Risk factors for obstructed labour in Eastern Uganda: A case control study

Introduction: Obstructed labour (OL) is an important clinical and public health problem because of the associated maternal and perinatal morbidity and mortality. Risk factors for OL and its associated obstetric squeal are usually context specific. No epidemiological study has documented the risk factors for OL in Eastern Uganda. This study was conducted to identify the risk factors for OL in Mbale Hospital. Objective: To identify the risk factors for OL in Mbale Regional Referral and Teaching Hospital, Eastern Uganda. Methods: We conducted a case control study with 270 cases of women with OL and 270 controls of women without OL. We consecutively enrolled eligible cases between July 2018 and February 2019. For each case, we randomly selected one eligible control admitted in the same 24-hour period. Data was collected using face-to-face interviews and a review of patient notes. Logistic regression was used to identify the risk factors for OL. Results: The risk factors for OL were, being a referral from a lower health facility (AOR 6.80, 95% CI: 4.20–11.00), prime parity (AOR 2.15 95% CI: 1.26–3.66) and use of herbal medicines in active labour (AOR 2.72 95% CI: 1.49–4.96). Married participants (AOR 0.59 95% CI: 0.35–0.97) with a delivery plan (AOR 0.56 95% CI: 0.35–0.90) and educated partners (AOR 0.57 95% CI: 0.33–0.98) were less likely to have OL. In the adjusted analysis, there was no association between four or more ANC visits and OL, adjusted odds ratio [(AOR) 0.96 95% CI: 0.57–1.63)]. Conclusions: Prime parity, use of herbal medicines in labour and being a referral from a lower health facility were identified as risk factors. Being married with a delivery plan and an educated partner were protective of OL. Increased frequency of ANC attendance was not protective against obstructed labour.publishedVersio

Effect of pre-operative bicarbonate infusion on maternal and perinatal outcomes among women with obstructed labour in Mbale hospital: A double blind randomized controlled trial

Introduction Oral bicarbonate solution is known to improve both maternal and perinatal outcomes among women with abnormal labour (dystocia). Its effectiveness and safety among women with obstructed labour is not known. Objective To determine the effect and safety of a single-dose preoperative infusion of sodium bicarbonate on maternal and fetal blood lactate and clinical outcomes among women with obstructed labour (OL) in Mbale hospital. Methods We conducted a double blind, randomised controlled trial from July 2018 to September 2019. The participants were women with OL at term (≥37 weeks gestation), carrying a singleton pregnancy with no other obstetric emergency, medical comorbidity or laboratory derangements. Intervention A total of 477 women with OL were randomized to receive 50ml of 8.4% sodium bicarbonate (238 women) or 50 mL of 0.9% sodium chloride (239 women). In both the intervention and controls arms, each participant was preoperatively given a single dose intravenous bolus. Every participant received 1.5 L of normal saline in one hour as part of standard preoperative care. Outcome measures Our primary outcome was the mean difference in maternal venous blood lactate at one hour between the two arms. The secondary outcomes were umbilical cord blood lactate levels at birth, neonatal sepsis and early neonatal death upto 7 days postnatal, as well as the side effects of sodium bicarbonate, primary postpartum hemorrhage, maternal sepsis and mortality at 14 days postpartum. Results The median maternal venous lactate was 6.4 (IQR 3.3–12.3) in the intervention and 7.5 (IQR 4.0–15.8) in the control group, with a statistically non-significant median difference of 1.2 mmol/L; p-value = 0.087. Vargha and Delaney effect size was 0.46 (95% CI 0.40–0.51) implying very little if any effect at all. Conclusion The 4.2g of preoperative intravenous sodium bicarbonate was safe but made little or no difference on blood lactate levels.publishedVersio

Brief report: active HIV case finding in the city of Kigali, Rwanda: assessment of voluntary assisted partner notification modalities to detect undiagnosed HIV infections

BACKGROUND: Voluntary assisted partner notification (VAPN) services that use contract, provider, or dual referral modalities may be efficient to identify individuals with undiagnosed HIV infection. We aimed to assess the relative effectiveness of VAPN modalities in identifying undiagnosed HIV infections. SETTING: VAPN was piloted in 23 health facilities in Kigali, Rwanda. METHODS: We identified individuals with a new HIV diagnosis before antiretroviral therapy initiation or individuals on antiretroviral therapy (index cases), who reported having had sexual partners with unknown HIV status, to assess the association between referral modalities and the odds of identifying HIV-positive partners using a Bayesian hierarchical logistic regression model. We adjusted our model for important factors identified through a Bayesian variable selection. RESULTS: Between October 2018 and December 2019, 6336 index cases were recruited, leading to the testing of 7690 partners. HIV positivity rate was 7.1% (546/7690). We found no association between the different referral modalities and the odds of identifying HIV-positive partners. Notified partners of male individuals (adjusted odds ratio 1.84; 95% credible interval: 1.50 to 2.28) and index cases with a new HIV diagnosis (adjusted odds ratio 1.82; 95% credible interval: 1.45 to 2.30) were more likely to be infected with HIV. CONCLUSION: All 3 VAPN modalities were comparable in identifying partners with HIV. Male individuals and newly diagnosed index cases were more likely to have partners with HIV. HIV-positive yield from index testing was higher than the national average and should be scaled up to reach the first UNAIDS-95 target by 2030

