Prediction of Caesarean Section delivery Data

Published: 31 October 2025| Version 1 | DOI: 10.17632/txpzxdbmns.1
Contributor:
Fatima Auwal Aliyu Tafoki

Description

The dataset comprises records from 1,163 observations, capturing various maternal health indicators, including age, blood pressure, blood sugar, body temperature, heart rate, and pregnancy history. The average age of participants is 29 years, ranging widely from 2 to 70 years, suggesting that the dataset includes a diverse population, possibly from very young to older mothers. In terms of blood pressure, the mean systolic pressure is 113 mmHg and the mean diastolic pressure is 76 mmHg, with respective standard deviations of 18 and 14. The central tendency (median) of systolic pressure is 120 mmHg, and that of diastolic pressure is 80 mmHg, indicating that most individuals fall within the normal blood pressure range. However, the maximum values of 200 mmHg (systolic) and 130 mmHg (diastolic) point to cases of hypertension among some participants. The average blood sugar level is 8 mmol/L, with a minimum of 6 mmol/L and a maximum of 60 mmol/L, showing the presence of extreme outliers that may represent gestational diabetes or poorly controlled glucose levels. Body temperature is relatively stable, averaging 98°F, with minimal variation (standard deviation of 2). This suggests that most participants had normal body temperatures during data collection. The average heart rate is 74 beats per minute (bpm), ranging between 7 bpm and 90 bpm. The very low minimum value (7 bpm) may indicate a recording or data entry error, as such readings are physiologically implausible. Lastly, the number of previous pregnancies (Gravida) ranges from 0 to 9, with a mean of 2, showing that most women had few previous pregnancies, while a few had many, indicating high variability in reproductive history within the dataset.

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Steps to reproduce

The data used in this study were collected retrospectively by reviewing patient paper records and manually entering the relevant information into a structured Google Form designed for data capture. The variables extracted included maternal age, blood pressure (systolic and diastolic), blood sugar level, body temperature, heart rate, and number of previous pregnancies (gravida). Data were collected from existing hospital records, ensuring that only complete and clearly documented cases were included.

Institutions

  • Kaduna State University
  • Kaduna State Government

Categories

Maternal Health, High-Risk Pregnancy, Childbirth, High-Risk Childbirth, Hospital Delivery

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