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python3 -c " import pdfplumber with pdfplumber.open('/home/daytona/workspace/attachments/27cec14d-3802-4868-8f84-2904403e2891/31dabec9-a53d-4c03-a5da-43c68c5a7831.pdf') as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): text = page.extract_text() print(f'--- PAGE {i+1} ---') print(text) print() "

I've read the full study guide. The PDF contains 8 MCQs on Fluid & Electrolyte Balance (Nursing). Let me run them as a mock test - I'll present each question one by one. But since this is a text-based interface, I'll present all 8 questions for you to attempt, then reveal answers with explanations.

🩺 Mock MCQ Test: Fluid & Electrolyte Balance

Topic: Fundamentals of Nursing | For: RRB / SGPGI / Nursing Officer Exams Total Questions: 8 | Time suggested: ~8 minutes

Q1. The percentage of water in the average young adult human body is approximately?

A) 40%
B) 50%
C) 60%
D) 70%

Q2. An older adult is at higher risk for dehydration than a middle-aged adult because:

A) They have more muscle mass.
B) They drink very little fluid.
C) Their body is almost 80% water.
D) Their compensatory mechanisms work less efficiently.

Q3. Which of the following is the most abundant cation in the extracellular fluid?

A) Potassium
B) Sodium
C) Calcium
D) Magnesium

Q4. A patient has a serum sodium level of 128 mEq/L. Which clinical feature would the nurse expect?

A) Intense thirst
B) Lethargy and confusion
C) Dry mucous membranes
D) Hypertension

Q5. What is the specific antidote for severe hypermagnesemia?

A) IV Furosemide
B) IV Insulin
C) IV Calcium Gluconate
D) Oral Magnesium supplements

Q6. Which assessment finding indicates fluid volume excess (hypervolemia)?

A) Weak, thready pulse
B) Decreased BP
C) Crackles on auscultation
D) Poor skin turgor

Q7. Insensible fluid loss occurs through which routes?

A) Kidney and bladder
B) Skin and lungs
C) Intestines and kidney
D) Skin and kidney

Q8. Normal serum osmolality range is:

A) 100 - 150 mOsm/kg
B) 275 - 295 mOsm/kg
C) 300 - 350 mOsm/kg
D) 400 - 450 mOsm/kg

Reply with your answers (e.g., "1-C, 2-D, 3-B...") and I'll score you and explain each answer in detail!

1-c,2-d,3-a,4-d,5-c,6-c,7-b,8-b,

📊 Mock Test Results: Fluid & Electrolyte Balance

Your Score: 6 / 8 (75%) ✅

Detailed Answer Review:

Q1. Percentage of water in a young adult body?

Your answer: C) 60% ✅ CORRECT
Young adults = 60% body weight is water. Simple benchmark to remember.

Q2. Why are older adults at higher risk for dehydration?

Your answer: D) Their compensatory mechanisms work less efficiently ✅ CORRECT
Aging impairs thirst sensation, kidney concentrating ability, and hormonal regulation (ADH response) - all reduce the body's ability to compensate for fluid loss.

Q3. Most abundant cation in extracellular fluid?

Your answer: A) Potassium ❌ INCORRECT
Correct answer: B) Sodium (Na⁺)
Remember: Na⁺ is the king of ECF - 98% of body sodium stays outside cells. Potassium is the major cation of intracellular fluid (ICF). This is a very common exam trap!
📌 Trick to remember: "Na⁺ = Outside, K⁺ = Inside"

Q4. Patient with serum Na⁺ = 128 mEq/L (Hyponatremia) - expected finding?

Your answer: D) Hypertension ❌ INCORRECT
Correct answer: B) Lethargy and confusion
Na⁺ < 135 = Hyponatremia → water shifts INTO cells → cerebral edema → neurological symptoms (confusion, lethargy, seizures, coma).
Intense thirst and dry membranes = Hypernatremia signs. Hypertension = seen in hypervolemia/Cushing's - not hyponatremia.
📌 Trick: Low Na⁺ = brain swells = neuro symptoms (confused, lethargic, seizures)

Q5. Antidote for severe hypermagnesemia?

Your answer: C) IV Calcium Gluconate ✅ CORRECT
Calcium directly antagonizes the cardiac and neuromuscular effects of excess magnesium. Same antidote is used in magnesium toxicity during eclampsia management.