Leveraging artificial intelligence and data science techniques in harmonizing, sharing, accessing and analyzing SARS-COV-2/COVID-19 data in Rwanda (LAISDAR Project):study design and rationale

Background: Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount of SARS-COV-2/COVID-19-related data have been collected including COVID-19 testing and hospital routine care data. Unfortunately, those data are fragmented in silos with different data structures or formats and cannot be used to improve understanding of the disease, monitor its progress, and generate evidence to guide prevention measures. The objective of this project is to leverage the artificial intelligence (AI) and data science techniques in harmonizing datasets to support Rwandan government needs in monitoring and predicting the COVID-19 burden, including the hospital admissions and overall infection rates.Methods: The project will gather the existing data including hospital electronic health records (EHRs), the COVID-19 testing data and will link with longitudinal data from community surveys. The open-source tools from Observational Health Data Sciences and Informatics (OHDSI) will be used to harmonize hospital EHRs through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The project will also leverage other OHDSI tools for data analytics and network integration, as well as R Studio and Python. The network will include up to 15 health facilities in Rwanda, whose EHR data will be harmonized to OMOP CDM.Expected results: This study will yield a technical infrastructure where the 15 participating hospitals and health centres will have EHR data in OMOP CDM format on a local Mac Mini (“data node”), together with a set of OHDSI open-source tools. A central server, or portal, will contain a data catalogue of participating sites, as well as the OHDSI tools that are used to define and manage distributed studies. The central server will also integrate the information from the national Covid-19 registry, as well as the results of the community surveys. The ultimate project outcome is the dynamic prediction modelling for COVID-19 pandemic in Rwanda.Discussion: The project is the first on the African continent leveraging AI and implementation of an OMOP CDM based federated data network for data harmonization. Such infrastructure is scalable for other pandemics monitoring, outcomes predictions, and tailored response planning

Leveraging artificial intelligence and data science techniques in harmonizing, sharing, accessing and analyzing SARS-COV-2/COVID-19 data in Rwanda (LAISDAR Project):study design and rationale

Background: Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount of SARS-COV-2/COVID-19-related data have been collected including COVID-19 testing and hospital routine care data. Unfortunately, those data are fragmented in silos with different data structures or formats and cannot be used to improve understanding of the disease, monitor its progress, and generate evidence to guide prevention measures. The objective of this project is to leverage the artificial intelligence (AI) and data science techniques in harmonizing datasets to support Rwandan government needs in monitoring and predicting the COVID-19 burden, including the hospital admissions and overall infection rates.Methods: The project will gather the existing data including hospital electronic health records (EHRs), the COVID-19 testing data and will link with longitudinal data from community surveys. The open-source tools from Observational Health Data Sciences and Informatics (OHDSI) will be used to harmonize hospital EHRs through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The project will also leverage other OHDSI tools for data analytics and network integration, as well as R Studio and Python. The network will include up to 15 health facilities in Rwanda, whose EHR data will be harmonized to OMOP CDM.Expected results: This study will yield a technical infrastructure where the 15 participating hospitals and health centres will have EHR data in OMOP CDM format on a local Mac Mini (“data node”), together with a set of OHDSI open-source tools. A central server, or portal, will contain a data catalogue of participating sites, as well as the OHDSI tools that are used to define and manage distributed studies. The central server will also integrate the information from the national Covid-19 registry, as well as the results of the community surveys. The ultimate project outcome is the dynamic prediction modelling for COVID-19 pandemic in Rwanda.Discussion: The project is the first on the African continent leveraging AI and implementation of an OMOP CDM based federated data network for data harmonization. Such infrastructure is scalable for other pandemics monitoring, outcomes predictions, and tailored response planning

Exploring mechanisms of excess mortality with early fluid resuscitation: insights from the FEAST trial

