Аннотация
Dear Editor, We read the article titled “Equipment Preparedness for Neonatal Resuscitation in Neonatal Intensive Care Unit in a resource-limited setting: cross-sectional study” by Hassen et al.1. This hospital-based study included 210 neonates admitted to the neonatal intensive care unit (NICU) at a comprehensive specialized hospital in a low-income country (LIC) with limited resources. Only 12.72% of the observations had complete equipment preparation, whereas 52.8% and 34.45% had minor and severe defects, respectively. The authors1 highlighted severe defects in equipment preparation (42.46%), radiant warmer setups (40%), and resuscitation medications (12.5%). Subsequently, conclusions were drawn regarding the insufficiency of the overall equipment preparation in the NICU and the need to improve equipment preparation for neonatal resuscitation and stabilization. Recommendations included the necessity to enhance equipment preparedness for neonatal resuscitation and to establish uniform guidelines for the staff of the NICUs. We fully agree with the authors1 on the importance of the duty staff’s high-quality equipment, resuscitation medications, and preparations and the need for uniform guidelines in all NICUs, especially in resource-limited settings. This study’s findings demonstrate the urgent need for these measures. It is important to note that the hospitals of the sample collected in this study were not specified, which could have affected the validity of the results1. However, this issue should be addressed in future studies. Another aspect of this problem is that when countries with dramatically different levels of poverty and richness exist worldwide, improvements in the management of NICUs alone are insufficient to decrease the neonatal mortality rate (NMR) substantially. For example, it is complicated to establish high-quality care for mothers and children in LICs when there is high corruption, permanent local fighting, violence, and destroyed healthcare management. These socio-economic factors significantly affect the availability and quality of healthcare services, making them a complex issue that requires comprehensive solutions. We analyzed routine equipment preparedness for neonatal resuscitation in NICUs in secondary (rural) and tertiary (urban) care hospitals in Kazakhstan (KZ) using the neonatal resuscitation clinical guideline equipment checklist provided in the original article1. Independent of care level (tertiary/secondary), hospitals had high-quality equipment and all medications necessary for neonatal resuscitation and stabilization. Duty staff, including physicians (neonatologists and resuscitators) and nurses, were responsible for preparing the equipment for neonatal resuscitation in the delivery room and NICUs. Subsequently, the neonatal mortality rate (NMR) has substantially decreased compared with historical data since 19912, when Kazakhstan (KZ) declared independence. We raised the question of whether KZ, with its advancements in NICU care and modern electronic healthcare management, could achieve NMR comparable to that of high-income countries (HICs). To address this query, we conducted a comparative analysis of the dynamic changes in NMR and gross domestic product (GDP) per capita metrics across KZ, Ethiopia (ET), Pakistan (PAK), Somalia (SO), Belgium (BE), and Luxembourg (LUX) between 2010 and 2023. Our data, sourced from the Macro Trends research platform2, were analyzed using GraphPad Prism version 8.4.2, employing two-way ANOVA and Tukey’s multiple comparisons test, followed by correlation analysis using a two-tailed Pearson’s test at the alpha level (0.05). ET was included as the country of origin by the authors1, PAK because of the high level of NMR in this Asian largest country, and SO as the country with the lowest GDP per capita among the LICs with limited resource settings2. Analogous parameters of BE and LUX were used to determine the lowest NMRs among HICs, depending on the high levels of GDP per capita when the metrics of this parameter reached a substantial gap between these countries. A two-way ANOVA of the overall results revealed significant impacts on the dynamics of the NMRs attributed to both country and time (P<0.0001). In contrast, the GDP per capita metrics were more significantly influenced by the countries’ impact (P<0.0001) than by temporal variations (P=0.0154). Generally, a substantially decreased NMR curve was observed in LICs, as illustrated graphically (Fig. 1, A), while the trajectory