRSA (n = 181) isolates and 37% of overall isolates (n = 102 of 274) compared to MSSA in total isolates (17.5%, n = 48), respectively. However, these were 28.4% (n = 78) and 12.4% (n = 34) for MRSA and MSSA infections in women, respectively. MRSA rates per age groups of 0-20, 21-50, and >50 years of age were 15% (n = 42), 17% (n = 48), and 32% (n = 89), respectively. However, MSSA in the same age groups were 13% (n = 35), 9% (n = 25), and 8% (n = 22). Interestingly, MRSA increased proportional to age, while MSSA concomitantly decreased, implying dominance of the latter ancestors early in life and then gradual replacement by MRSA. The dominance and seriousness of MRSA despite enormous efforts in place is potentially for the increased use of beta-lactams known to enhance virulence. The Intriguing prevalence of the CA-MRSA patterns in young otherwise healthy individuals replaced by MRSA later in seniors and the dominance of penicillin-resistant MSSA phenotypes imply three types of host- and age-specific evolutionary lineages. Thus, the decreasing MSSA trend by age with concomitant increase and sub-clonal differentiation into HA-MRSA in seniors and CA-MRSA in young and otherwise healthy patients strongly support the notion of subclinal emergences from a resident penicillin-resistant MSSA ancestor. Future vertical studies should focus on the surveillance of invasive CA-MRSA rates and phenotypes.

Molecular and Source-Specific Profiling of Hospital Staphylococcus aureus Reveal Dominance of Skin Infection and Age-Specific Selections in Pediatrics and Geriatrics.

Staphylococcus aureus is a major human-associated pathogen that causes a wide range of clinical infections. However, the increased human dynamics and the changing epidemiology of the species have made it imperative to understand the population structure of local ecotypes, their transmission dynamics, and the emergence of new strains. Since the previous methicillin-resistant S. aureus (MRSA) pandemic, there has been a steady increase in global healthcare-associated infections involving cutaneous and soft tissue and resulting in high morbidities and mortalities. Limited data and paucity of high-quality evidence exist for many key clinical questions about the pattern of S. aureus infections. Using clinical, molecular, and epidemiological characterizations of isolates, hospital data on age and infection sites, as well as antibiograms, we have investigated profiles of circulating S. aureus types and infection patterns. We showed that age-specific profiling in both intensive care unit (ICU) and non-ICU revealed highest infection rates (94.7%) in senior-patients > 50 years; most of which were MRSA (81.99%). However, specific distributions of geriatric MRSA and MSSA rates were 46.5% and 4.6% in ICU and 35.48% and 8.065% in non-ICU, respectively. Intriguingly, the age groups 0−20 years showed uniquely similar MRSA patterns in ICU and non-ICU patients (13.9% and 9.7%, respectively) and MSSA in ICU (11.6%). The similar frequencies of both lineages in youth at both settings is consistent with their increased socializations and gathering strongly implying carriage and potential evolutionary replacement of MSSA by MRSA. However, in age groups 20−50 years, MRSA was two-fold higher in non-ICU (35%) than ICU (18.6%). Interestingly, a highly significant association was found between infection-site and age-groups (p-value 0.000). Skin infections remained higher in all ages; pediatrics 32.14%, adults 56%, and seniors 25% while respiratory infections were lower in pediatrics (14.3%) and adults (17%) while it was highest in seniors (38%). Blood and "other" sites in pediatrics were recorded (28.6%; 25%, respectively), and were slightly lower in adults (18.6%; 8.6%) and seniors (14%; 22.8%), respectively. Furthermore, a significant association existed between infection-site and MRSA (Chi-Square Test, p-value 0.002). Thus, the common cutaneous infections across all age-groups imply that skin is a significant reservoir for endogenous infections; particularly, for geriatrics MRSA. These findings have important clinical implications and in understanding S. aureus profiles and transmission dynamics across different age groups that is necessary for strategic planning in patient management and infection control.

Self-reported Antiretroviral Adherence: Association With Maternal Viral Load Suppression in Postpartum Women Living With HIV-1 From Promoting Maternal and Infant Survival Everywhere, a Randomized Controlled Trial in Sub-Saharan Africa and India.

