Ez tables, figures or datasets). In this paper we fill this shortage and present corresponding numerical estimations (dataset) of the required vertical electric fields values Ez. Our dataset is valuable for comparison of the LAI-models with the electric fields observations and to contrast different LAI-coupling models with each other.Researches in the field of the lithosphere-atmosphere-ionosphere (LAI) coupling involve discussions on the physical mechanisms that might be responsible for that coupling. Hypotheses that are based on an electromagnetic physical mechanism of seismo-ionosphere disturbances generation trigger discussions on the required electric fields. Kuo and Lee [doi: 10.1002/2016JA023441] proposed and discussed an improved coupling model for the lithosphere-atmosphere-ionosphere system but did not provide any electric fields values ( Required seismogenic electric currents data are taken according to Ref. Ez variations for a characteristic cross-section plane (top panel) and at specific altitudes (bottom plane).The proposed dataset is a modelled dataset that is not linked to any specific Earth's locations. 2in-situ seismogenic electric currents are the worst known ones. The representation of those data is expected to facilitate the analysis and is desirable to be unambiguous and explicit.Unresolved strong earthquakes prediction problem triggered multiple interdisciplinary attempts to build self-consistent models that describe lithosphere-atmosphere-ionosphere (LAI) coupling. Those relying on an electromagnetic LAI-coupling usually require either (1) significantly enhanced electric conductivity values near the ground at the bottom part of the electric conductivity profile or (2) very intense electric field. To consistently explain the items above or to provide a complete qualitative model that does not rely on significant electric conductivity or electric fields modifications is a challenge nowadays for the electromagnetic LAI-coupling  that correspond to their simulated data on ground-to-ionosphere electric currents of seismic origin. In the supporting information file only Ez data recalculation, paper Ez values. We must note that Ez data are among the first ones to validate when deal with electromagnetic LAI-coupling models. A validation usually includes Ez data comparison with a few known reference entities . A contrast with other electromagnetic LAI-coupling models often reveal principal similarities and divergences, thus, allowing to highlight model's advances and to reveal principle challenges to solve.Unfortunately, researchers To facilitate the aforementioned opportunities, we re-calculate vertical electric fields from (1) the original electric currents data jz, jy, jz of electric currents densities (in units of A/km2), position  and corresponding grid number .In this paper we utilize as input the dataset Ez, we utilize the following analytical formulation of the electric conductivity profile according to the equation 8 in paper 0 is the conductivity at z = 0 km , σ0 = 2∙10−14 S/m, and hz = 6 km is the conductivity scale height.To calculate vertical electric field values It is clear that in the formulation 1 the electric conductivity σ is a scalar function. It is also clear that the given conductivity formula does not depend on the x or y co-ordinates. Corresponding altitudinal variation of the electric conductivity profile is illustrated in Ez dataset, we use the Ohm's law which, given the conductivity is a scalar and electric currents are curl-free, has the following form:Jz is the vertical electric current density.To calculate the vertical electric fields Ez dataset is obtained according to the equation Ez spatial distribution are illustrated in Described in this paper vertical electric fields Ez dataset and the source code as Jupyter (formerly known as IPython) notebooks at gitlab public repository (see URL in the specification table) to make our results reproducible by other researchers and to facilitate further analysis and discussions. To re-use the notebooks one will need Jupyter with Python3 and SciPy, NumPy, and matplotlib packages installed. It allows data investigation with opensource and free software without the need for a proprietary data formats and software preventing the so called “vendor lock-in”, thus, facilitating scientific collaboration and making the data easier to find, re-use and validate. Our data representation is suitable for use as input parameters to other models that require electric fields values in the considered spatial domain. It is also suitable for cross-comparison with other models' data and observations .We published the vertical electric fields 2.1Ez we assume that all the following conditions are met:-Electric currents are purely conductivity currents, i.e. they are due to the conduction only;-All transitional processes have passed, i.e. the currents are steady-state currents;-Vertical profile of the electric conductivity is a scalar function of an altitude.To re-calculate ground-to-ionosphere vertical electric fields Ez data from the Earth's ground (0 km) up to the 40–50 km above the Earth's surface although the dataset upper boundary is 130 km to meet the data domain in Ref. Ez data in the ionosphere  where the electric conductivity becomes a tensor.Due to the above, it is reasonable to analyze the calculated this way vertical electric fields


A recent cohort study among Papua New Guinean women surprisingly showed iron deficiency during pregnancy to be associated with increased birth weight. These findings seemingly contradict previous trial evidence that iron supplementation leads to increased birth weight, particularly in iron-deficient women, and hence require explanation.We have re-analysed data from a previous trial in Kenya and demonstrated that, because women who were initially iron deficient respond better to iron supplementation, they show an increase in birthweight. There is evidence that this benefit is decreased in iron-replete women, possibly due to the adverse effects of haemoconcentration that can impair oxygen and nutrient transfer across the placenta. The Papua New Guinean results might be explained by a similar differential response to the iron supplements that they all received.Antenatal iron supplementation should ideally be administered in conjunction with measures to prevent, diagnose and treat malaria given the propensity of pathogenic microorganisms to proliferate in iron-supplemented individuals. However, even where services to prevent and treat malaria are poor, current evidence supports the conclusion that the benefits of universal iron supplementation outweigh its risks.https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-018-1146-z.Please see related article: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-019-1376-8.Please see related article: The online version of this article (10.1186/s12916-019-1375-9) contains supplementary material, which is available to authorized users. A recent cohort study in Papua New Guinean pregnant women reported an association between iron deficiency (ferritin concentration < 15 μg/L) and higher birth weight by 230 g), particularly among primigravidae [30 g, parThe WHO recommendation was based on a meta-analysis of randomised trials in which antenatal iron supplementation was suggested to lead to a slight increase in birth weight  [Plasmodium infection. These markers were used to calculate the body iron index, i.e. the natural logarithm of the ratio of the adjusted ferritin concentration to the adjusted transferrin receptor concentration. This quantitative indicator has been shown to be linearly associated with the size of the body iron store in iron-replete individuals, and with the size of the functional deficit that would need to be corrected before iron could again be accumulated in the store in an iron-deficient individual. Multiple fractional polynomial regression analysis showed that the birth weight response to administered iron decreased with initial iron status . All women in the study were prescribed daily supplementation with iron and folic acid. Consistent with our findings in Kenyan women, iron-supplemented women who were initially iron deficient had newborns with a higher birth weight than their peers who were initially iron replete. What could explain this phenomenon?In normal pregnancies, plasma volume expansion leads to a gradual reduction in haemoglobin concentration and haematocrit levels in the gestational age period between 7 and 36 weeks, despite concurrent increases in the total erythrocyte and haemoglobin mass . This haIn iron-deficient women, haemodilution without an adequate supply of iron to the developing erythrocyte and haemoglobin mass will likely result in placental insufficiency, leading to low birth weight and prematurity. This may explain the negative association that we found between iron status and birthweight in women who were not supplemented with iron  without an apparent effect on P. falciparum infection risk [There is ample evidence that iron supplementation predisposes towards the proliferation of pathogenic microorganisms. In vitro studies indicate that asexual blood stages of ividuals , 9. Thesothelium , thus avion risk .Randomised trials offer superior methodology and should be given higher priority in the hierarchy of evidence than cohort studies because they minimise the risk of selection bias. Benefits of universal iron supplementation in pregnancy are likely to vary with the prevalence of iron deficiency  and are Plasmodium infection may also improve the absorption of non-haem iron from supplements or dietary sources [Antenatal malaria prevention not only results in direct health benefits to mothers and neonates, but has the additional advantage that elimination of inflammation associated with chronic  sources .The efficacy and coverage of preventive measures against malaria in pregnancy are generally low. For example, among African countries that reported on intermittent preventive treatment in pregnancy in 2016, only 19% received the recommended minimum of three doses of intermittent preventive treatment . It seemAdditional file 1:Methods to assess the influence of maternal body iron status at baseline (i.e. second trimester of pregnancy) on the magnitude of the effect of antenatal iron supplementation on neonatal birth weight. (DOCX 19 kb)