of KZ showed a slight decline, reaching a plateau in 2018 and persisting until 2023. Conversely, HICs exhibited relatively stable NMRs throughout the study period, although the separately analyzed NMR metrics of HICs demonstrated a significant time impact (P=0.0026) without country influence (P=NS).Figure 1: Infant mortality rate per 1000 live births (A) and grand domestic product (GDP) per capita (B) metrics in Belgium (BE), Luxembourg (LUX), Ethiopia (ET), Kazakhstan (KZ), Pakistan (PAK) and Somalia (SO) between 2010 and 2023 years (www.macrotrends.net).The curve of GDP per capita metrics in USD demonstrated considerable fluctuations (Fig. 1, B), with LUX registering the highest ranges (between 105.462 and 133.711), followed by BE (41.008–51.850), KZ (7.714–13.891), PAK (1.012–1.621), ET (0.335–1.129), and the lowest metrics in SO (0.000–0.775). Statistically significant disparities were evident in GDP per capita metrics between HICs and LICs (P<0.0001), as well as in KZ metrics significantly differing from those of all other nations (P<0.0001). Tukey’s multiple comparisons of NMRs between BE and LUX revealed no significant differences (P=NS) for all periods analyzed since 2010 (Table 1). This finding suggests that NMRs in high-income countries (HICs) are relatively stable and not significantly different. Conversely, highly significant differences were observed comparing NMRs between the LICs (P<0.0001: ET vs. PAK; ET vs. SO; PAK vs. SO). NMRs’ trajectory dynamics in KZ were significantly higher than those in HICs and lower than in LIC (P<0.0001). Although the NMRs have decreased in these LICs since 2010, they have remained markedly elevated in Somalia and Pakistan (see Fig. 1, A). The NMR dynamics in ET were lower than those in the other two LICs but higher than those in KZ (P<0.0001). This finding highlights the need for continued efforts to improve neonatal care in LICs and middle-income countries (MICs), particularly in countries where NMR has plateaued. Table 1 - Statistical comparisons of annual parameters of neonatal mortality rate (NMR) and the gross domestic product (GDP) per capita metrics in Belgium (BE), Luxembourg (LUX), Ethiopia (ET), Kazakhstan (KZ), Pakistan (PAK) and Somalia (SO) between 2010 and 2023 years using two-way ANOVA with Tukey’s multiple comparisons test. Data received from www.macrotrends.net/global-metrics/countries/. Statistical comparisons Analyzed period, years Metrics Countries 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 NMR per 1000 live births KZ vs. HIC 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 KZ vs. LIC 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 BE vs. LUX NS NS NS NS NS NS NS NS NS NS NS NS NS NS ET vs. PAK 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 ET vs. SO 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 PAK vs. SO 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 GDP per capita KZ vs. HIC 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 KZ vs. LIC 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 BE vs. LUX 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 ET vs. PAK NS NS NS NS NS NS NS NS NS NS NS NS NS NS ET vs. SO NS NS NS NS NS NS NS NS NS NS NS NS NS NS PAK vs. SO NS NS NS NS NS NS NS NS NS NS NS NS NS NS HIC, high-income countries (BE and LUX); LIC, low-income countries (ET, PAK, SO); NS, not specified. The findings on neonatal mortality dynamics can be explained by analyzing the GDP per capita of these countries3. The highest level of GDP per capita was observed in the LUX compared to the BE (P<0.0001) and all other countries (P<0.0001) using Tukey’s multiple comparison tests (Table 1). Comparative analysis of these parameters between LUX and BE did not show any substantial impact of high GDP per capita on NMR in LUX because both countries (BE and LUX) reached the lowest level of NMR. The GDP per capita of KZ was significantly lower (P<0.0001) than that of LUX and BE and significantly higher (P<0.0001) than that of LICs (ET, PAK, and SO). The NMR of KZ was dramatically higher than that of HICs (P<0.0001) and significantly lower than that of LICs (P<0.0001). Comparisons of the GDP per capita metrics of LICs did not reveal any significant differences between these countries (P=NS: ET vs. PAK, ET vs. SO, and PAK vs. SO). Pearson analysis demonstrated a very high negative correlation between the NMRs and the GDP per capita metrics of ET (r=-0.9879) and SO (r=-0.8760), with a significant association (P<0.0001) and a high negative correlation