Q6. Assessment finding in hypervolemia (fluid excess)?

Your answer: C) Crackles on auscultation ✅ CORRECT
Excess fluid leaks into the lungs (pulmonary edema) → crackles on auscultation. Weak pulse, low BP, and poor skin turgor are all hypovolemia signs.

Q7. Routes of insensible fluid loss?

Your answer: B) Skin and lungs ✅ CORRECT
Insensible = losses you cannot directly measure. Sweat (skin) ~600-800 mL/day and respiration (lungs) ~400-600 mL/day. Urine = sensible (measurable) loss.

Q8. Normal serum osmolality?

Your answer: B) 275 - 295 mOsm/kg ✅ CORRECT
This is a fixed value to memorize. Values >295 indicate hypertonic state (dehydration); <275 indicate hypotonic state (overhydration).

📈 Performance Summary

#	Topic	Result
Q1	Body fluid % - young adult	✅
Q2	Older adult dehydration risk	✅
Q3	Major ECF cation	❌
Q4	Hyponatremia signs	❌
Q5	Hypermagnesemia antidote	✅
Q6	Hypervolemia sign	✅
Q7	Insensible fluid loss	✅
Q8	Normal serum osmolality	✅

🎯 Key Takeaways for Weak Areas:

ECF vs ICF ions - Na⁺ dominates ECF, K⁺ dominates ICF. This distinction appears in almost every nursing exam.
Hyponatremia vs Hypernatremia signs - Low Na⁺ = neuro symptoms (brain swells). High Na⁺ = thirst + dry membranes (brain shrinks).

Great attempt! Would you like another round of MCQs or a deeper review of any topic?