APO activates D1, D2S, D2L, D3, D4, and D5 receptors (and is thus classified as a non-selective dopamine agonist), serotonin receptors , and α-adrenergic receptors . In veterinary medicine, APO is used to induce vomiting in dogs, an important early treatment for some common orally ingested poisons . In human medicine, it has been used in a variety of treatments ranging from the treatment of addiction , for treatment of erectile dysfunction in males and hypoactive sexual desire disorder in females to the treatment of patients with Parkinson's disease (PD). Currently, APO is used in patients with advanced PD, for the treatment of persistent and disabling motor fluctuations which do not respond to levodopa or other dopamine agonists, either on its own or in combination with deep brain stimulation. Recently, a new and potentially important therapeutic role for APO in the treatment of Alzheimer’s disease has been suggested; APO seems to stimulate Aβ catabolism in an animal model and cell culture, thus reducing the rate of Aβ oligomerisation and consequent neural cell death.Apomorphine  Phosphodiesterase inhibitors  reduce the breakdown of cGMP by phosphodiesterase 5 [The intracellular second messengers that mediate smooth muscle relaxation are cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP). Intracellular NO increases the production of cGMP by stimulating the guanylyl cyclase enzyme. Intracellular concentration of cAMP is increased by increased binding of prostaglandin Eterase 5 ,40,43,44s.l.) formulation, that maintained the erectogenic function while decreasing adverse events, enabled its use in human medicine [1 and D2) in the hypothalamus and is effective as a precoital s.l. agent. A European multicentre study on 507 patients (254 received APO and 253 a placebo) with ED, evaluated the tolerability of s.l. APO in a forced dose-escalation regimen. The conclusion of the study was that the use of s.l. APO is safe and well tolerated by the patients. Adverse effects were not treatment limiting. The risk/benefit ratio analysis supported APO as a safe and effective alternative in managing ED [without effect”. The most often reported clinical adverse effects in this study were headache and nausea [APO has long been known as an erectogenic agent but only the development of a sublingual  is the most common neurodegenerative disease in human characterized by a progressive and irreversible loss of cognitive functions ,52,53. TIn human, the amyloid precursor protein (APP) is a single-pass transmembrane protein with a large transmembrane domain. The physiological significance of APP is not fully understood although APP production in the mature, normal CNS is substantial . APP is Attached to the cell membrane, APP can be proteolyzed by two competing pathways that generate either senile plaque-promoting byproducts or non-senile plaque-promoting byproducts. The enzyme α-secretase breaks down mature APP into a soluble peptide APPα and an 83-amino acid membrane bound C-terminal fragment (83-CTF). The soluble APPα diffuses into the extracellular space and the 83-CTF is further proteolyzed into a p3 peptide. The alternative, senile plaque promoting pathway, involves first the breakdown of APP with β-secretase—generating a soluble APPβ peptide and a 99-amino acid membrane bound C-terminal fragment (99-CTF) − and then proteolysis of the 99-CTF with γ-secretase into a APP intracellular domain fragment (APP-ICD) and a neurotoxic 37–44 amino acid Aβ peptide.An alternative fate for the membrane bound APP is its reinternalisation into endosomes containing the β- and γ-secretases leading to the intracellular production of Aβ. This fraction of the Aβ peptide is exported to the extracellular space (via vesicular transport) or degraded in lysosomes. . Reinter2O2 and O2−, that oxidize prostaglandins forming F2α-isoprostanes. H2O2 and F2α-isoprostanes accelerate aggregation of Aβ [Accumulation of soluble and unfolded monomers of Aβ peptides promotes their conformational change, formation of oligomers and aggregation of fibrils. The final stage of Aβ peptide assembly in the extracellular space is the formation of amyloidal plaques in the gray matter of the brain. Aβ42 monomers with intermediate conformations and Aβ42 oligomers are assumed to be the most potent neurotoxins while the amyloid plaques are supposed to be relatively inert ,67. Aβ aon of Aβ ,70.2O2 induced, p53 mediated apoptosis [The presence of extracellular Aβ42 leads to an increase in intracellular Aβ42 ,71,72. Ipoptosis ,74,75,76poptosis . The locpoptosis ,78,79,80Patients with AD can accumulate senile plaques in their brains for decades before the onset of the first symptoms of cognitive impairment . There a1-antichymotrypsin ACT [Tau is a phosphoprotein that interacts with tubulin to promote tubulin assembly into microtubules and also promotes microtubule stability. Tau is abundant in neurons of the CNS and also expressed at very low levels in astrocytes and oligodendrocytes.. Tau actpsin ACT ,85,86,87An important contributing factor to the development of AD could be oxidative stress—an imbalance between the production and inactivation of ROS—that is supposed to contribute to age-related changes in the brain . Oxidati2O2 toxicity a finding that has been confirmed in experiments with a human neuroblastoma cell line [The potential, therapeutic effects of APO were studied in the triple transgenic AD mouse model 3xTg-AD and on cultured cells SH-SY5Y . Himeno ell line . The actell line . A dose 4 receptors was reported to inhibit oxidative stress-induced nerve cell death [2, D3 and D4 receptors [APO is a well-known non-selective dopamine agonist and has also a potent antioxidant effect. Therefore, the reported beneficial effects of APO on AD could be mediated by dopamine receptor-dependent or dopamine receptor-independent mechanisms. Activation of dopamine Dll death . The synll death . Howevereceptors  and APO eceptors . TherefoThe hypothetical, AD-protective dopamine-independent effects of APO, supported by direct or indirect experimental evidence, are increased intracellular degradation of Aβ40 and Aβ42 , protects.c. infusion. This would suggest that APO treatment would be practical only for people with early sings of AD. Also, as mentioned previously, the cost of APO treatment by s.c. infusion is not insignificant but could be reduced by economies of scale if there is an increased demand.The potential of APO for treatment of AD will be further enhanced by supportive data from independent laboratories. Assuming the exciting results reported by Himeno and coworkers will be confirmed, there are many questions that have to be answered before APO can be certified for treatment of AD. The APO doses that had an anti-AD effect in cell cultures and in mouse models  were aboThe beneficial actions of APO treatment are dopamine-receptor mediated or non-dopamine-receptor mediated. The dopamine-receptor mediated effects are put to an effective use for the treatment of persistent and disabling motor fluctuations in patients with advanced Parkinson’s disease. The recently reported, non-dopamine-receptor mediated effects of APO treatment, in an animal model, suggest a new and potentially important therapeutic role for APO in the treatment of Alzheimer’s disease.


Background: Birth is a traumatic event with molding forces directed to the fetal skull, which may result in intracranial hemorrhages. However, the knowledge on prevalence and risk factors of incidental brain magnetic resonance imaging (MRI) findings in infants is still inconclusive.Methods: The prevalence and nature of incidental MRI findings were assessed in a birth cohort of 175 asymptomatic infants. The role of delivery method as well as other potential risk factors for intracranial hemorrhages were evaluated. The infants underwent 3T MRI at the age of 2–5 weeks, and the neurological status of the infants with an incidental finding was evaluated by a pediatric neurologist. Information on the delivery method, duration of delivery, parity, used anesthesia, oxytocin induction, and Apgar score was gathered to evaluate their association with the prevalence of hemorrhages.Results: Incidental intracranial hemorrhages were detected in 12 infants (6.9%), all following spontaneous or assisted vaginal delivery. Vacuum-assistance was found to be a risk factor for subdural hemorrhages with an odds ratio (OR) of 4.7 . All infants were evaluated to develop normally by their clinical status.Conclusions: Incidental intracranial hemorrhages are relatively common among infants born by vaginal delivery. They are often of little clinical significance within the first years of life and have unlikely consequences for later neurodevelopment either. Despite their benign character, investigators should be prepared to share this information with parents competently as the findings can cause parental anxiety, and especially as the popularity of MRI as a research tool is increasing. Incidental intracranial hemorrhages are common findings in neonatal magnetic resonance imaging (MRI). This is not surprising given the remarkable molding and deformation of the fetal head in the birth canal , 2. DespThe estimated prevalence of intracranial hemorrhages in term asymptomatic healthy newborn populations deviate greatly from 8.1 to 46% in previous studies –5. SubduNeonatal intracranial hemorrhages may appear in multiple locations , 4. Subdn = 88 and n = 111) reported that none of the infants born by cesarean (c-) section had hemorrhages (n = 101) reported a relatively high prevalence in the c-section group (18%)  . One stuup (18%) .Incidental findings in MR images seldom have major clinical significance, but as they are common , they alTo these ends, we measured the prevalence of incidental brain imaging findings in healthy infants, characterized the findings e.g., according to their location, evaluated their association with obstetric factors, and assessed their possible effects on neurological development during infancy.This study was reviewed and approved by the Ethics Committee of the Hospital District of Southwest Finland and performed in accord with the Declaration of Helsinki.www.finnbrain.fi; , scoring <5 in the 5 min Apgar score; previously diagnosed central nervous system anomaly, an abnormal finding in any previous MRI scan or birth weight <1,500 g. The participating infants were full-term . All were born from singleton pregnancies.www.thl.fi), and included information on duration and mode of delivery, gestational age, use of anesthetics or oxytocin induction during delivery, mother's parity, possible episiotomy, gestational age at birth, child Apgar scores (1 min and 5 min), head circumference, birth weight, birth height and pH of the umbilical blood, among other data that were filled in by the medical staff following delivery at the hospital. Mode of delivery was categorized into (a) vaginal, (b) assisted deliveries (vacuum-assistance), and (c) c-sections (elective or emergency). With anesthetics, two categories were formed: (1) epidural and spinal anesthesia and their combinations and (2) all other anesthetic forms or no pain alleviation. Episiotomy is not a routinely performed procedure during delivery in Finland, as it is in some countries. It was included as one of the obstetric variables as it was considered to be an indirect indicator of increased pressure on the fetus during the second stage of labor.Obstetric data were gathered from the Finnish Medical Birth Register of the National Institute for Health and Welfare  at age 2–5 weeks, calculated from the due date, at the Turku University Hospital. Upon arrival, an experienced radiographer went through the study protocol with the parents and confirmed the lack of contraindications for the scan. Before the scan, the infants were fed with (breast) milk to help them to sleep and then swaddled into a vacuum mattress to reduce possible limb movement. The scan was performed without anesthetics, and the children were provided with sufficient hearing protection (infant ear wax and custom-sized ear muffs) of ~42 dB noise reduction. The duration of the whole scanning protocol was ~40 min (maximum duration 60 min). The family was free to discontinue the study at any point and the scan was aborted if the baby was not soundly asleep and/or still in the scanner.Axial PD-T2-weighted sequence with 1.0 × 1.0 × 1.0 mm isotropic voxels, TR of 12,070 ms and effective TE times of 13 and 102 ms were used to produce both PD-weighted and T2-weighted images from the same acquisition. The total number of slices was 128. A sagittal 3D T1 sequence with 1.0 × 1.0 × 1.0 mm voxel size  was also acquired. Additionally, the imaging included field mapping, a set of DTI images and functional imaging for some participants (data not reported here) .n = 175) brain structural T1 and/or T2 images were evaluated by a radiologist specialized in pediatric neuroradiology (author RP). When incidental findings were detected, the researchers informed the families about the finding(s) in 1–4 weeks' time. All the families with a finding were offered a child neurological examination and consultation by an experienced pediatric neurologist (author TL), and 11 out of 13 families used this opportunity.All the successful  or nonparametric Wilcoxon rank-sum test (medians and median absolute deviation (MAD), scaled by a factor k = 1.4826) depending on the normality of the distribution of the data. Multiple comparison corrections were not performed due to small sample size. In the risk factor analysis, statistical significance was calculated by using Boschloo's test . Descriptive statistics, group comparison analysis and odds ratios for putative risk factors for incidental intracranial hemorrhages were calculated. Statistical significance in the comparisons for the categorical variables was determined with Chi-square test, and for continuous variables, with two-sample o's test , 23.All 175 infants were born from singleton pregnancies without any significant prenatal complications as per inclusion criteria. 