INTRODUCTION: Optimal adherence to antiretroviral therapy (ART) is crucial to promoting maternal-infant health. SETTING: Fourteen sites in 7 countries within sub-Saharan Africa and India. METHODS: The multicomponent, open-label strategy PROMISE trial enrolled breastfeeding mother-infant pairs not meeting in-country criteria for maternal ART (mART) initiation in the postpartum component within 5 days of delivery. Randomization was to mART versus infant NVP (iNVP) prophylaxis. Infants in the mART arm also received 6 weeks of iNVP. Self-reported adherence was assessed in a secondary analysis. Time-to-event analyses were performed to explore the association between adherence and maternal viral load (mVL) in the mART arm. RESULTS: Two thousand four hundred thirty-one mother-infant pairs were enrolled between 2011 and 2014; the baseline maternal median CD4 was 686 (IQR 553-869), and the median mVL was 322 copies/mL (IQR 40-1422). Self-reported adherence was lower in the mART arm compared with the iNVP arm (no missed doses within 4 weeks of all study visits: 66% vs 83%; within 2 weeks: 71% vs 85%; P < 0.0001). The iNVP adherence at week 6 was high in both arms: 97% in mART arm; 95% in iNVP arm. Time-to-event analyses showed that adherence to mART was associated with time to first mVL ≥400 copies/mL ( P < 0.0001). Missing 1 full day of doses over 3 days was associated with a 66% risk of mVL ≥1000 copies/mL (HR: 1.66; 95% CI: 1.37, 1.99). CONCLUSIONS: Postpartum women were less adherent to their own ART than mothers providing their infant's nevirapine prophylaxis. The self-reported missed mART doses were associated with high mVL. Strategies to optimize postpartum mART adherence are urgently needed. CLINICAL TRIAL NUMBER: ClinicalTrials.gov: NCT01061151; closed to follow-up.

Impact of Motivational Enhanced Adherence Counseling and Point-of-Care Viral Load Monitoring on Viral Load Outcome in Women on Life-Long ART: A Randomized Pilot Study.

We piloted the combined effectiveness of point-of-care viral load monitoring plus motivational enhanced adherence counseling (intervention) compared with routine care (control) in women identified at risk of virologic failure in the PROMOTE study in Zimbabwe. In an unblinded randomized study, consenting women with last viral load ≥200 copies/ml and/or pill count outside 90-110% range were randomized 1 : 1 to receive the intervention or continue routine care, comprising laboratory-based VL monitoring and standard EAC, from trained nurses and counsellors. Viral load was measured 0, 3, 6, and 12 months after enrolment. We compared viral suppression <200 copies/ml at 6 and 12 months between the arms through Fisher's exact test and sought associated factors by logistic regression with a 95% confidence interval (CI). Between December 2018 and July 2019, 50 women were enrolled (25 intervention and 25 controls) and followed until November 2020. At entry, 60% of the women were virally suppressed, 52% intervention vs. 68% control arm. Viral suppression was balanced between the two arms (p value = 0.248). At month 6 post study entry (primary endpont), 64% of the women retained in care were virally suppressed, 54% intervention vs. 76% control arm (p value = 0.124). At month12 post study entry (secondary endpoint), 69% of the women retained in care were virally suppressed, 67% intervention vs. 71% control arm women (p value = 0.739). More intervention women completed all scheduled sessions by month 6. Control group women were more likely to be virally suppressed at both timepoints. Only 25% had treatment switch by 12 months. Despite intense adherence support and viral load monitoring, sustained viral suppression remained elusive in women identified at risk of viral failure. These findings highlight the continued need for effective adherence intervention for women with unsuppressed HIV viral loads, efficient treatment switch strategies, as well as drug level monitoring.

Maternal and infant renal safety following tenofovir disoproxil fumarate exposure during pregnancy in a randomized control trial.