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python3 << 'EOF' from reportlab.lib.pagesizes import A4 from reportlab.lib import colors from reportlab.lib.units import mm from reportlab.platypus import (SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, HRFlowable) from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle from reportlab.lib.enums import TA_CENTER, TA_LEFT from reportlab.platypus import KeepTogether import os os.makedirs('/home/daytona/workspace/fluid-electrolyte-card', exist_ok=True) output_path = '/home/daytona/workspace/fluid-electrolyte-card/Fluid_Electrolyte_Quick_Reference.pdf' # ── Colour palette ────────────────────────────────────────────────── NAVY = colors.HexColor('#1A3557') TEAL = colors.HexColor('#1B7F8E') ORANGE = colors.HexColor('#E87722') LIGHT_BG = colors.HexColor('#EEF4F8') YELLOW_BG = colors.HexColor('#FFF8E7') RED_LIGHT = colors.HexColor('#FDE8E8') GREEN_BG = colors.HexColor('#E8F5E9') GRAY = colors.HexColor('#555555') WHITE = colors.white MID_GRAY = colors.HexColor('#DDDDDD') doc = SimpleDocTemplate( output_path, pagesize=A4, leftMargin=12*mm, rightMargin=12*mm, topMargin=10*mm, bottomMargin=10*mm ) styles = getSampleStyleSheet() def S(name, **kw): return ParagraphStyle(name, **kw) title_style = S('Title', fontSize=17, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER, spaceAfter=2) subtitle_style = S('Sub', fontSize=9, textColor=colors.HexColor('#CCE0FF'), fontName='Helvetica', alignment=TA_CENTER, spaceAfter=4) section_style = S('Sec', fontSize=9, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER) body_style = S('Body', fontSize=7.8, textColor=colors.HexColor('#222222'), fontName='Helvetica', leading=11) bold_style = S('Bold', fontSize=7.8, textColor=NAVY, fontName='Helvetica-Bold', leading=11) small_style = S('Small', fontSize=7, textColor=GRAY, fontName='Helvetica', leading=10) bullet_style = S('Bullet', fontSize=7.5, textColor=colors.HexColor('#222222'), fontName='Helvetica', leading=11, leftIndent=8, firstLineIndent=-8) red_bold = S('RedBold', fontSize=7.8, textColor=colors.HexColor('#C0392B'), fontName='Helvetica-Bold', leading=11) green_bold = S('GreenBold', fontSize=7.8, textColor=colors.HexColor('#1B6B3A'), fontName='Helvetica-Bold', leading=11) def section_header(text, bg=TEAL): data = [[Paragraph(text, section_style)]] t = Table(data, colWidths=[186*mm]) t.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,-1), bg), ('TOPPADDING', (0,0), (-1,-1), 4), ('BOTTOMPADDING', (0,0), (-1,-1), 4), ('LEFTPADDING', (0,0), (-1,-1), 6), ('RIGHTPADDING', (0,0), (-1,-1), 6), ('ROUNDEDCORNERS', [4]), ])) return t def mini_header(text, bg=NAVY, width=186*mm): data = [[Paragraph(text, S('mh', fontSize=7.5, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER))]] t = Table(data, colWidths=[width]) t.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,-1), bg), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 4), ])) return t story = [] # ══════════════════════════════════════════════════════════ # TITLE BANNER # ══════════════════════════════════════════════════════════ title_data = [[ Paragraph('Fluid & Electrolyte Balance', title_style), Paragraph('Quick Reference Card', title_style), ]] title_table = Table(title_data, colWidths=[110*mm, 76*mm]) title_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,-1), NAVY), ('TOPPADDING', (0,0), (-1,-1), 8), ('BOTTOMPADDING', (0,0), (-1,-1), 8), ('LEFTPADDING', (0,0), (-1,-1), 8), ('RIGHTPADDING', (0,0), (-1,-1), 8), ('SPAN', (0,0), (0,0)), ('VALIGN', (0,0), (-1,-1), 'MIDDLE'), ])) story.append(title_table) sub_data = [[Paragraph('Fundamentals of Nursing | RRB / SGPGI / Nursing Officer Exams | June 2026', subtitle_style)]] sub_table = Table(sub_data, colWidths=[186*mm]) sub_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,-1), TEAL), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ])) story.append(sub_table) story.append(Spacer(1, 4*mm)) # ══════════════════════════════════════════════════════════ # ROW 1 : TBW | Compartments # ══════════════════════════════════════════════════════════ # --- TBW table --- tbw_head = Table([[Paragraph('TOTAL BODY WATER (TBW)', S('h', fontSize=7.5, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER))]], colWidths=[89*mm]) tbw_head.