94 (54%) were males and 81 (46%) females. The mean (SD) maternal age was 30 (4.2) years. Out of the whole sample, 125 (71%) infants were born through non-assisted vaginal delivery, 21 (12%) with instrumentally assisted delivery using vacuum extraction and 29 (18%) with c-section. Epidural or spinal anesthesia was used as analgesia in 95 (59%) deliveries. In all, 72 (41%) of the mothers were primigravida. The study sample was considered to be representative of the Finnish population, as the proportions of different delivery methods as well as other obstetric factors corresponded well with the national statistics on deliveries . The demIncidental brain imaging findings were detected in 13  out of 175 infants, the prevalence of all findings thus being 7.4%, and hemorrhages in 12 infants, making the prevalence of hemorrhages 6.9%. All deliveries within the group of incidental findings were vaginal, of which four were assisted with vacuum [the prevalence in vacuum-assisted deliveries 19% (4/21)].n = 10, 5.7%). Subdural hemorrhages were mostly located in multiple sites (n = 10) was located in the posterior fossa (n = 4) and occipital (n = 3) hemorrhages were detected. The temporal subdural hemorrhages coincided mainly with hemorrhages located in the posterior fossa and in the occipital lobe (3 out of 4). Two infants with subdural hemorrhages had also additional parenchymal involvement; one cyst-associated hemorrhage in the caudo-thalamic region  and especially for temporally located hemorrhages   of 4.7  . Of altoNo imaging findings were detected in the section-delivered infant group. Birth weight, height, infant sex, duration of gestation or duration of delivery, maternal age, used anesthetics, infant Apgar score at 1 or 5 min, use of oxytocin induction or maternal parity were not related to the occurrence of hemorrhages. The median (MAD) infant age at imaging calculated from the date of birth in the hemorrhage group [23.0 (5.9) days] was slightly lower than in the group with no incidental hemorrhages [26.0 (7.4) days]. Age was not controlled in the risk factor calculations due to small group sizes, but no significant differences were observed in ages between the groups in risk factor analysis.All infants with an incidental finding had been discharged from the maternity ward according to a normal procedure, without any observed long-lasting symptoms. Infants stayed in the maternity hospital, on average, 3.1 days . One newborn, who initially required acute surveillance due to breathing difficulties, was posteriorly diagnosed with cerebellum intraparenchymal hemorrhage. His clinical presentation at birth was deemed to be caused by an infection and he was evaluated as normal upon a neurological consultation visit.None of the 11 infants who attended the pediatric neurologist's visit had any clinically identifiable, significant neurological symptoms or deficits in their development at the time of the examination . Infant age at neurological examination varied due to scheduling issues but the comparability of the data on neurological development was ensured by using two different, age-appropriate assessment protocols. One family choosing not to book a visit was contacted by phone by the pediatric neurologist. The family explained they did not regard the visit necessary as the child was considered to develop normally in the controls of well-baby clinics.n = 9) was performed by the Dubowitz neurologic examination proforma   , while wn = 46) –5. As ouVaginal delivery and vacuum-assistance were the only significant risk factors for intracranial hemorrhages, from a number of obstetric variables evaluated in our study. In Finland, the rate of c-sections almost doubled between the years 1998 and 2005, from 6.8 to 11.3% , with thWhen instrumental assistance is required during delivery, vacuum-assistance is currently the preferred method. The most common indications for the use of vacuum are problems with recording fetal heart rate and prolonged second stage of labor, and vacuum assistance is associated with primiparity, regional analgesia, smaller birth weight, and induction of labor acting as contributory factors , 31. HowMany limitations in extant studies weaken the comparison of consequences between different delivery modes, including incomplete reporting of events during labor that may substantially contribute to the choice of delivery method. Future prospective studies are needed to address this issue.The neurological assessment of all children was normal measured by 1–2 standardized systems , 21. HowIncidental findings are becoming continuously more frequent as the usage and accuracy of MRI increase. This is especially relevant in research scans using high resolution MRI sequences as a common practice, as the prevalence of incidental findings is higher in them compared to when MRI is performed as a part of clinical screenings, with lower resolution  . CurrentWe followed a recommended protocol in the handling of incidental findings , includiParental distress can have grave effects on parent-child bonding and attachment behavior , 39, whi* weighted sequences which would improve the detection of intraparenchymal microhemorrhages. SWI sequence does not show hypoxia, which is a more direct sign of brain damage, and which on the other hand is shown in T1 weighted images in addition to subdural hemorrhages .The datasets generated for this study will not be made publicly available because of restriction imposed by the Finnish law and the study's ethical permissions do not allow sharing of the data used in this study. Requests to access the datasets should be directed to the Principal investigator of the FinnBrain Birth Cohort Study HK (The studies involving human participants were reviewed and approved by the Ethics Committee of the Hospital District of Southwest Finland. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.HK and LK devised the project and main conceptual ideas. HK, LK, JT, and NS designed the infant imaging study setting. SL, JT, and NS collected the imaging data. VK, SL, JT, and NS contributed to the analysis of the data. VK, SL, AC, ES, JT, NS, TL, and RK participated to writing the manuscript. TL performed the neurological examinations. RP reviewed the MR images and evaluated the incidental findings. JS, HM, and JT designed the imaging scheme, provided the technical details, and contributed to the analysis tools. HK, NS, and JT supervised the project. All authors provided critical feedback, helped shape the manuscript, and accepted it in it's final form.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


While existing research on regions with high prevalence of centenarians has focused on selected candidate geographical regions, we explore the existence of hotspots in the whole of Denmark.We performed a Kulldorff spatial scan, searching for regions of birth, and of residence at age 71, where an increased percentage of the cohort born 1906-1915 became centenarians. We then compared mortality hazards for these regions to the rest of the country.We found a birth hotspot of 222 centenarians, 1.37 times more than expected, centered on a group of rural islands. Lower mortality hazards from age 71 onwards were confined to those born within the hotspot and persisted over a period of at least 30 years. At age 71, we found two residence-based hotspots of 348 respectively 238 centenarians, 1.46 and 1.44 times the expected numbers. One hotspot, located in high-income suburbs of the Danish capital, seems driven by selective in-migration of low-mortality individuals. The other hotspot seems driven by selective migration and lower morality among those born and residing in the hotspot.Thus, Danish centenarian hotspots do exist. The locations and interpretation depend on whether we look at place of birth or of residence late in life. Those who reach hundred years of age capture our imagination. While the specific number is an arbitrary marker, becoming a centenarian is not a meaningless indicator of longevity, and the interest in geographical regions where a high proportion of people become centenarians has been ongoing at least since the start of the 20th century . The firA plethora of explanatory factors has been proposed, roughly separating into seeing any effect as either genetic, rooted in local culture, or caused by local physical environment. For high-longevity zones in Calabria, Italy, Montesanto et al.  note a lSo far, the known longevity hotspots are in isolated, economically disadvantaged regions. In addition, the known longevity hotspots have been identified by spatial smoothing methods (as detailed in ) after fIn terms of longevity, Denmark is a curious case. The country is small, socially homogeneous, highly economically developed, and has one of the world's most generous universal welfare systems. At the same time, Denmark also has considerable social inequalities in health and a comparatively modest life expectancy of 80.7 years in 2016, compared to 80.6 for the EU in general and 78.7 for the US . This stst 2015). Of the group excluded, 1.3% became centenarians – although the proportion was 1.6 for those with municipality but not parish of birth recorded.There were 740,927 live births in Denmark from 1906 to 1915 . Of thesWhen scanning for hotspots by place of birth, we found one hotspot centered on a group of rural islands  than for men . This corresponds to the proportion surviving from 71 to 100 being 2.8% and 1.9% inside and outside the birth hotspot for women, and 0.6% and 0.5% for men .Mortality for those born in the birth hotspot and still remaining there by age 71 was slightly lower than for those who had left the birth hotspot  but with overlapping confidence intervals. There was no decrease in mortality for those born outside the birth hotspot but resident in the birth hotspot by age 71 . The centenarian proportions reflect this pattern: the proportion surviving to 100 is 1.3% for those born outside and 1.8% for those born inside the birth hotspot, wherever they live by age 71. Adjustment for birth year, socioeconomic position, marital status and homeownership did not materially change the effect sizes.Age-specific mortality rates for the cohorts born in the birth hotspot in the periods 1916-25 and 1926-35 are shown in the A sensitivity analysis where the group coded with municipality rather than parish of birth was not excluded  found the same primary hotspot, with 240 centenarian cases, 1.33 times the expected number with a p-value of 0.10.Here, we found one primary hotspot with 1.46 times , and one secondary hotspot with 1.44 times  the expected number of centenarians. The primary residence hotspot consisted of parishes in generally high-income suburbs in Northern Zealand. The secondary residence hotspot covered a region in Mid-Jutland. The total number of centenarians in each region was 348 and 238, respectively, for the primary and secondary residence hotspots. There were no further secondary clusters.The primary residence hotspot in Northern Zealand showed a higher proportion with a high socioeconomic position  and a higher proportion of divorcees  whereas Of the 12,472 subjects born in the birth hotspot, 453 (3.6%) and 59 (0.5%) were living in the primary and secondary residence hotspots by age 71, compared to 4.9% and 3.6% for the total population . A Cox rWe discovered a Danish longevity birth hotspot centered on a group of rural islands, with a 1.37 times increased chance of becoming a centenarian for the cohort born 1906-1915. The hotspot has lower post-71 mortality for both men and women, although markedly more so for women. Mortality is lower for all those born in the hotspot, whether or not they are still living there by age 71. The difference in mortality is still observable and not substantially