In Lesotho he organised guerrilla operations of the MK in South Africa. By 1982, Hani had become prominent enough that he was the target of assassination attempts, and he eventually moved to the ANC's headquarters in Lusaka, Zambia. As head of Umkhonto we Sizwe, he was responsible for the suppression of a mutiny by dissident anti-Communist ANC members in detention camps, but denied any role in abuses including torture and murder.[4] Many MK female operatives like Dipuo Mvelase adored Chris Hani for having protected women's rights and caring about their wellbeing at military camps.[7]
The Steering Group paid special attention to the integration of DECIDE-AI within the broader scheme of AI guidelines (for example, TRIPOD-AI, STARD-AI, SPIRIT-AI and CONSORT-AI). It also focused on DECIDE-AI being applicable to all types of decision support modalities (that is, detection, diagnostic, prognostic and therapeutic). The final checklist should be considered as minimum scientific reporting standards and does not preclude reporting additional information, nor are the standards a substitute for other regulatory reporting or approval requirements. The overlap between scientific evaluation and regulatory processes was a core consideration during the development of the DECIDE-AI guideline. Early-stage scientific studies can be used to inform regulatory decisions (for example, based on the stated intended use within the study) and are part of the clinical evidence generation process (for example, clinical investigations). The initial item list was aligned with information commonly required by regulatory agencies, and regulatory considerations are introduced in the E&E paragraphs. However, given the somewhat different focuses of scientific evaluation and regulatory assessment34, as well as differences between regulatory jurisdictions, it was decided to make no reference to specific regulatory processes in the guideline, nor to define the scope of DECIDE-AI within any particular regulatory framework. The primary focus of DECIDE-AI is scientific evaluation and reporting, for which regulatory documents often provide little guidance.
PDF Being Chris Hanis 33
Current research supports the recommendation for regular physical activity (PA) during pregnancy, as it has been shown to reduce excessive gestational weight gain, and associated complications such as gestational diabetes mellitus (da Silva et al. 2016) and preeclampsia (Aune et al. 2014). Excessive gestational weight gain in particular appears to have an adverse effect on maternal health risk and cardiovascular outcomes later in life. Women with a high gestational weight gain have a greater risk of being overweight postpartum (Fraser et al. 2011), and maternal overnutrition during pregnancy may put the fetus at risk of macrosomia and later life obesity through influencing appetite and metabolism (Catalano and Ehrenberg 2006). Therefore, physical activity interventions during pregnancy may have the opportunity to break the obesity cycle in current and future generations (Catalano and Ehrenberg 2006).
Although a greater proportion of black than non-black South African women had ER-negative or TRN breast cancer, in all racial groups in this study breast cancer was predominantly ER-positive and was being diagnosed at earlier stages over time. These observations provide initial indications that late-stage aggressive breast cancers may not be an inherent feature of the breast cancer burden across Africa.
ER, PR, and HER2 distributions are shown in Table 2, and both crude and adjusted risk ratios for an ERN, PRN, and HER2P tumor associated with other clinical characteristics are provided in Table 3. The greatest ERN and PRN differences occurred with tumor grade: a fourfold greater risk of the tumor being ERN existed if it was grade 3 compared with grade 1 (Table 3). Higher grade was also, but less strongly, associated with an increased risk of HER2P status. Similar to tumor grade, stage III and IV tumors were almost 2 times more likely to be ERN and PRN, but stage was less strongly associated with HER2 status (Table 2). Consequently, both higher grade and later stage were strongly associated with the combined subtype. HER2P-enriched (66%) and 58% of TRNs were diagnosed at stages III/IV compared with 47% of luminal A tumors. Both HER2P-enriched and TRN subtypes had >60% grade 3 tumors, compared with 28% of luminal A.
After adjusting for age, year, and stage, nonblack women had a 39% lower risk of having an ERN tumor, a 29% lower risk of a PRN tumor compared with black patients, but no significant difference in HER2 status (Table 3). Compared with 11% of tumors that were HER2P enriched and 20% TRNs in black breast cancer patients, corresponding values were 5% and 13% in white, 8% and 10% in colored, and 5% and 16% in Asian women (Table 2). After adjusting for age and stage, nonblack women had approximately half the odds of a HER2 tumor compared with having a luminal A tumor (OR, 0.40 (0.17 to 0.96) and half the odds of a TRN tumor (OR, 0.47, 0.24 to 0.89) than did black women (Table 4). These differences were also present before adjustment for age and stage, because nonblack and black women did not differ in age at diagnosis (mean ages, 54.1 years (SD, 13.3) and 55.3 (SD, 14.6) respectively, P = 0.36) and stage at diagnosis (percentages diagnosed at stages I/II, III, and IV being 47.0, 42.7, and 10.3 in nonblack and 46.4, 45.1, and 8.5 in black women; P = 0.74).
Age-at-diagnosis distributions by subtype are shown in Figure 2 among black patients. ERP, PRP, and HER2P tumors all had peak incidences in the middle to late forties and a slight dip in the mid-fifties, indicating deceleration of the rate of increase of the underlying incidence rates. A dome-shaped distribution was found for luminal A tumors, and peaks followed by troughs for luminal B, HER2P enriched, and TRNs. Median age at diagnosis was youngest for luminal B tumors (49.6 years that is, >5 years younger than for luminal A tumors (55.0 years)). HER2P tumors were also diagnosed at younger ages than were TRN tumors. These arise from the trend of older age associated with a lower risk of being HER2P (Table 3), whereas age was not strongly associated with ER or PR status. 2ff7e9595c
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