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),TEAL), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3)])) tbw_rows = [ [Paragraph('Age Group', bold_style), Paragraph('% Body Wt', bold_style), Paragraph('Risk', bold_style)], [Paragraph('Infant (<1 yr)', body_style), Paragraph('80%', red_bold), Paragraph('HIGHEST', red_bold)], [Paragraph('Young Adult', body_style), Paragraph('60%', body_style), Paragraph('Baseline', body_style)], [Paragraph('Older Adult', body_style), Paragraph('55%', body_style), Paragraph('Higher', body_style)], ] tbw_table = Table(tbw_rows, colWidths=[38*mm, 26*mm, 25*mm]) tbw_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,0), LIGHT_BG), ('BACKGROUND', (0,1), (-1,1), RED_LIGHT), ('ROWBACKGROUNDS', (0,2), (-1,-1), [WHITE, LIGHT_BG]), ('GRID', (0,0), (-1,-1), 0.4, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 5), ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'), ('FONTSIZE', (0,0), (-1,-1), 7.5), ])) tip1 = Table([[Paragraph('📌 60 kg adult ≈ 40 L total body fluid', small_style)]], colWidths=[89*mm]) tip1.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),YELLOW_BG), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3), ('LEFTPADDING',(0,0),(-1,-1),5), ('BOX',(0,0),(-1,-1),0.5,ORANGE)])) # --- Compartments --- comp_head = Table([[Paragraph('FLUID COMPARTMENTS', S('h', fontSize=7.5, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER))]], colWidths=[93*mm]) comp_head.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),TEAL), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3)])) comp_rows = [ [Paragraph('Compartment', bold_style), Paragraph('% TBF', bold_style), Paragraph('Cation', bold_style), Paragraph('Anion', bold_style)], [Paragraph('ICF (inside cells)', body_style), Paragraph('70%', body_style), Paragraph('K⁺', red_bold), Paragraph('Phosphate', body_style)], [Paragraph('ECF (outside cells)', body_style), Paragraph('30%', body_style), Paragraph('Na⁺', green_bold), Paragraph('Cl⁻', body_style)], ] comp_table = Table(comp_rows, colWidths=[38*mm, 15*mm, 22*mm, 18*mm]) comp_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,0), LIGHT_BG), ('ROWBACKGROUNDS', (0,1), (-1,-1), [RED_LIGHT, GREEN_BG]), ('GRID', (0,0), (-1,-1), 0.4, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 5), ('FONTSIZE', (0,0), (-1,-1), 7.5), ])) tip2 = Table([[Paragraph('📌 Na⁺ = Outside (ECF) | K⁺ = Inside (ICF) — 98% each', small_style)]], colWidths=[93*mm]) tip2.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),YELLOW_BG), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3), ('LEFTPADDING',(0,0),(-1,-1),5), ('BOX',(0,0),(-1,-1),0.5,ORANGE)])) row1 = Table([[[tbw_head, tbw_table, tip1], [comp_head, comp_table, tip2]]], colWidths=[93*mm, 97*mm]) row1.setStyle(TableStyle([ ('VALIGN', (0,0), (-1,-1), 'TOP'), ('LEFTPADDING', (0,0), (-1,-1), 0), ('RIGHTPADDING', (0,0), (-1,-1), 4), ('TOPPADDING', (0,0), (-1,-1), 0), ('BOTTOMPADDING', (0,0), (-1,-1), 0), ])) story.append(row1) story.append(Spacer(1, 3*mm)) # ══════════════════════════════════════════════════════════ # ROW 2: Transport Mechanisms | Fluid Balance # ══════════════════════════════════════════════════════════ trans_head = Table([[Paragraph('TRANSPORT MECHANISMS', S('h', fontSize=7.5, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER))]], colWidths=[89*mm]) trans_head.