weakened for women born in the hotspot 1916-25 and 1926-35. We find two regions with significantly increased probabilities of reaching age 100 for those resident there at age 71, both with centenarian rates similar to those of the birth hotspot.The main strength of this study is that the use of routinely collected, nation-wide registry data allows us to explore longevity distribution across an entire country for a 10-year birth cohort, that we have full follow-up from at least the age of 71, and that we can examine the effect in subsequent birth cohorts. One weakness is that we only have follow-up from 1977 and thus are unable to examine the extent to which our effects are shaped by mortality or emigration earlier in life. We only measure place of residence at two points in life, although people may have moved in and out of the regions studied. We do not have information on length of life after emigration, which in case of geographically skewed migration might bias results.The Kulldorff cluster detection method is known to be conservative , and is Although nearly 10% of observations were excluded due to missing information on parish of birth, sensitivity analyses including these observations did not change the location of the birthplace hotspot, and while the effect size decreased past the point of statistical insignificance, the absolute change was only from a ratio of 1.37 to a ratio of 1.33. As noted above, we would expect effect sizes to decrease when including data aggregated to larger geographical units.The absolute centenarian proportions in the study are not large. Comparison between studies are complicated by different outcome measures and especially different study periods, but the relative increase in probability of becoming a centenarian of 37% can be compared to the 50% increase in probability for the Sardinian blue zone or the three-fold increase in probability for the Sardinian restricted blue zone . SimilarWhatever the causes of the observed increases in extreme longevity for those born in birth hotspot, they seem to be determined before age 71. We see comparable post-71 mortality estimates for those born and staying in and leaving the hotspot, and no decrease in mortality for those moving to the birth hotspot as compared to those born and remaining outside the hotspot. The fact that there seems to be no benefits to moving to the birth hotspot is reinforced by the results of the scan for residence-based hotspots – the best place to be born is not the best place to grow old. This could point to the causes of the increase in centenarian prevalence being genetic or related to early life exposures, or being rooted in behaviors that are learned before old age and continued after leaving the region. The analyses of the subsequent cohorts suggest that whatever the determinants of longevity in the birth hotspot, they remain a factor over a period of at least 30 years.The hotspots we have identified all seem more favorable to women. This is contrary to the situation for the Nicoya hotspot, where increased centenarian rates are seen only for men , and theWhen looking for causes for the birth hotspot, we should note that this area historically has been a poor area with an agricultural economy dominated by large estates. The main island of Langeland experienced mass emigration for a period leading up to the birth of the cohort studied - 30% of the population emigrated in the period 1868-1909 as compared to a national average of 10% . While bThe interpretation of the age 71 residence hotspots is less straightforward than that of the birth hotspot, due to the nature of migration. Place of residence at age 71 is an indicator of socioeconomic and health status, and thus a straightforward interpretation of the secondary hotspots as "the best places to grow old" is not possible. They can just as well be interpreted as "the places where the fittest live by age 71". The fact that the Northern Zealand hotspot was only beneficial for those born outside it might suggest that the effect is one of selective migration. Certainly, the Northern Zealand residential hotspot has markedly higher socioeconomic position by 1970 than the cohort in general and there could plausibly be selection factors into the Mid-Jutland hotspot as well.Does a Danish longevity hotspot by place of birth exist? Our finding must be seen in the light of the limitations discussed: The relative increase in centenarian proportion is moderate as is the statistical significance level, and our results may be shaped by emigration or mortality before age 71. On the other hand, the hotspot observed persists for a period of at least 30 years, which makes it less likely to be merely a statistical fluke. In contrast to the primary residence hotspot, the place-of-birth hotspot is not immediately explained by socioeconomic factors. And so, even when scanning across a geographically and socially homogeneous country, centenarian hotspots can be found, although we can make no real guess as to the causes.st 2015.We constructed a cohort of men and women born in Denmark from 1906 to 1915 and still alive at the age of 71. For each person, we identified parish of birth and place of residence by age 71 plus date of death and emigration. The data source was the Population Registration System of Denmark, which allows individual follow-up for all persons resident in Denmark since 1968 [The choice of cohort and of the reference age of 71 were pragmatic: We wanted to look at the most recent 10-year birth cohort that could have been recorded as centenarians by the time the study was begun, and as the oldest of this group had turned 71 by the time parish of birth was introduced as a register variable, we had to restrict to the subcohort surviving to this point. For simplicity, in the analyses of residence later in life, we chose to look at place of residence at age 71 rather than at some other age.We searched for clusters of centenarians using a Kulldorff spatial scan  as impleHaving detected a hotspot, we compared mortality and centenarian proportion in people born inside and outside the hotspot for men and women. Mortality was compared via hazard ratios computed by Cox regressions in which the outcome was death, and those who survived past the end of follow-up (Dec 31 2015) were censored. We also compared mortality and centenarian proportion according to whether the subjects were born and stayed in, had left, were born outside and had moved to, or were born and had stayed outside the cluster by age 71. We adjusted for birth year, socioeconomic position, marital status and homeownership. Missing values of covariates were set to the most common value for marital status, and to lowest for socioeconomic position.In order to explore the extent to which the effect was stable over time, we compared cohort mortality for those born inside and outside the cluster over the period from 1978 to 2015 for the cohorts with birth years 1906-1915, 1916-1925 and 1926-1935. Five-year mortality rate ratios were computed by Poisson regression.As a sensitivity analysis, since a large percentage of observations were coded with municipality rather than parish of birth, we performed cluster detection where the observations coded with municipality were weighted out across the parishes whose centroids were inside that municipality. The weights were proportional to the size of the birth cohort by year and sex in each parish.We also performed cluster detection based not on the proportion of a birth cohort reaching age 100, but on the proportion of those residents in a region by age 71 who become centenarians.Figure 1 and 2Analyses were done using R version 3.2.3 software.Supplementary Tables


This study sought to evaluate the performance of metabolic gestational age estimation models developed in Ontario, Canada in infants born in Bangladesh. Cord and heel prick blood spots were collected in Bangladesh and analyzed at a newborn screening facility in Ottawa, Canada. Algorithm-derived estimates of gestational age and preterm birth were compared to ultrasound-validated estimates. 1036 cord blood and 487 heel prick samples were collected from 1069 unique newborns. The majority of samples (93.2% of heel prick and 89.9% of cord blood) were collected from term infants. When applied to heel prick data, algorithms correctly estimated gestational age to within an average deviation of 1 week overall (root mean square error = 1.07 weeks). Metabolic gestational age estimation provides accurate population-level estimates of gestational age in this data set. Models were effective on data obtained from both heel prick and cord blood, the latter being a more feasible option in low-resource settings. Complications from preterm birth are the leading cause of death among children under five. Ultrasounds are routinely used in wealthy countries to track babies' development. In countries with limited resources, however, ultrasounds are rare, making it harder to estimate how many children are born prematurely. Blood tests may offer a way to determine whether a newborn was born too early when ultrasounds are not available. Many countries already require clinicians to collect a drop of blood from newborns via a heel-prick or from their umbilical cord. Testing these blood spots identifies babies at risk of rare conditions so they can receive prompt treatment.Chemicals in the blood vary depending on how long the newborn spent growing in its mother’s womb. Scientists have developed a mathematical formula that can estimate a baby’s gestational age based on these chemicals. Using blood spots to estimate gestational age worked well when this strategy was tested in Canada, a high-income country. More tests are needed to determine if it works in low-income countries.Now, Murphy et al. show their blood spot-testing strategy also reliably predicts the gestational age of babies in Matlab, Bangladesh. In the experiments, blood spots were collected from 1,069 newborns. This included 1,036 cord blood samples and 487 heel prick samples. Nearly all the samples came from full-term infants. A mathematical model estimated the infants' gestational age to within an average of one week of their true age when applied to heel-prick blood samples and to within two weeks of the baby’s true gestational age 94% of the time.The model also provided reliable estimates of babies’ gestational ages when cord blood samples were tested, which is useful as the Bangladeshi parents were more comfortable with this method of blood collection. Using this strategy to estimate how many babies are born too early in low-income countries may help the countries develop strategies to reduce preterm births. The estimates might also help identify preterm babies who need special care. Complications related to preterm birth are the leading cause of death among children under 5 years of age . EstimatAlgorithms based on newborn metabolic profiles in combination with clinical covariates such as sex and birthweight have demonstrated the potential to accurately categorize infants across preterm birth categories in high-resource settings . Data frOne cord blood sample was excluded because 100% of analyte values were missing. Imputation was conducted for the remaining samples missing analyte values  analyte values missing). The final cohort consisted of 1523 samples from 1069 unique individual newborns. 1036 samples were collected immediately after birth (range: 0 min - 2 hr 1 min) from the umbilical cord, and 487 heel prick samples were collected an average of 14 hr 58 min after birth (range: 25 min - 40 hr 30 min). The majority of samples received  were from term infants . 