BACKGROUND: Tenofovir disoproxil fumarate (TDF) in combination with other antiretroviral (ARV) drugs has been in clinical use for HIV treatment since its approval in 2001. Although the effectiveness of TDF in preventing perinatal HIV infection is well established, information about renal safety during pregnancy is still limited. TRIAL DESIGN: The IMPAACT PROMISE study was an open-label, strategy trial that randomized pregnant women to one of three arms: TDF based antiretroviral therapy (ART), zidovudine (ZDV) based ART, and ZDV alone (standard of care at start of enrollment). The P1084s substudy was a nested, comparative study of renal outcomes in women and their infants. METHODS: PROMISE participants (n = 3543) were assessed for renal dysfunction using calculated creatinine clearance (CrCl) at study entry (> 14 weeks gestation), delivery, and postpartum weeks 6, 26, and 74. Of these women, 479 were enrolled in the P1084s substudy that also assessed maternal calcium and phosphate as well as infant calculated CrCl, calcium, and phosphate at birth. RESULTS: Among the 1338 women who could be randomized to TDF, less than 1% had a baseline calculated CrCl below 80 mL/min. The mean (standard deviation) maternal calculated CrCl at delivery in the TDF-ART arm [147.0 mL/min (51.4)] was lower than the ZDV-ART [155.0 mL/min (43.3); primary comparison] and the ZDV Alone [158.5 mL/min (45.0)] arms; the mean differences (95% confidence interval) were - 8.0 mL/min (- 14.5, - 1.5) and - 11.5 mL/min (- 18.0, - 4.9), respectively. The TDF-ART arm had lower mean maternal phosphate at delivery compared with the ZDV-ART [- 0.14 mg/dL (- 0.28, - 0.01)] and the ZDV Alone [- 0.17 mg/dL (- 0.31, - 0.02)] arms, and a greater percentage of maternal hypophosphatemia at delivery (4.23%) compared with the ZDV-ART (1.38%) and the ZDV Alone (1.46%) arms. Maternal calcium was similar between arms. In infants, mean calculated CrCl, calcium, and phosphate at birth were similar between arms (all CIs included 0). CONCLUSIONS: Although mean maternal calculated CrCl at Delivery was lower in the TDF-ART arm, the difference between arms is unlikely to be clinically significant. During pregnancy, the TDF-ART regimen had no observed safety concerns for maternal or infant renal function. TRIAL REGISTRATION: NCT01061151 on 10/02/2010 for PROMISE (1077BF). NCT01066858 on 10/02/2010 for P1084s.

COVID-19 Clinical Profiles and Fatality Rates in Hospitalized Patients Reveal Case Aggravation and Selective Co-Infection by Limited Gram-Negative Bacteria.

Bacterial co-infections may aggravate COVID-19 disease, and therefore being cognizant of other pathogens is imperative. We studied the types, frequency, antibiogram, case fatality rates (CFR), and clinical profiles of co-infecting-pathogens in 301 COVID-19 patients. Co-infection was 36% (n = 109), while CFR was 31.2% compared to 9.9% in non-co-infected patients (z-value = 3.1). Four bacterial species dominated, namely, multidrug-resistant Klebsiella pneumoniae (37%, n = 48), extremely drug-resistant Acinetobacter baumannii (26%, n = 34), multidrug-resistant Eschericia. coli (18.6%, n = 24), and extremely drug-resistant Pseudomonas aeruginosa (8.5%, n = 11), in addition to other bacterial species (9.3%, n = 12). Increased co-infection of K. pneumoniae and A. baumannii was associated with increased death rates of 29% (n = 14) and 32% (n = 11), respectively. Klebsiella pneumoniae was equally frequent in respiratory and urinary tract infections (UTI), while E. coli mostly caused UTI (67%), and A. baumannii and P. aeruginosa dominated respiratory infections (38% and 45%, respectively). Co-infections correlated with advance in age: seniors ≥ 50 years (71%), young adults 21-49 years (25.6%), and children 0-20 years (3%). These findings have significant clinical implications in the successful COVID-19 therapies, particularly in geriatric management. Future studies would reveal insights into the potential selective mechanism(s) of Gram-negative bacterial co-infection in COVID-19 patients.

Effects of long-term antiretroviral therapy in reproductive-age women in sub-Saharan Africa (the PEPFAR PROMOTE study): a multi-country observational cohort study.