Background Early rapid fluid resuscitation (boluses) in African children with severe febrile illnesses increases the 48-hour mortality by 3.3% compared with controls (no bolus). We explored the effect of boluses on 48-hour all-cause mortality by clinical presentation at enrolment, hemodynamic changes over the first hour, and on different modes of death, according to terminal clinical events. We hypothesize that boluses may cause excess deaths from neurological or respiratory events relating to fluid overload. Methods Pre-defined presentation syndromes (PS; severe acidosis or severe shock, respiratory, neurological) and predominant terminal clinical events (cardiovascular collapse, respiratory, neurological) were described by randomized arm (bolus versus control) in 3,141 severely ill febrile children with shock enrolled in the Fluid Expansion as Supportive Therapy (FEAST) trial. Landmark analyses were used to compare early mortality in treatment groups, conditional on changes in shock and hypoxia parameters. Competing risks methods were used to estimate cumulative incidence curves and sub-hazard ratios to compare treatment groups in terms of terminal clinical events. Results Of 2,396 out of 3,141 (76%) classifiable participants, 1,647 (69%) had a severe metabolic acidosis or severe shock PS, 625 (26%) had a respiratory PS and 976 (41%) had a neurological PS, either alone or in combination. Mortality was greatest among children fulfilling criteria for all three PS (28% bolus, 21% control) and lowest for lone respiratory (2% bolus, 5% control) or neurological (3% bolus, 0% control) presentations. Excess mortality in bolus arms versus control was apparent for all three PS, including all their component features. By one hour, shock had resolved (responders) more frequently in bolus versus control groups (43% versus 32%, P <0.001), but excess mortality with boluses was evident in responders (relative risk 1.98, 95% confidence interval 0.94 to 4.17, P = 0.06) and 'non-responders' (relative risk 1.67, 95% confidence interval 1.23 to 2.28, P = 0.001), with no evidence of heterogeneity (P = 0.68). The major difference between bolus and control arms was the higher proportion of cardiogenic or shock terminal clinical events in bolus arms (n = 123; 4.6% versus 2.6%, P = 0.008) rather than respiratory (n = 61; 2.2% versus 1.3%, P = 0.09) or neurological (n = 63, 2.1% versus 1.8%, P = 0.6) terminal clinical events. Conclusions Excess mortality from boluses occurred in all subgroups of children. Contrary to expectation, cardiovascular collapse rather than fluid overload appeared to contribute most to excess deaths with rapid fluid resuscitation. These results should prompt a re-evaluation of evidence on fluid resuscitation for shock and a re-appraisal of the rate, composition and volume of resuscitation fluids. Trial registration: ISRCTN6985659

Age, Growth, Food, and Yield of the White Sturgeon (<i>Acipenser transmontanus</i>) of the Fraser River, British Columbia

For white sturgeon taken incidentally in the salmon gillnet fishery in the Fraser River during the summer of 1962, pectoral fin ray sections indicated that over three-quarters were fish aged 9–16 years. Gillnets for salmon apparently select sturgeon over a size range between 30 and 60 inches. Back-calculation of size attained at previous ages indicated that after attaining a length close to 20 inches by age 5, the sturgeon grow about 2 inches per year to about age 25. Limited data from pectoral fin ray sections suggest that age at first spawning is from 11 to 22 years for males, and from 11 to 34 for females. Subsequent spawning is apparently at intervals of 4–9 years. Fraser River sturgeon are more piscivorous than has been recorded for white sturgeon and other sturgeon species elsewhere, about one-half of the stomachs containing fish, especially eulachons. The age distribution in the catch, though biased by selection, was used to estimate rates of natural and fishing mortality. The eumetric fishing curve suggests that present yield could be increased by a greater size at first capture, particularly if the natural mortality rate is as low as 0.05. The history of the sturgeon fishery suggest that sustainable yield could exceed 100,000 lb per year. The commercial landings in recent years average 30,000–40,000 lb. The sport fishery may take an additional 20,000–30,000 lb. Sustained yield in the circumstances of the present fishery could be 80,000 lb per year, about 25% more than the present catch. Some recommendations are made for management, stressing the importance of protection of an annual spawning population of 300–600 females. </jats:p

Risk factors for obstructed labour in Eastern Uganda: A case control study

Introduction: Obstructed labour (OL) is an important clinical and public health problem because of the associated maternal and perinatal morbidity and mortality. Risk factors for OL and its associated obstetric squeal are usually context specific. No epidemiological study has documented the risk factors for OL in Eastern Uganda. This study was conducted to identify the risk factors for OL in Mbale Hospital. Objective: To identify the risk factors for OL in Mbale Regional Referral and Teaching Hospital, Eastern Uganda. Methods: We conducted a case control study with 270 cases of women with OL and 270 controls of women without OL. We consecutively enrolled eligible cases between July 2018 and February 2019. For each case, we randomly selected one eligible control admitted in the same 24-hour period. Data was collected using face-to-face interviews and a review of patient notes. Logistic regression was used to identify the risk factors for OL. Results: The risk factors for OL were, being a referral from a lower health facility (AOR 6.80, 95% CI: 4.20–11.00), prime parity (AOR 2.15 95% CI: 1.26–3.66) and use of herbal medicines in active labour (AOR 2.72 95% CI: 1.49–4.96). Married participants (AOR 0.59 95% CI: 0.35–0.97) with a delivery plan (AOR 0.56 95% CI: 0.35–0.90) and educated partners (AOR 0.57 95% CI: 0.33–0.98) were less likely to have OL. In the adjusted analysis, there was no association between four or more ANC visits and OL, adjusted odds ratio [(AOR) 0.96 95% CI: 0.57–1.63)]. Conclusions: Prime parity, use of herbal medicines in labour and being a referral from a lower health facility were identified as risk factors. Being married with a delivery plan and an educated partner were protective of OL. Increased frequency of ANC attendance was not protective against obstructed labour