18.1% of heel prick samples and 15.9% of cord blood samples were derived from infants with a birthweight <2500 g. Of the 1069 infants included in the study, 454 contributed both heel and cord blood samples. A summary of participant demographics is provided in We determined the performance of previously published metabolic gestational dating algorithms in heel prick-derived data from the Bangladeshi infant cohort. Results of linear regression analyses for heel prick metabolic profiles demonstrated optimal performance among term infants between 38 and 39 completed gestational weeks . ResiduaA baseline model including only clinical covariates  provided the least accurate estimation of gestational age relative to ultrasound-validated gestational age estimates, RMSE 1.46 weeks. By comparison, a model including analyte covariates (Model 2) had an RMSE of 1.35 weeks. A full model containing all clinical and analyte data (Model 3) demonstrated the lowest RMSE (best performance) of 1.07 weeks and correctly estimated gestational age to within 1 week for 63.9%, and within 2 weeks for 94.3% of all heel prick samples. Among small for gestational age infants, the full heel prick model had an RMSE of 1.12 weeks when growth restriction was defined as birthweight below the 10th percentile for gestational age and an RMSE of 1.30 weeks when defined as birthweight below the 3rd percentile for gestational age. By these definitions, our model accurately estimated gestational age to within 1 week for 62.8% and 53.4% of growth-restricted infants, respectively.As with heel prick data, algorithmic estimates of gestational age most accurate among term infants . When apWe evaluated the discrimination of gestational age across a dichotomous preterm birth threshold  . GestatiIn this paper, we demonstrate that algorithms developed using newborn screening data from Ontario, Canada are effective in deriving estimates of gestational age in infants born in Matlab, Bangladesh that are accurate to within approximately 1 to 2 weeks of ultrasound-validated gestational age. Data derived from newborn heel prick samples consistently yielded more accurate estimates of gestational age than cord blood-derived data, likely reflecting the fact that our models were originally developed from data obtained from this sample type. Indeed, we have shown that the correlation between cord blood and heel prick-derived data varies significantly across analyte subtypes (Appendix 1).Accurate assessment of gestational age, preterm birth and small for gestational age is a recognized priority area where there is a need to improve program tracking and accountability . AlthougMetabolic gestational dating approaches emerged in response to the urgent need to improve the epidemiology and surveillance of preterm birth. Circulating newborn metabolites are known to be affected by gestational age and gestational age is routinely considered in the interpretation of newborn screening analysis . To dateOur study had a number of important strengths and limitations. Strengths of our approach include the use of internationally-derived samples to externally validate our models and using samples from a well-described cohort of infants with gestational age confirmed by first trimester ultrasound. The study design of the PreSSMat cohort in which our study was nested ensured that enrollment was open to a representative selection of women and newborns delivering in the Matlab icddr,b service area. Other strengths include the high quality of samples received for analysis, and the use of paired cord blood and heel prick samples to compare model performance metrics. The primary limitation of this study is the participation bias against very preterm and extremely preterm infants, whose parents expressed reluctance to subjecting their newborn to these collection procedures. As a result, we had a relatively small number of samples collected from very preterm and extremely preterm infants, limiting our ability to comment on model performance in these sub-groups. In this Bangladesh cohort, the gestational ages estimated from our models were most accurate in infants who were confirmed to be close to full-term by first trimester ultrasound. Algorithm-derived gestational ages tended to be overestimated in preterm infants and underestimated in post-term infants. This suggests that calibration in the large  overall and correctly ascertain gestational age to within 2 weeks for 94.9% of infants (vs. 94.3% for the Bangladeshi cohort) ; estimatUltimately, acceptable levels of error in gestational age measurements will need to be determined by public health and maternal child health officials. Given the acknowledged limitations of existing alternatives to ultrasound estimation, metabolic gestational dating approaches appear to offer reliable estimates that are unencumbered by user variability. As we prepare for the scale-up and implementation of metabolic gestational dating approaches for robust population-level estimates of preterm birth, our findings highlight a number of opportunities and challenges. First, heel prick samples taken for newborn screening are typically collected at least 24 hr after birth to accommodate postpartum fluctuations in analyte levels. In many settings around the world, mother-infant pairs are discharged from healthcare settings within the first 24 hr after delivery . As a reIn summary, metabolic gestational age dating approaches offer a novel means for providing accurate population-level gestational age estimates. As we work toward implementing preterm birth surveillance initiatives in a variety of low-income settings , the levOur objective was to validate the performance of previously published gestational age estimation models developed in Ontario, Canada  in a cohNewborn screening is a public health initiative that screens for rare, treatable conditions that typically produce no symptoms in the neonatal period. Programs vary in scope by jurisdiction, screening for one to over 50 conditions . In OntaSample collection was conducted in the Matlab sub-district of Chandpur, Bangladesh where the International Centre for Diarrhoeal Disease Research, Bangladesh  has been running a Health and Demographic Surveillance System (HDSS) in Matlab since 1966. Based on service provision, the HDSS area is divided into two jurisdictions: 1) the icddr,b service area where women of reproductive age and their children under 5 years of age receive care though icddr,b facilities; and 2) the government service area where individuals receive care from government facilities as in other areas of the country. The present study was conducted in the icddr,b service area, and nested within a cohort study entitled ‘Preterm and Stillbirth Study, Matlab’ (PreSSMat) that was designed to capture data on the biological determinants of adverse pregnancy outcomes, including preterm births. In the PreSSMat cohort, pregnant women were followed prospectively along the pregnancy continuum, with scheduled visits at 11–14 (enrollment and ultrasound), 22–24, and 32 weeks’ gestation, at delivery, and at 6 weeks post-partum to collect socio-demographic and clinical data as well as biological specimens. Preterm births were defined as all births that occurred at <37 weeks’ gestation. ‘Very preterm births’ were those that occurred at <32 weeks, and ‘extremely preterm births’ were those that occurred at <28 weeks. Small for gestational age (SGA10) was defined as cases where birthweight was below the 10th percentile within categories of week of gestational age at delivery and infant sex. The percentiles were calculated and applied based on a North American distribution of birthweight within sex and gestational age categories. We also calculated SGA3, which identifies infants below the 3rd percentile within gestational age and sex categories and is much more likely to reflect infants who suffered intrauterine growth restriction, especially in low and middle-income countries such as Bangladesh where birthweights are lower. Pregnant women were identified by community health workers through monthly home visits. All enrolled women underwent a gestational dating ultrasound at enrollment; otherwise no explicit inclusion or exclusion criteria were applied. All women enrolled in the PreSSMat cohort were eligible for participation in the current study.To examine the effect of timing of sample collection on newborn metabolic profiles, cord blood was collected immediately after birth and spotted on Whatman 903 filter paper. A second dried blood spot sample was also collected via heel prick within 72 hr of delivery or immediately prior to discharge, whichever happened first. The latter reflects the timing of collection for samples used to develop our previously published gestational age estimation models . Samples were collected onto filter paper, air-dried and shipped weekly to Newborn Screening Ontario (NSO), the provincial newborn screening facility in Ottawa, Canada. Samples were stored in a temperature and humidity-controlled environment prior to shipment. Eight 3.2 mm diameter samples were punched from each sample for testing of the following analytes: hemoglobin profiles; 17α hydroxyprogesterone (17-OHP); thyroid stimulating hormone (TSH); immunoreactive trypsinogen (IRT); a panel of 12 amino acids and 31 acylcarnitines; t-cell receptor excision circles (TREC); biotinidase activity; and galactose-1-phosphate uridylyltransferase activity. Hemoglobin profiles were determined by high-performance liquid chromatography on a Bio Rad Variant nbs system; neonatal 17-OHP, TSH and IRT were measured using PerkinElmer AutoDELFIA Immunoassays; amino acid and acylcarnitine analysis was performed by electrospray ionization tandem mass spectrometry (Waters TQD); total TREC copy number was measured by quantitative polymerase chain reaction using a ThermoFisher Scientific Viia 7; biotinidase and galactose-1-phosphate uridyltransferase levels were measured using the Astoria-Pacific SPOTCHECK Pro system. Clinical covariates were retrieved from the PreSSMat database to facilitate clinical interpretation of newborn screening data, and also for inclusion as model parameters in this study. Newborn screening blood spots are subject to degradation if collected or handled inappropriately. Samples with insufficient good-quality dried blood to complete the full panel of assays were excluded from analysis. Samples with missing analyte values had the missing levels imputed (see Appendix 1 for details). In the process of applying newborn screening procedures for the analysis of samples, results of ‘screen negative’ and ‘screen positive’ were generated for conditions screened for by the NSO program. Management of incidental clinical findings (screen-positive cases) has been reported elsewhere .We sought to compare estimates of gestational age and preterm birth based on our analysis of blood spots against first trimester ultrasound estimates, which are considered the gold standard for gestational age measurement . The perModel 1: Baseline model containing only the clinical factors of infant sex, birthweight, and multiple birth (yes/no)Model 2: Analytes model including infant sex, multiple birth (yes/no) and newborn screening analytes and pairwise interactions including acylcarnitines, amino acids, endocrine and enzyme markers.Model 3: Full model containing both clinical and analyte data , birthweight, newborn screening analytes and pairwise interactions)Statistical modeling approaches are described in Appendix 1. In brief, sample data were scored using multivariable models previously developed using heel prick blood spot samples in a large cohort of infants born in Ontario, Canada . The fitMothers provided informed consent for their infants to be included in the PreSSMat birth cohort and to have clinical data, cord blood and newborn heel prick samples collected and analysed. The present study was approved by the Research Review and Ethical Review Committees of the International Centre for Diarrhoeal Disease Research, Bangladesh (PR-16039) on July 10, 2016. Approvals were also obtained from the Research Ethics Boards of the Ottawa Health Science Network (20160219–01H) on June 10, 2016, and the Children’s Hospital of Eastern Ontario (16/20E) on June 8, 2016. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Prabhat Jha as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Jessica Duby (Reviewer #1); Eric Ohuma (Reviewer #2).Thank you for submitting your article "Postnatal gestational age estimation using newborn metabolic profiles in Matlab, Bangladesh" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:In this manuscript by Murphy et al., the authors study the accuracy of a metabolic based model to determine gestational age for neonates in Bangladesh when compared to a first trimester ultrasound. The authors make a strong case for the potential impact of a successful algorithm in determining population rates of preterm birth and small-for-gestational age in low-resource settings. This is a potentially important study but the description of the study design and execution is far from complete.In addition, whilst there is no doubt an accurate estimate of GA is important, there are fundamental problems with this approach that is based on postnatal estimation of GA. First, it helps to perpetuate a standard of care that even WHO has abandoned, namely managing pregnancies without knowing the due date. This is the reason the new WHO guidelines recommend at least one ultrasound scan, in part to estimate gestational age prenatally.In addition, the authors do not properly address the model's ability to distinguish small-for-gestational age (SGA) neonates, which should be one of the model's primary advantages over using birth weight alone as a surrogate marker for gestational age.Essential revisions:1) There are deviations from the cited, published protocol that remain unexplained by the authors. Major differences between published protocol and current manuscript:a) Sample size: The protocol's sample size requirements are calculated to be 3,500 participants. The current manuscript details 1523 samples from 1069 newborns with no discussion regarding the achieved sample size. As part of addressing sample size differences, it may benefit the authors to present a figure detailing number of eligible participants, number approached for consent, number consented, etc.b) Models: The proposed models to test in the protocol are quite different than the models tested in the current manuscript and no justification is provided. For reference, the models listed in the protocol are: "1) birth weight alone; 2) combination of birth weight and fetal/adult haemoglobin levels; 3) combination of birth weight, haemoglobin levels, thyroid-stimulating hormone and 17-OHP ; and 4) birth weight and the full panel of newborn screening analytes. Sex and multiple birth  will be included in all models."  For models used in the reported study, refer to the subsection “Validation of algorithms”.2) SGA/large-for-gestational age (LGA) babies: The authors need to provide further analysis and discussion regarding the algorithm's performance in SGA/LGA identification. Specifically, the authors need to identify how many SGA/LGA neonates were in their sample and the models' accuracy for these important sub-groups. The authors had listed this analysis in their protocol and have previously performed similar sub-group analysis on the original Ontario cohort which can be used as a guide. .3) While the authors do sub-group analyses by birth weight (<2500g and ≥2500g) in Table 2, weight alone is unimportant when we consider the overarching goal of finding a model that can distinguish preterm birth from SGA and post-term birth from LGA. I would recommend replacing the columns under each of the sample types in Table 2 to be:1) Overall;2) SGA;3) Appropriate-for-gestational age (AGA); and4) LGA.4) Imputation of missing values: As only 46 (11%) of observations were imputed, did the authors do a sensitivity analysis of the performance of the model with and without the imputed missing values to evaluate their influence on the results?5) Prediction score (nomogram) – it would be useful for the authors to also show the relative contribution of each factor in their model. For example, in the baseline model with birthweight, infant sex and multiple births, what is the greatest predictor of GA? A quantification of the relative contribution of each of the factors is useful in understanding their contribution and justification as important variables the prediction of GA. Similarly, this should be done for models 2 and 3 as it allows one to make judgements on how much more improvements in prediction is provided for by including the clinical and analyte data. Also, a comparison of scores helps to discern whether some factors included in the model are correlated and thus are similar in their prediction of GA.6) Would also be helpful for the author to show a plot of true GA vs. predicted GA  as this will evidently show the variability of the prediction as a function of GA as opposed to the aggregated estimates they have presented by GA in Figure 1.7) The cohort was apparently nested within a PreSSMat study in Matlab but the authors do not provide key information on timing of ultrasound examination, birth examinations and weight and criteria used to categorize infants as either preterm, small for gestational age (SGA) or combinations thereof. Please add the necessary level of detail to the methodology and Results sections.8) Given the issues with cord blood specificity and the wide range of times in collection of heel prick samples (from a few hours to up to 40 hours), one is left guessing as to the fidelity of design of the gold standard used in this study and early measures. Please explain when were these measurements obtained?9) Please explain what standards were used for ultrasound based gestational age and add an appropriate justification for adoption of the chosen standards.10) The overall rates of prematurity in the cohort determined from the study (both cord and heel prick samples) are implausibly low (given what is known from ANISA and AMANHI studies done in Bangladesh). Please explain the reasons for these differences.11) The authors should comment on what is known about prematurity incidence from prior studies of maternal antenatal care and nutrition supplementation done in Bangladesh on large rural cohorts including Matlab, without that information, it is difficult to place this study in the context of what else is known. Summary:In this manuscript by Murphy et al., the authors study the accuracy of a metabolic based model to determine gestational age for neonates in Bangladesh when compared to a first trimester ultrasound. The authors make a strong case for the potential impact of a successful algorithm in determining population rates of preterm birth and small-for-gestational age in low-resource settings. This is a potentially important study but the description of the study design and execution is far from complete.In addition, whilst there is no doubt an accurate estimate of GA is important, there are fundamental problems with this approach that is based on postnatal estimation of GA. First, it helps to perpetuate a standard of care that even WHO has abandoned, namely managing pregnancies without knowing the due date. This is the reason the new WHO guidelines recommend at least one ultrasound scan, in part to estimate gestational age prenatally.Thank you for addressing this point. We agree that managing pregnancies without knowledge of gestational age is not recommended. We therefore do not seek to implement our postnatal estimation models as a clinical tool replace prenatal ultrasound. Rather, we propose that our models could have utility in deriving population-level estimates of preterm birth in geographies or locales where prenatal ultrasound data are frequently available. We have noted in the Introduction that these models are intended for use when ultrasound is not available.“…these algorithms have the potential to provide reliable population estimates of preterm birth burden when prenatal ultrasound is not available”.In addition, the authors do not properly address the model's ability to distinguish small-for-gestational age (SGA) neonates which should be one of the model's primary advantages over using birth weight alone as a surrogate marker for gestational age.Thank you. One of the limitations of our best performing model is its reliance on birthweight as a covariate in estimating gestational age. Including birthweight in the models limits our ability to identify SGA or IUGR infants as the impact of birthweight on gestational age is confounded in these infants.th and 3rd percentiles for gestational age and sex as defined by a North American population, however a large proportion of these infants are not truly growth restricted in the context of the local Bangladesh population distribution.When birthweight is removed from the model, its performance deteriorates substantially among infants overall, but improves slightly in SGA infants. We have included model performance results for infants with birthweight below the 10Future work will seek to refine our model that excludes birthweight as a covariate in order to improve its utility in these populations. We discuss the utility of our current models with and without birthweight in SGA cases in greater detail below in response to the other SGA-related reviewer questions.Essential revisions:1) There are deviations from the cited, published protocol that remain unexplained by the authors. Major differences between published protocol and current manuscript:a) Sample size: The protocol's sample size requirements are calculated to be 3,500 participants. The current manuscript details 1523 samples from 1069 newborns with no discussion regarding the achieved sample size. As part of addressing sample size differences, it may benefit the authors to present a figure detailing number of eligible participants, number approached for consent, number consented, etc.Thank you for giving us the opportunity to address the differences between our published protocol and our completed study. As the reviewer has noted, we ultimately collected and analysed fewer samples than we initially anticipated. This was due to administrative delays at the outset of the project, particularly while the study was reviewed by three research ethics boards in two countries. By the time the study was initiated, there was less time in which to recruit eligible participants before the end of the study. The sample size calculations presented in our protocol were presented across a range of scenarios, and sample sizes of 1500 and 3500 were projections for Zambia and Bangladesh respectively. The projected sample size of 3500 in Bangladesh was based on Power to detect differences in AUCs for models classifying <34 weeks vs. ≥34 weeks GA. We ended up recruiting fewer total subjects and unfortunately almost no infants <34 weeks, so we have only presented results classifying <37 weeks vs. ≥37 weeks. We still have good statistical power to report c-statistics with good precision. For continuous models, sample size estimates were also driven by the desire to have a minimum number of samples to validate using RMSE estimation  in the smallest subgroups of interest. Thus, we cannot report on validation in <34 weeks. For example, where we only had 3 subjects, but we do have sufficient sample in 34-36 week preterm infants as well as term and post-term infants to report our findings among this group. The following statement has been added to the manuscript:“Due to logistical challenges in initiating the study, fewer samples were collected than initially anticipated in our protocol, leading to low numbers of infants with gestational age below 34 weeks. Our methods of sample collection and analysis remain the same, recognizing these sampling limitations.”b) Models: The proposed models to test in the protocol are quite different than the models tested in the current manuscript and no justification is provided. For reference, the models listed in the protocol are: "1) birth weight alone; 2) combination of birth weight and fetal/adult haemoglobin levels; 3) combination of birth weight, haemoglobin levels, thyroid-stimulating hormone and 17-OHP ; and 4) birth weight and the full panel of newborn screening analytes. Sex and multiple birth  will be included in all models."  