BACKGROUND: We report the long-term impact of ART in women of reproductive age (15-49 years) in Africa who have been using ART for up to 10 years. We assess outcomes of retention, adherence, maternal health, fertility intentions, and safety. METHODS: This longitudinal, multicountry study (PROMOTE) enrolled women who initiated ART in an earlier perinatal clinical trial, PROMISE. PROMISE occurred from 2011 to 2016 and PROMOTE follow-up started in 2016 and is ongoing. The PROMOTE study was done at eight sites in four countries: Malawi (Blantyre and Lilongwe), South Africa (Durban and Soweto), Uganda (Kampala), and Zimbabwe (Harare, Seke North, and St Mary's). After baseline enrolment, women and their children are followed up every 6 months to collect information on medical history, antiretroviral therapy (ART) use, adherence, and health information, and to do physical examinations and laboratory tests. Obesity was defined as a body-mass index of 30 kg/m2 or more. Data analyses were restricted to summaries of the main long-term outcomes (retention, adherence, maternal health, fertility intentions, and safety). We used descriptive and stratified analyses, and estimated rates using person-years of follow-up and computed probabilities based on Kaplan-Meier methods. FINDINGS: PROMOTE enrolled 1987 mothers and 2522 children. The median follow-up time for mothers was 41·8 (IQR 35·8-42·0) months and for children was 35·7 (23·8-42·0) months. Overall retention rates were 96·5% for mothers and 94·3% for children at 12 months, and, at 42 months, were 88·9% for mothers and 85·4% for children. 1115 (89·1%) of 1252 women had an undetectable viral load at 42 months, which varied by site (81·7-93·8%). Reported maternal health improved over time, with the proportion of women with excellent to very good health increasing from 67·5% at baseline to 87·5% at 42 months, the proportion of unwell participants who visited a health centre declining from 14·7% to 2·8%, and the proportion of those admitted to hospital declining from 1·5% to 1·0%. The desire to have more children was consistently high at some sites. The proportion of women with obesity was high in South Africa and increased over time from 40·2% at baseline to 52·8% at 42 months. The overall pregnancy rate was 17·6 (95% CI 16·5-18·7) per 100 women-years, and mortality rates were 2·4 (1·4-3·9) per 1000 person-years for mothers and 3·4 (2·2-5·10) per 1000 person-years for children (0-9 years). INTERPRETATION: The findings from this multicountry study are reassuring. These findings show that African women can consistently use ART for a long period after initiation, and long-term benefits can be maintained. Services to support maternal HIV care, treatment, and reproductive health should be strengthened. FUNDING: US President's Emergency Plan for AIDS Relief.

Hybrid classification structures for automatic COVID-19 detection.

This paper explores the issue of COVID-19 detection from X-ray images. X-ray images, in general, suffer from low quality and low resolution. That is why the detection of different diseases from X-ray images requires sophisticated algorithms. First of all, machine learning (ML) is adopted on the features extracted manually from the X-ray images. Twelve classifiers are compared for this task. Simulation results reveal the superiority of Gaussian process (GP) and random forest (RF) classifiers. To extend the feasibility of this study, we have modified the feature extraction strategy to give deep features. Four pre-trained models, namely ResNet50, ResNet101, Inception-v3 and InceptionResnet-v2 are adopted in this study. Simulation results prove that InceptionResnet-v2 and ResNet101 with GP classifier achieve the best performance. Moreover, transfer learning (TL) is also introduced in this paper to enhance the COVID-19 detection process. The selected classification hierarchy is also compared with a convolutional neural network (CNN) model built from scratch to prove its quality of classification. Simulation results prove that deep features and TL methods provide the best performance that reached 100% for accuracy.

Deep-learning-based seizure detection and prediction from electroencephalography signals.

Electroencephalography (EEG) is among the main tools used for analyzing and diagnosing epilepsy. The manual analysis of EEG must be conducted by highly trained clinicians or neuro-physiologists; a process that is considered to have a comparatively low inter-rater agreement. Furthermore, the new data interpretation consumes an excessive amount of time and resources. Hence, an automatic seizure detection and prediction system can improve the quality of patient care in terms of shortening the diagnosis period, reducing manual errors, and automatically detecting debilitating events. Moreover, for patient treatment, it is important to alert the patients of epilepsy seizures prior to seizure occurrence. Various distinguished studies presented good solutions for two-class seizure detection problems with binary classification scenarios. To deal with these challenges, this paper puts forward effective approaches for EEG signal classification for normal, pre-ictal, and ictal activities. Three models are presented for the classification task. Two of them are patient-specific, while the third one is patient non-specific, which makes it better for the general classification tasks. The two-class classification is implemented between normal and pre-ictal activities for seizure prediction and between normal and ictal activities for seizure detection. A more generalized three-class classification framework is considered to identify all EEG signal activities. The first model depends on a Convolutional Neural Network (CNN) with residual blocks. It contains thirteen layers with four residual learning blocks. It works on spectrograms of EEG signal segments. The second model depends on a CNN with three layers. It also works on spectrograms. On the other hand, the third model depends on Phase Space Reconstruction (PSR) to eliminate the limitations of the spectrograms used in the first models. A five-layer CNN is used with this strategy. The advantage of the PSR is the direct projection from the time domain, which keeps the main trend of different signal activities. The third model deals with all signal activities, and it was tested for all patients of the CHB-MIT dataset. It has a superior performance compared to the first models and the state-of-the-art models.