between the PAK parameters (r=-0.7978, P=0.0010). A negative moderate correlation of the NMRs with GDP per capita metrics was found for BE (r=−0.5087) and LUX (r=−0.4808) with no significant associations (P=NS). In contrast, the metrics only in KZ were weakly correlated positively (r=0.1805) with no significant association (P=NS). In general, higher levels of NMR can be explained by the level of GDP per capita, indicating that the highest parameter of GDP per capita metrics resulted in the lowest NMR rate and vice versa. From this analysis, we found that a significantly increased gap in GDP per capita metrics (P<0.0001) between reach countries (BE vs. LUX) did not considerably change neonatal mortality dynamics (P=NS). By contrast, the lowest GDP per capita metric corresponded to a dramatically increased NMR in the SO (P<0.0001). However, there were no significant differences in GDP per capita metrics (P=NS) between SO and the other two LICs (ET and PAK). Multiple factors influence neonatal mortality in LICs when the healthcare system cannot provide efficient medical management. Therefore, further studies are needed to shed light on medical care problems in countries with low-resource settings. Guidelines for NICUs should be designed considering the possibilities of the healthcare system to provide medical care and the political, socio-economic, financial, and cultural aspects of these LICs and middle-income countries (MICs). In our opinion, a further decrease in neonatal mortality in HICs depends on the development of new medical technologies and genetic medications to treat currently incurable neonatal diseases, congenital anomalies, and fetal malformations4 as well as the prevention of preterm births5 and other complications during pregnancy and delivery, resulting in neonatal morbidity and mortality. Our analysis suggests that higher NMRs correspond to lower GDP per capita levels, highlighting the complex interplay between socio-economic factors and healthcare outcomes. Despite these significant disparities, the impact of per capita GDP on neonatal mortality dynamics varies across countries. Addressing neonatal mortality comprehensively requires tailored interventions considering socio-economic, political, and cultural contexts, particularly in LICs with insufficient settings, where healthcare challenges are multifaceted. Additionally, efforts to reduce neonatal mortality in HICs should focus on technological advancements and preventive measures to address underlying medical issues. In MICs, understanding the intricate relationship between GDP per capita and healthcare outcomes is crucial for designing effective interventions to mitigate neonatal mortality risk. Ethical approval Although ethics approval with informed consent was not required for this correspondence, we included the statement because we discussed the collected information from hospitals, which was related to the routine work of the authors and their colleagues, as mentioned in the acknowledgement section, as well as metrics of NMR and GDP per capita of several countries sourced from the Macro Trends research platform2. The South Kazakhstan Medical Academy Ethical Review Committee approved the study concerning neonatal mortality protocol N1 from 31.01.2023. Consent Although informed consent was not required for this correspondence, we included the statement that all clinical activities were performed according to the approved study protocol by the institution’s ethical committee, and signed informed consent was obtained from the children’s parents. Source of funding Not applicable. Author contribution All authors have read the original article and collectively contributed to the conceptualization, investigation, methodology, review, data curation, and interpretation of the results. L.V.A., G.E.B., S.M.T., Zh.R.K., M.M.S., K.S.I. and L.E.A. collected the data. K.S.I. supervised and validated. Zh.R.K., M.M.S., and OAM performed statistical analysis and software. O.A.M. supervised and drafted the manuscript, and all authors have read and agreed to the final version of this correspondence. Conflicts of interest disclosure The authors declared that they have no competing interests. Research registration unique identifying number (UIN) Not applicable. Guarantor Ospan A Mynbaev. Data availability statement All data generated or analyzed during this study are included in this correspondence and are available upon request. Provenance and peer review Not commissioned, externally peer-reviewed.