For models used in the reported study, refer to the subsection “Validation of algorithms”.Models 1, 2 and 3 were conducted as described in the published protocol. This was an editorial omission. All three models included infant sex and multiple birth (yes/no). Model 1 additionally included birthweight, model 2 excluded birthweight and included analytes and pairwise interactions. Model 3 included birthweight, analytes and pairwise interactions in addition to sex and multiple birth (yes/no). This has been corrected in the Statistical Analysis section of the Materials and methods as follows:“The performance of the following models was assessed:Model 1: Baseline model containing only the clinical factors of infant sex, birthweight, and multiple birth (yes/no);Model 2: Analytes model including infant sex, multiple birth (yes/no) and newborn screening analytes and pairwise interactions including acylcarnitines, amino acids, endocrine and enzyme markers;Model 3: Full model containing both clinical and analyte data , birthweight, newborn screening analytes and pairwise interactions)”.The intermediate models that limited analytes to fetal/adult hemoglobin ratio, and fetal/adult hemoglobin ratio+17OHP+TSH were not included in the results because, although these subgroups of analytes were more simply and cheaply measurable, the models including only these analytes did not reach the level of predictive accuracy that would make them useful. For the sake of clarity and parsimony we opted not to report the results for those subsets of analytes, which were initially chosen for pragmatic rather than scientific reasons.2) SGA/large-for-gestational age (LGA) babies: The authors need to provide further analysis and discussion regarding the algorithm's performance in SGA/LGA identification. Specifically, the authors need to identify how many SGA/LGA neonates were in their sample and the models' accuracy for these important sub-groups. The authors had listed this analysis in their protocol and have previously performed similar sub-group analysis on the original Ontario cohort which can be used as a guide. .Thank you. We address this point and point 3 in one response, below.3) While the authors do sub-group analyses by birth weight (<2500g and ≥2500g) in Table 2, weight alone is unimportant when we consider the overarching goal of finding a model that can distinguish preterm birth from SGA and post-term birth from LGA. I would recommend replacing the columns under each of the sample types in Table 2 to be:1) Overall;2) SGA;3) Appropriate-for-gestational age (AGA); and4) LGA.Response to points 2 and 3:th percentile for given infant sex and GA in weeks. We have added details to the Study Design section of the Materials and methods as follows:Thank you, we agree that the performance of our models among SGA infants is important. We did not have access to local reference distributions of appropriate weight for gestational age, so we relied on our North American reference distributions, from which we applied cutpoints to define small and large for gestational age  fell into this group.4) Imputation of missing values: As only 46 (11%) of observations were imputed, did the authors do a sensitivity analysis of the performance of the model with and without the imputed missing values to evaluate their influence on the results?We did a complete case analysis and investigated the range of results in each of the 10 imputed datasets and determined that the results did not vary substantially in either the complete case analysis, or among the 10 independent imputations. We reported the average performance across the 10 imputed datasets for the validation results.5) Prediction score (nomogram) – it would be useful for the authors to also show the relative contribution of each factor in their model. For example, in the baseline model with birthweight, infant sex and multiple births, what is the greatest predictor of GA? A quantification of the relative contribution of each of the factors is useful in understanding their contribution and justification as important variables the prediction of GA. Similarly, this should be done for models 2 and 3 as it allows one to make judgements on how much more improvements in prediction is provided for by including the clinical and analyte data. Also, a comparison of scores helps to discern whether some factors included in the model are correlated and thus are similar in their prediction of GA.Thank you. In the current study, we are using a previously-developed model to score an external cohort for the purposes of external validation and assessment of generalizability. We did not report on the model building and the relative importance of factors in the final model in this study. We did however report on these details in our previously published studies where these models were developed. However, we appreciate the reviewer’s point that this information is important enough to reiterate, so we have added the following to the Statistical Analysis section of the Materials and methods:+analytes and full models).”“The fitted models used for scoring the Bangladesh data included numerous main effects and interaction terms including both analytes and clinical measures . However, there was a subset of predictors that were clearly the strongest contributors to the model in terms of independent contribution to explained variance: birthweight (in base and full models) and fetal/adult hemoglobin ratio, TSH, 17OHP, ALA, c5, C4DC and TYR (in the sex+multiple birtH6) Would also be helpful for the author to show a plot of true GA vs. predicted GA  as this will evidently show the variability of the prediction as a function of GA as opposed to the aggregated estimates they have presented by GA in Figure 1.Thank you. In evaluating our models, we generated residual plots across the range of true gestational ages, but did not include these figures in the manuscript. We agree that these plots are very helpful in understanding the performance of these models above and beyond the aggregate RMSE plots we previously included. We have now included a new figure , which is a panel plot of the three models in both heel prick and cord blood models .7) The cohort was apparently nested within a PreSSMat study in Matlab but the authors do not provide key information on timing of ultrasound examination, birth examinations and weight and criteria used to categorize infants as either preterm, small for gestational age (SGA) or combinations thereof. Please add the necessary level of detail to the methodology and Results sections.th percentile for given infant sex and GA in weeks. This has been added to the Materials and methods section:Thank you for this opportunity to provide additional details. Within the PreSSMat study, pregnant women visited the local clinic three times during pregnancy. The first visit to obtain an ultrasound occurred between 11-14 weeks’ gestation. Subsequent visits occurred at 22-24 weeks, 32 weeks, delivery, and six-weeks post-partum. Preterm births were defined as all births that occurred at <37 weeks’ gestation. “Very preterm births” were those that occurred at <32 weeks, and “extremely preterm births” were those that occurred at <28 weeks. As noted, above, we did not have access to local reference distributions of appropriate weight for gestational age, so we relied on our North American reference distributions, from which we applied cutpoints to define small and large for gestational age , 22-24, and 32 weeks’ gestation, at delivery, and at 6-weeks post-partum to collect socio-demographic and clinical data as well as biological specimens. […] The percentiles were calculated and applied based on a North American distribution of birthweight within sex and gestational age categories.”8) Given the issues with cord blood specificity and the wide range of times in collection of heel prick samples (from a few hours to up to 40 hours), one is left guessing as to the fidelity of design of the gold standard used in this study and early measures. Please explain when were these measurements obtained?Thank you. As noted above, the gold-standard against which our GA estimates were compared was first trimester ultrasound (see below our response to the following comment for more information). We have noted as a limitation that heel-prick samples should be collected at least 24 hours after birth, but given the rates of early mother-child discharge from hospital, heel-prick samples were often collected before this time out of necessity. The post-partum analyte fluctuations that occur within the first few days of birth are a limitation of cord and early heel-prick sampling, and we have noted that this may have affected the performance of our model. However, as ultrasound-validated GA estimates were obtained between 11-14 weeks’ gestation, we are confident that the gestational ages against which our model was compared were accurate to within one week.9) Please explain what standards were used for ultrasound based gestational age and add an appropriate justification for adoption of the chosen standards.Thank you. Ultrasound-based gestational age was determined via first trimester ultrasound (between 11-14 weeks). The American College of Obstetricians and Gynecologists recommends first-trimester ultrasound (up to 14 weeks) as the most accurate method of establishing and measuring gestational age . In this study, a portable ultrasound machine was used for all participants, and included measurement of crown-rump length, biparietal diameter, occipito-frontal diameter, head and abdominal circumferences, and femur length. We have referenced the ACOG recommendations within our manuscript.10) The overall rates of prematurity in the cohort determined from the study (both cord and heel prick samples) are implausibly low (given what is known from ANISA and AMANHI studies done in Bangladesh). Please explain the reasons for these differences.Thank you for this comment. We believe there are two primary reasons for the lower rates of preterm birth seen in this cohort. First, the women in this cohort benefited from being in the service area for icddr,b, the organization implementing the study in Matlab. Compared to individuals outside of this service area, women in the icddr,b service area benefit from a high level of prenatal and other health care. Additionally, participation in this study allowed pregnancies to be monitored and antenatal care to be provided in ways that may not have occurred had these women not participated in the study. Second, many parents of very preterm and extremely preterm infants were reluctant to have their infants subjected to the sample collection procedures given the challenges already experienced by these infants, and thus did not consent to participate in the study. This was highlighted previously in our Discussion section, but we have made this limitation more explicit. As our objective was not to determine rates of preterm birth in this area however, we have not expanded further as to why our study contains relatively few preterm infants.“The primary limitation of this study is the participation bias against very preterm and extremely preterm infants, whose parents expressed reluctance to subjecting their newborn to these collection procedures. As a result, we had a relatively small number of samples collected from very preterm and extremely preterm infants, limiting our ability to validate model performance in these sub-groups.”11) The authors should comment on what is known about prematurity incidence from prior studies of maternal antenatal care and nutrition supplementation done in Bangladesh on large rural cohorts including Matlab, without that information, it is difficult to place this study in the context of what else is known.Thank you. We believe that this falls outside the scope of our study, as our aim was not to estimate the incidence of preterm birth in Matlab, but rather to comment on our model’s ability to estimate GA in this context. The next step in the implementation of our model will be to use the model to estimate the incidence of preterm birth, but that was not our goal at this time.