Maternal Human Immunodeficiency Virus (HIV) Drug Resistance Is Associated With Vertical Transmission and Is Prevalent in Infected Infants.

BACKGROUND: We aimed to assess if maternal human immunodeficiency virus (HIV) drug resistance is associated with an increased risk of HIV vertical transmission and to describe the dynamics of drug resistance in HIV-infected infants. METHODS: This was a case-control study of PROMISE study participants. "Cases" were mother-infant pairs with HIV vertical transmission during pregnancy or breastfeeding and "controls" were mother-infant pairs without transmission matched 1:3 by delivery date and clinical site. Genotypic HIV drug resistance analyses were performed on mothers' and their infants' plasma at or near the time of infant HIV diagnosis. Longitudinal analysis of genotypic resistance was assessed in available specimens from infants, from diagnosis and beyond, including antiretroviral therapy (ART) initiation and last study visits. RESULTS: Our analyses included 85 cases and 255 matched controls. Maternal HIV drug resistance, adjusted for plasma HIV RNA load at infant HIV diagnosis, enrollment CD4 count, and antepartum regimens, was not associated with in utero/peripartum HIV transmission. In contrast, both maternal plasma HIV RNA load and HIV drug resistance were independent risk factors associated with vertical transmission during breastfeeding. Furthermore, HIV drug resistance was selected across infected infants during infancy. CONCLUSIONS: Maternal HIV drug resistance and maternal viral load were independent risk factors for vertical transmission during breastfeeding, suggesting that nevirapine alone may be insufficient infant prophylaxis against drug-resistant variants in maternal breast milk. These findings support efforts to achieve suppression of HIV replication during pregnancy and suggest that breastfeeding infants may benefit from prophylaxis with a greater barrier to drug resistance than nevirapine alone.

A Multi-Point Surveillance for Antimicrobial Resistance Profiles among Clinical Isolates of Gram-Negative Bacteria Recovered from Major Ha'il Hospitals, Saudi Arabia.

The devastating nosocomial resistance is an on-going global concern. Surveillance of resistance is crucial for efficient patient care. This study was aimed to conduct a surveillance in four major Ha'il Hospitals from September to December 2020. Using a multipoint program, records of 621 non-duplicate Gram-negative cultures were tested across 21 drugs belonging to different categories. Major species were Klebsiella pneumoniae (n = 187, 30%), E. coli (n = 151, 24.5%), Pseudomonas aeruginosa, (n = 84, 13.6%), Acinetobacter baumannii (n = 82, 13.3%), and Proteus mirabilis (n = 46, 7%). Based on recent resistance classifications, A. baumanni, P. aeruginosa, and enteric bacteria were defined as pan-resistant, extremely resistant, and multi-drug resistant, respectively. A. baumannii (35%) and K. pneumoniae (23%) dominated among coinfections in SARS-CoV2 patients. The "other Gram-negative bacteria" (n = 77, 12.5%) from diverse sources showed unique species-specific resistance patterns, while sharing a common Gram-negative resistance profile. Among these, Providencia stuartii was reported for the first time in Ha'il. In addition, specimen source, age, and gender differences played significant roles in susceptibility. Overall infection rates were 30% in ICU, 17.5% in medical wards, and 13.5% in COVID-19 zones, mostly in male (59%) senior (54%) patients. In ICU, infections were caused by P. mirabilis (52%), A. baumannii (49%), P. aeruginosa (41%), K. pneumoniae (24%), and E. coli (21%), and most of the respiratory infections were caused by carbapenem-resistant A. baumannii and K. pneumoniae and UTI by K. pneumoniae and E. coli. While impressive IC, hospital performances, and alternative treatment options still exist, the spread of resistant Gram-negative bacteria is concerning especially in geriatric patients. The high selective SARS-CoV2 coinfection by A. baumannii and K. pneumoniae, unlike the low global rates, warrants further vertical studies. Attributes of resistances are multifactorial in Saudi Arabia because of its global partnership as the largest economic and pilgrimage hub with close social and cultural ties in the region, especially during conflicts and political unrests. However, introduction of advanced inter-laboratory networks for genome-based surveillances is expected to reduce nosocomial resistances.