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),NAVY), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3)])) trans_rows = [ [Paragraph('Process', bold_style), Paragraph('Movement', bold_style), Paragraph('ATP?', bold_style)], [Paragraph('Diffusion', body_style), Paragraph('Solute: High → Low', body_style), Paragraph('No', body_style)], [Paragraph('Osmosis', body_style), Paragraph('Water: Low solute → High solute', body_style), Paragraph('No', body_style)], [Paragraph('Filtration', body_style), Paragraph('Fluid: High press → Low press', body_style), Paragraph('No', body_style)], [Paragraph('Active Transport', body_style), Paragraph('Solute: Low → High', body_style), Paragraph('YES', red_bold)], ] trans_table = Table(trans_rows, colWidths=[32*mm, 42*mm, 15*mm]) trans_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,0), LIGHT_BG), ('ROWBACKGROUNDS', (0,1), (-1,-1), [WHITE, LIGHT_BG, WHITE, LIGHT_BG]), ('GRID', (0,0), (-1,-1), 0.4, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 5), ('FONTSIZE', (0,0), (-1,-1), 7.5), ])) osm_tip = Table([[Paragraph('📌 Normal Serum Osmolality: 275 – 295 mOsm/kg', small_style)]], colWidths=[89*mm]) osm_tip.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),YELLOW_BG), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3), ('LEFTPADDING',(0,0),(-1,-1),5), ('BOX',(0,0),(-1,-1),0.5,ORANGE)])) # Fluid I/O fio_head = Table([[Paragraph('FLUID INTAKE & OUTPUT', S('h', fontSize=7.5, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER))]], colWidths=[93*mm]) fio_head.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),NAVY), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3)])) fio_rows = [ [Paragraph('Route', bold_style), Paragraph('Volume', bold_style), Paragraph('Type', bold_style)], [Paragraph('Kidney (Urine)', body_style), Paragraph('Major portion', body_style), Paragraph('Sensible', green_bold)], [Paragraph('Skin (Sweat)', body_style), Paragraph('600–800 mL/day', body_style), Paragraph('Insensible', red_bold)], [Paragraph('Lungs (Resp.)', body_style), Paragraph('400–600 mL/day', body_style), Paragraph('Insensible', red_bold)], ] fio_table = Table(fio_rows, colWidths=[35*mm, 34*mm, 24*mm]) fio_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,0), LIGHT_BG), ('ROWBACKGROUNDS', (0,1), (-1,-1), [WHITE, LIGHT_BG, WHITE]), ('GRID', (0,0), (-1,-1), 0.4, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 5), ('FONTSIZE', (0,0), (-1,-1), 7.5), ])) daily_tip = Table([[Paragraph('📌 Daily intake: 2300–2800 mL | Insensible = skin + lungs', small_style)]], colWidths=[93*mm]) daily_tip.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),YELLOW_BG), ('TOPPADDING',(0,0),(-1,-1),3),('BOTTOMPADDING',(0,0),(-1,-1),3), ('LEFTPADDING',(0,0),(-1,-1),5), ('BOX',(0,0),(-1,-1),0.5,ORANGE)])) row2 = Table([[[trans_head, trans_table, osm_tip], [fio_head, fio_table, daily_tip]]], colWidths=[93*mm, 97*mm]) row2.setStyle(TableStyle([ ('VALIGN', (0,0), (-1,-1), 'TOP'), ('LEFTPADDING', (0,0), (-1,-1), 0), ('RIGHTPADDING', (0,0), (-1,-1), 4), ('TOPPADDING', (0,0), (-1,-1), 0), ('BOTTOMPADDING', (0,0), (-1,-1), 0), ])) story.append(row2) story.append(Spacer(1, 3*mm)) # ══════════════════════════════════════════════════════════ # ROW 3: Hypovolemia vs Hypervolemia # ══════════════════════════════════════════════════════════ story.append(section_header('FLUID VOLUME IMBALANCES', ORANGE)) story.append(Spacer(1, 1.5*mm)) imb_rows = [ [Paragraph('System', bold_style), Paragraph('Hypovolemia (Deficit)', S('hv', fontSize=7.8, textColor=colors.HexColor('#C0392B'), fontName='Helvetica-Bold')), Paragraph('Hypervolemia (Excess)', S('hve', fontSize=7.8, textColor=colors.HexColor('#1B6B3A'), fontName='Helvetica-Bold'))], [Paragraph('Cardiovascular', body_style), Paragraph('↑ Pulse (thready), ↓ BP, ↓ CVP', body_style), Paragraph('Bounding pulse, ↑ BP, ↑ CVP, distended veins', body_style)], [Paragraph('Respiratory', body_style), Paragraph('Tachypnea, dyspnea', body_style), Paragraph('↑ Rate + Crackles on auscultation', body_style)], [Paragraph('Renal', body_style), Paragraph('↓ Urine output (oliguria)', body_style), Paragraph('↑ Urine output (polyuria)', body_style)], [Paragraph('Skin / Integument', body_style), Paragraph('Dry skin, poor turgor (tenting), dry mouth', body_style), Paragraph('Pitting edema, pale & cool skin', body_style)], [Paragraph('Neuro', body_style), Paragraph('Confusion, dizziness', body_style), Paragraph('Confusion, headache', body_style)], [Paragraph('Lab Values', body_style), Paragraph('↑ Osmolality (>295), ↑ Hct, ↑ BUN, ↑ Na⁺, ↑ Urine SG (>1.030)', body_style), Paragraph('↓ Hct (dilution), ↓ BUN, ↓ Na⁺, ↓ Urine SG', body_style)], ] imb_table = Table(imb_rows, colWidths=[28*mm, 79*mm, 79*mm]) imb_table.setStyle(TableStyle([ ('BACKGROUND', (0,0), (-1,0), LIGHT_BG), ('BACKGROUND', (1,1), (1,-1), colors.HexColor('#FEF5F5')), ('BACKGROUND', (2,1), (2,-1), colors.HexColor('#F0FBF4')), ('ROWBACKGROUNDS', (0,1), (0,-1), [WHITE, LIGHT_BG, WHITE, LIGHT_BG, WHITE, LIGHT_BG]), ('GRID', (0,0), (-1,-1), 0.4, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 5), ('FONTSIZE', (0,0), (-1,-1), 7.5), ('VALIGN', (0,0), (-1,-1), 'MIDDLE'), ])) story.append(imb_table) story.append(Spacer(1, 3*mm)) # ══════════════════════════════════════════════════════════ # ROW 4: Electrolyte Imbalances (Na + Mg) side by side # ══════════════════════════════════════════════════════════ story.append(section_header('ELECTROLYTE IMBALANCES', NAVY)) story.append(Spacer(1, 1.5*mm)) def electrolyte_block(title, normal, low_name, low_val, low_causes, low_sx, low_mgmt, high_name, high_val, high_causes, high_sx, high_mgmt, width): hdr_s = S('es', fontSize=7.5, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER) cell_s = S('ec', fontSize=7, textColor=colors.HexColor('#222222'), fontName='Helvetica', leading=10) bold_cell = S('eb', fontSize=7, textColor=NAVY, fontName='Helvetica-Bold', leading=10) col = width / 3 rows = [ [Paragraph(f'{title} Normal: {normal}', bold_cell), '', ''], [Paragraph('Parameter', bold_cell), Paragraph(f'{low_name} {low_val}', S('rh', fontSize=7, textColor=colors.HexColor('#C0392B'), fontName='Helvetica-Bold', leading=10)), Paragraph(f'{high_name} {high_val}', S('gh', fontSize=7, textColor=colors.HexColor('#1B6B3A'), fontName='Helvetica-Bold', leading=10))], [Paragraph('Causes', bold_cell), Paragraph(low_causes, cell_s), Paragraph(high_causes, cell_s)], [Paragraph('Signs/Sx', bold_cell), Paragraph(low_sx, cell_s), Paragraph(high_sx, cell_s)], [Paragraph('Management', bold_cell), Paragraph(low_mgmt, cell_s), Paragraph(high_mgmt, cell_s)], ] col_w = [col*0.65, col*1.175, col*1.175] t = Table(rows, colWidths=col_w) t.setStyle(TableStyle([ ('SPAN', (0,0), (2,0)), ('BACKGROUND', (0,0), (-1,0), TEAL), ('BACKGROUND', (0,1), (-1,1), LIGHT_BG), ('BACKGROUND', (1,2), (1,-1), colors.HexColor('#FEF5F5')), ('BACKGROUND', (2,2), (2,-1), colors.HexColor('#F0FBF4')), ('GRID', (0,0), (-1,-1), 0.4, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 4), ('VALIGN', (0,0), (-1,-1), 'TOP'), ('FONTSIZE', (0,0), (-1,-1), 7), ])) return t na_block = electrolyte_block( 'SODIUM (Na⁺) — Major ECF Cation', '135–145 mEq/L', 'Hyponatremia', '< 135 mEq/L', 'Vomiting, diarrhea, diuretics, SIADH, Addison\'s disease, excess hypotonic IVF', 'Confusion, lethargy, seizures, coma (cerebral edema); Nausea, vomiting', 'IV: 0.9% NS or 3% NS (slowly); Oral: increase salt', 'Hypernatremia', '> 145 mEq/L', 'Excess intake, DI (Diabetes Insipidus), fever, Cushing\'s syndrome, hyperventilation', 'Restlessness, irritability, seizures; Intense thirst, dry mucous membranes', 'IV: 0.45% NS (hypotonic); Oral: encourage free water', 90*mm ) mg_block = electrolyte_block( 'MAGNESIUM (Mg²⁺) — Neuromuscular & Cardiac', '1.7–2.4 mg/dL', 'Hypomagnesemia', '< 1.7 mg/dL', 'Malnutrition, vomiting, diarrhea, diuretics, hyperglycemia, celiac disease', 'Tachycardia, HTN; Seizures, paresthesia, twitching; +Trousseau\'s & Chvostek\'s; Tall T waves', 'Replace Mg²⁺ orally or IV', 'Hypermagnesemia', '> 2.4 mg/dL', 'Kidney failure, excess Mg²⁺ antacids or laxatives', 'Bradycardia, hypotension; Muscle weakness, absent DTRs; Wide QRS, prolonged PR', 'Antidote: IV Calcium Gluconate; Diuretics', 96*mm ) elec_row = Table([[[na_block], [mg_block]]], colWidths=[93*mm, 97*mm]) elec_row.setStyle(TableStyle([ ('VALIGN', (0,0), (-1,-1), 'TOP'), ('LEFTPADDING', (0,0), (-1,-1), 0), ('RIGHTPADDING', (0,0), (-1,-1), 3), ('TOPPADDING', (0,0), (-1,-1), 0), ('BOTTOMPADDING',(0,0), (-1,-1), 0), ])) story.append(elec_row) story.append(Spacer(1, 3*mm)) # ══════════════════════════════════════════════════════════ # EXAM MEMORY TRICKS BOX # ══════════════════════════════════════════════════════════ trick_title = Table([[Paragraph('⚡ HIGH-YIELD EXAM MEMORY TRICKS', S('tt', fontSize=8, textColor=WHITE, fontName='Helvetica-Bold', alignment=TA_CENTER))]], colWidths=[186*mm]) trick_title.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),ORANGE), ('TOPPADDING',(0,0),(-1,-1),4),('BOTTOMPADDING',(0,0),(-1,-1),4)])) story.append(trick_title) tricks = [ ('Na⁺ vs K⁺ location', 'Na⁺ = Outside (ECF) | K⁺ = Inside (ICF) — 98% rule'), ('Hypo vs Hyper Na', 'Low Na⁺ → brain SWELLS → neuro symptoms (confusion, seizures) | High Na⁺ → brain SHRINKS → thirst, dry membranes'), ('Mg antidote', 'Hypermagnesemia antidote = IV Calcium Gluconate (blocks cardiac/neuro effects)'), ('Insensible loss', 'Skin + Lungs = Insensible | Urine = Sensible (measurable)'), ('Hypervolemia sign', 'Fluid excess → fluid in lungs → CRACKLES on auscultation'), ('Dehydration risk', 'Infants (80% water, immature kidneys) > Older adults (55%, poor compensation) > Young adults (60%)'), ('Hyponatremia link', 'SIADH & Addison\'s → Hyponatremia | Cushing\'s & Diabetes Insipidus → Hypernatremia'), ] trick_rows = [[Paragraph(f'{k}', S('tk', fontSize=7.5, textColor=NAVY, fontName='Helvetica-Bold', leading=11)), Paragraph(v, S('tv', fontSize=7.5, textColor=colors.HexColor('#222222'), fontName='Helvetica', leading=11))] for k, v in tricks] trick_table = Table(trick_rows, colWidths=[40*mm, 146*mm]) trick_table.setStyle(TableStyle([ ('ROWBACKGROUNDS', (0,0), (-1,-1), [YELLOW_BG, WHITE]), ('GRID', (0,0), (-1,-1), 0.3, MID_GRAY), ('TOPPADDING', (0,0), (-1,-1), 3), ('BOTTOMPADDING', (0,0), (-1,-1), 3), ('LEFTPADDING', (0,0), (-1,-1), 6), ('VALIGN', (0,0), (-1,-1), 'MIDDLE'), ])) story.append(trick_table) # Footer story.append(Spacer(1, 3*mm)) footer = Table([[Paragraph('Fluid & Electrolyte Balance Quick Reference Card | Fundamentals of Nursing | For RRB / SGPGI / Nursing Officer Exams | © 2026', S('ft', fontSize=6.5, textColor=WHITE, fontName='Helvetica', alignment=TA_CENTER))]], colWidths=[186*mm]) footer.setStyle(TableStyle([('BACKGROUND',(0,0),(-1,-1),NAVY), ('TOPPADDING',(0,0),(-1,-1),4),('BOTTOMPADDING',(0,0),(-1,-1),4)])) story.append(footer) doc.build(story) print(f'PDF created: {output_path}') EOF

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Fluid Electrolyte Quick Reference

PDF Document · PDF

Here's what's packed into the single-page A4 card:

Section	Content
Total Body Water	Age-group table (Infant/Adult/Older) with risk levels
Fluid Compartments	ICF vs ECF - %, major cations & anions
Transport Mechanisms	Diffusion, Osmosis, Filtration, Active Transport + ATP requirement
Fluid Intake & Output	Daily volumes, sensible vs insensible routes
Fluid Volume Imbalances	Side-by-side Hypovolemia vs Hypervolemia across 6 systems + labs
Sodium Imbalances	Hypo/Hypernatremia - causes, signs, management
Magnesium Imbalances	Hypo/Hypermagnesemia - causes, signs, antidote
Memory Tricks	7 high-yield exam mnemonics (including your two missed questions!)

Color-coded: red for deficit/low states, green for excess/high states, orange for exam tips.

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