Low birth weight at birth is an important underlying contributor for neonatal and infant mortality. It accounts for nearly half of all perinatal deaths. Identifying predictors of low birth weight is the first essential step in designing appropriate management strategies. Hence, this study aimed to identify risk factors for low birth weight in hospitals of northeastern Ethiopia.th April to 15th December 2016. Three hundred sixty mother-infant pairs  were included in the study. Data were collected by face-to-face interview. Univariable and multivariable logistic regression models were computed to examine the effect of independent variables on outcome variable using SPSS 20.0. Variables with p-value <0.05 were considered statistically significant.An institution based case-control study design was conducted from 10The mean (±SD) gestational age and birth weight (±SD) were 39.2 (±1.38) weeks and 2800 (±612), grams respectively. Partner’s education/being illiterate , antenatal care visit at private health institutions , having history of obstetric complications , maternal weight during pregnancy  and gravidity  were significantly associated with low birth weight. Additionally, a site for water storage and water treatment were significant environmental factors.Maternal weight during pregnancy, paternal education, previous obstetric complication and place of antenatal follow-up were associated with low birth weight. The risk factors identified in this study are preventable. Thus, nutritional counseling, health education on improvement of lifestyle and early recognition and treatment of complications are the recommended interventions. Low birth weight (LBW) is defined as a birth weight less than 2500g and LBW infants are at greater risk of death and disability . GloballGlobally, an estimated 15% to 20% of all births are LBW . The preVery low birth weight infants have decreased cognitive, language and motor functions . A systeOne cohort study showed vomiting during the early trimester of pregnancy was associated with a higher risk of low birth weight . In deveIn 2014, the World Health Organization (WHO) identified evidence-based interventions to prevent low birth weight . OvervieEthiopia has made a notable achievement in reducing neonatal mortality during the era of the Millennium Development Goals (MDGs) . Goal 3 A hospital-based unmatched case-control study design was employed from April 10 to December 15, 2016, in North Wello zone hospitals. This zone has an estimated total population of 1,500,303 . Based on reports from the zone’s health sector office, North Wello zone has 3 hospitals and 64 functional health centers. The study was conducted in the three hospitals; Woldia General Hospital, Lalibela hospital, and Kobo hospital, which are located 520, 700 and 571 kilometers away from Addis Ababa respectively. In 2015, there were 6,013 births in Woldia, Lalibela and Kobo towns.Newborns who were born in the three public hospitals during the study period (8 months) were the source population of this study. Mothers of the newborns were the source of the information. Live newborns delivered at term without known risk factors (i.e. intrauterine growth restriction) of low birth weight were included in the study. Mothers who gave birth before 37 completed weeks of gestation and mothers with medical conditions, which affect birth weight , were excluded from the study. Mothers who gave birth to neonates weighing less than 2500 grams were cases and neonates ≥2500 grams were controls.The outcome/dependent variable was low birth weight. The exposure/independent variables were socio-demographic variables , obstetric factors  and environmental characteristics .2 = 1.96), power (Zβ = 0.84), control to case ratio 2:1 (r = 2), odds ratio to be detected 2.1 and 20% 33]. AnotThis study identified history of obstetric complications as a risk factor for low birth weight. Study subjects who did not experience any obstetric complications during their past pregnancies had decreased risk of low birth weight babies. Similar findings were reported by other descriptive studies in Ethiopia , 23, 32.The present finding showed the protective effect of storing water in an open container and drinking without treatment for low birth weight. Studies showed that prenatal exposure to chlorination by-products in drinking water was associated with risks of small for gestational age , 44. A cAs strength, the authors excluded known risk factors of low birth weight to minimize possible confounding. Additionally, the authors selected institution-based cases to minimize selection bias. However, this study may be prone to recall bias because the respondents were asked about their previous obstetric characteristics. Moreover, some confounders may not be controlled due to unmatched selection of study subjects. Generalizability of the results to the general population should be made cautiously, as observation was not made for house and environmental factors.This study showed that socio-demographic, maternal/obstetric and environmental characteristics were risk factors for low birth weight in the study areas. Husband educational status, place of ANC visits, previous obstetric complications, maternal weight during pregnancy and gravidity were significantly associated with low birth weight. Nutritional counseling during ANC visits for pregnant mothers and health information about obstetric complications should be advocated. Health professionals should be vigilant in early detection and management of complications during pregnancy. Additionally, efforts should be done to improve living standard and lifestyles of mothers. Community based studies are needed to better address household and environmental factors with observation.S1 Table(DOCX)Click here for additional data file.S1 File(SAV)Click here for additional data file.


The pilonidal cyst is an infection of the skin and the subcutaneous tissue,secondary to a chronic inflammation with a greater frequency in thesacrococcygeal region, and associated to the presence of hair. The treatmentis eminently surgical. To demonstrate the endoscopic treatment of pilonidal cyst. Prospective study with 67 patients who had as surgical indication thediagnosis of pilonidal cyst. They were submitted to a surgical procedurefrom June 2014 to March 2018. The equipment used was the Meinerofistuloscope, a shutter, a monopolar electrode, a brush and endoscopicforceps. Of the 67 patients, 67% (n=45) were male and 33% (n=22) female, with a meanage of 25 years (17-45). Surgical time in average was 40 min (20-120) andmean healing time of four weeks (3-12). Surgical complications werepresented in 7% cases (n=5) and recurrences in 9% (n=6). The endoscopic treatment of the pilonidal cyst is feasible and presents goodsurgical results.  Pilonidal cyst is a well-known skin and subcutaneous tissue disease, occurringpredominantly in men with a mean age of 30 years and an incidence of 26 cases per100,000,,The treatment is essentially surgical, with a wide variety of techniques includingremoval of the cyst by means of flap procedures, as seen in the modified Karydakisand Limberg,The minimally invasive endoscopic treatment of pilonidal cyst (EPSiT) proposed byMeinero et alThe objective of this study was to demonstrate the effectiveness of minimallyinvasive endoscopic treatment.This study was approved by the research ethics committees in the Argentinian andBrazilian institutions, and the patients provided the informed consent form beforethe surgical procedure.This is a prospective study, carried out from June 2014 to March 2018, comprisingpatients with symptomatic pilonidal cyst who were admitted to Rosario ProvincialHospital in Santa Fe, Argentina, and Santa Izabel Hospital in Salvador, Brazil.The endoscopic technique was performed according to the method idealized byMeinero et al. (2014)The procedure begins with the identification and characterization of cystextension, as well as secondary cavities by insertion of the fistuloscope withinfusion of glycine or mannitol into the spontaneous opening of the cyst B. The cyThe characteristics of the patients and the results obtained are shown in Between June 2014 and March 2018, 67 patients were selected, of which 67% were menand with a mean age of 31 years (17-45). The surgical procedure lasted on average 40min; the patients were discharged on the same day after the procedure and the meanhealing time was four weeks (3-12).Major complications were not observed; however, five cases had minor complicationssuch as prolonged bleeding and pain. The cure rate was 91%, and five patients hadrecurrence, and no other case of treatment failure or cyst persistence.Although pilonidal cyst was described more than 150 years ago,In this scenario, Meinero et alThe endoscopic technique for the treatment of pilonidal cyst causes lesspostoperative pain, faster healing and less time to return to daily activities. Inaddition, it is highly efficient in cases of cyst recurrence.Endoscopic treatment requires shorter operative time compared to excision methods;Limberg’s flap technique takes an average of 54 min, while that of KarydakisThe endoscopic technique has advantages over the less invasive ones that areperformed blindly, which explains the greater occurrence of relapses. Endoscopictreatment is favored by the observation of the interior of the cyst, allowing thesurgeon to identify the location of the hairs, as well as damaged tissues,contributing to the higher success rateThe time required for healing after the EPSiT technique was lower than other surgicalapproaches, presenting even fewer complications. According to Bernier et al.(2015)The complications associated with EPSiT treatment observed in this study were 7%,with self-limiting bleeding in three patients and two reports of pain for aprolonged period, requiring the use of analgesics. No patient demonstratedcomplications such as necrosis or seroma during follow-up. Prolonged pain requiringanalgesics was described in two (22%) patients by Chia et al (2015)According to Umesh et al (2018)Among the several treatments for the pilonidal cyst, the EPSiT technique presentsitself as a safe alternative; however, its use depends on specific equipment, whichmay limit itDodaro and Renda (2014)This technique, pioneered in Brazil and Argentina, represents a safe and reproduciblealternative for the treatment of the pilonidal cyst, also allowing the patient toresume his daily activities in a short period of time and in a more aesthetic way,as it results in few scars when compared to other treatments.Endoscopic treatment for pilonidal cyst treatment demonstrated great safety andefficiency. The technique offers benefits such as good results, reduced recoverytime, and low rate of complications.