Mid-thigh circumference as an indicator of nutritional status to predict adverse pregnancy outcomes among HIV-infected and HIV-uninfected women in Malawi.

BACKGROUND: High rates of adverse pregnancy outcomes globally raise the need to understand risk factors and develop preventative interventions. The Pregnancy Outcomes in the Era of Universal Antiretroviral Treatment in Sub-Saharan Africa (POISE Study) was a prospective, observational cohort study conducted from 2016 to 2017 in Blantyre, Malawi. We examine the associations between indicators of nutritional status, specifically mid-thigh circumference (MTC) and body-mass index (BMI), and adverse pregnancy outcomes, low birth weight (LBW), preterm birth (PTB), and small-for-gestational age (SGA), in a cohort of HIV-infected and HIV-uninfected women. METHODS: Sociodemographic, clinical, laboratory, and maternal height, weight and MTC data were collected immediately before or after delivery at the Queen Elizabeth Central Hospital (QEHC) and 4 affiliated health centers in Blantyre, Malawi. LBW was defined as birth weight < 2.5 kg; PTB as gestational age < 37 weeks using Ballard score; and SGA as birth weight < 10th percentile for gestational age. Descriptive, stratified, and multivariable logistic regression were conducted using R. RESULTS: Data from 1298 women were analyzed: 614 HIV-infected and 684 HIV-uninfected. MTC was inversely associated with LBW (adjusted odds ratio [aOR] = 0.95, p = 0.03) and PTB (aOR 0.92, p < 0.001), after controlling for HIV status, age, socioeconomic status and hemoglobin. The association between MTC and SGA was (aOR 0.99, p = 0.53). Similarly, higher BMI was significantly associated with lower odds of PTB (aOR 0.90, p < 0.001), LBW (aOR 0.93, p = 0.05), and SGA (aOR 0.95, p = 0.04). CONCLUSIONS: We observed an inverse relationship between MTC and adverse pregnancy outcomes in Malawi irrespective of HIV infection. MTC performs comparably to BMI; the ease of measuring MTC could make it a practical tool in resource-constrained settings for identification of women at risk of adverse pregnancy outcomes.

Deep convolutional neural networks for COVID-19 automatic diagnosis.

This article is mainly concerned with COVID-19 diagnosis from X-ray images. The number of cases infected with COVID-19 is increasing daily, and there is a limitation in the number of test kits needed in hospitals. Therefore, there is an imperative need to implement an efficient automatic diagnosis system to alleviate COVID-19 spreading among people. This article presents a discussion of the utilization of convolutional neural network (CNN) models with different learning strategies for automatic COVID-19 diagnosis. First, we consider the CNN-based transfer learning approach for automatic diagnosis of COVID-19 from X-ray images with different training and testing ratios. Different pre-trained deep learning models in addition to a transfer learning model are considered and compared for the task of COVID-19 detection from X-ray images. Confusion matrices of these studied models are presented and analyzed. Considering the performance results obtained, ResNet models (ResNet18, ResNet50, and ResNet101) provide the highest classification accuracy on the two considered datasets with different training and testing ratios, namely 80/20, 70/30, 60/40, and 50/50. The accuracies obtained using the first dataset with 70/30 training and testing ratio are 97.67%, 98.81%, and 100% for ResNet18, ResNet50, and ResNet101, respectively. For the second dataset, the reported accuracies are 99%, 99.12%, and 99.29% for ResNet18, ResNet50, and ResNet101, respectively. The second approach is the training of a proposed CNN model from scratch. The results confirm that training of the CNN from scratch can lead to the identification of the signs of COVID-19 disease.